Techstrong TV – February 27, 2025

Ladies and gentlemen in this corner, the Once and Future Champion of ai, IBM, you're watching Textron Gang. Hey, everyone. Happy, uh, Thursday to you.

It's been a crazy week. It's Thursday already. I, I just, it's flying by.

So much news, so much going on that the chaos just keeps spinning round and round. Um, but we've got a lot to go over today. I teased it a little bit upfront, uh, big news from IBM in, in the AI space, but I don't know how much of it, well, there's a lot of it.

That's ai, but there's more to it than ai. But we're going to get into that. We've got that, we've got Google what's going on with them and, uh, some things.

And then we, we, interestingly, we, we, we found some people with a conscience in the, uh, department of Government efficiency. I thought they, they purged all those people. But anyway, let's first introduce our panel.

Who's gonna discuss these matters today? I'm gonna start off out west, uh, with our Silicon Valley eye in the sky. Jon Swartz.

John, how are you? I'm doing well. I'm, uh, it's a crazy news cycle as you just mentioned, Alan, so we're just trying to keep our head above water.

All, all one. I think a lot of people are in that boat, John. Yep.

Just trying to, not just tech. Yes. Yep.

Trying to keep your head above water. Moving from there, I guess we'll go down to Austin, Texas, where preparations are underway for South by Southwest. We hear it's our own and a whole ward, and good to have you.

How's everything? Always a pleasure. It's wonderful, beautiful sunny weather here.

Couldn't be happier with that. And preparations are well underway for South by Southwest. Be You've been exercising your liver.

It be a Good one. It's gonna be a good one. Sorry, I said, have you been exercising your liver?

I, I need to find another one. I need to get a donor probably by the end of the week, but It'll be a good time. Good for you.

Moving up to you. Uh, Ohio, where she's back from, her recent trip to New York. She's our editor for Textron ai, gestalt it and more coming down the pike.

Sulagna Saha Saha. Hi Sagner. How are you?

Hi, Ellen. I'm good, thank you. Good.

It's great to have you. Thank you. Uh, yeah.

Okay. And then finally the Dean of Harrison, our chief content Officer, Mike Vizard. How are you?

Dean Harrison is in Westchester County, otherwise known as the central of all things IBM, because well just about everybody here who's in I Tech seems to work for IBM. Yes. The old Armon.

So Armon isn't Westchester, is it? It, it's it's one county North Putnam, but, uh, well, actually Armon is in Westchester. It's, um, I forgot the other town.

They used to be where they had the big pyramid building that they abandoned a couple years ago. Hmm. Okay.

I always thought it was Putnam, but could be. Yeah. I mean, certainly, I mean, here look down here in Boco is a big IBM town too, right.

Months five. They Have a huge office in presence in Austin as well. Yeah.

And San Jose, California, they had the Coddle Road, uh, labs where my dad worked for 20 years. Yeah. I mean, they look, they're IBM They're everywhere.

Yeah. They Were for more than a hundred years. Um, but some big news out of IBM Mike, why don't you kick us off with this?

All right, let's jump in here At IBM bought Data stacks, which originally cut its name on this, uh, open source Cassandra NoSQL database. It was more of a higher performance database than your average document database. And it got a solid following.

And then data stacks extended its reach into vectors and their ability to use that as a foundation for training, uh, models. And then they also built a, um, a more elegant alternative to lang chain, which you can use for training the models. And it's one of the lang chain being widely used open source tool, but it's a little cumbersome.

So Data Stacks has this alternative. John, you wrote this story, but what are they saying in the Valley about all this? Because, you know, here at one point IBM was supposed to be, you know, the next overlord, right.

And Watson in jeopardy. And then, uh, suddenly they were chasing everybody. I think the same, and I think the same applies to Silicon Valley.

They're almost an, I mean, I hate to say this, given the presence that I just mentioned that they had in San Jose for so long, they were the tech company here. They're an afterthought in the valley. They're rarely talked about.

Um, they have a presence, but it's tucked up in the hills in Northern San Jose. Um, in a sense, when we talk about the AI race, IBM is rarely mentioned here in the only references to Watson. Um, and that's from years ago.

So the, this idea that IBM is, is acquiring data stacks is interesting. I mean, it's a move by IBM to kind of turbocharge its Watson X portfolio and kind of make this, make the use of gen generative AI within enterprises kind of accelerate that. Um, it's, it's importance.

It's just, you know, Mike, it's here. It's so interesting the way things develop here. And this is not so much about IABM, but about just the perception of companies.

Here they are. The hot company for a few years, like IBM was then my Microsoft was the anti IBM, and then Google became the anti Microsoft. Apple is the anti-everything.

They, they have their runs. And I would even venture to say that a company like IBM is starting to get a little long in the two, excuse me. A company like Apple is starting to get long in the tooth and being considered kind of an older fuddyduddy type of company versus the upstarts.

So the, unfortunately that's the culture here, the new shiny object. So the announcement by IBM is interesting. It will have an impact, I would assume, among some of the customers that already use data stacks and financial services.

But for the most part, it's kind of under the radar. Um, I mean, it's a, it's a, it's a data grab, right? I mean, it's, it's the AI gold rush for data.

Um, I have nothing but good things to say about IBM because they were very good to me. I was in their futurist program for a very long time. They flew me around the world, uh, to just try products and tweet about it.

It was really fun. Um, but I think being cool in Silicon Valley is, is something that I used to care about and I don't anymore. It's very freeing.

But I mean, it's a, it's, it's essentially the future. You're living in the future when you live in Silicon Valley, and that means a lot of sacrifice to your day-to-day life. It also means that you're a startup or you're nothing.

And so I, I don't think that that's really necessarily a gauge of success. IBM has had the staying power, uh, uh, beyond any other tech company. And this just shows you how they plan to continue to evolve and survive.

We, You, you know, the one thing I was gonna mention too is the, um, the idea that Silicon Valley reminds me, you, you spark this man of Hollywood, you know, you're hot, you're in, and then you're discarded until you come back and do something again. So there are all sorts of companies and individuals who are the person of the moment who went away. So staying power is really important.

And I, you're right, IBM has been around for more than 110 years. I think I remember doing one of those a hundred year stories years ago. It's, it, it, it's, it's interesting.

But, and again, in the, in the big picture, the frame of things, this is kind of a small piece. I don't mean to undersell it, but I, that's basically a perception here at least. So, so I'm scared Mike ahead.

No, Mike, you go. So the thing with IBM is they, they obsess about the monetization and rightfully so. But what happens is, is every time they do something new or interesting, or they acquire it, they shove it in this kit bag that they give to IBM consulting, who then goes down and visits all these enterprises and, you know, integrates all that stuff into these global 2000 companies.

And that's the business model. And so that's why every time they acquire something or they do something innovative, it just kind of falls by the wayside. Because when it comes to actually implementing it, there isn't really a push to build a platform and invite developers.

And I mean, they talk about doing that stuff, but they, on the execution side, they just blow it every time. 'cause they're kind of obsessed with being a consulting company at the end of the day. In fact, they, uh, just unveiled their AI integration consulting services, uh, around agent tech ai, which is supposed to help companies, uh, impact generative AI more safely and expedite the adoption just yesterday, I think.

Uh, but I feel like IBM may be onto something. I know they got leapfrogged a bunch of times, even though they were first really one of the first people in the AI race. Um, so I think with their, lately with their efforts around what's next, uh, their AI product portfolio and, uh, and the data stack acquisition.

And then, uh, with the data stack acquisition announcement, they also announced, uh, an agreement with the REA there, the new, uh, Saudi airline company that they're integrating what's next into their operations. And, uh, and with the upcoming MWC Barcelona in March, I hear that AI is going to be a big, uh, area of focus. Um, so IBM claims that their AI journey started back in, you know, uh, nine in the 1950s when the programmed the seven four mainframe computer with the, to play chess and wherever.

Um, but, um, really, and, uh, with IBMI feel like that this company has touched literally every milestone technology in the tech space for over a hundred years. Like punch cards, PCs, uh, mainframe. And, uh, I feel like they're more gearing up for the ai, uh, uh, revolution, uh, than before.

Um, like, uh, and like all big companies and that, that have skin in the game, the vision is to embed AI across the board, which may not necessarily be, uh, like, uh, the most, uh, distinctive strategy. But I feel like that, uh, they have done a few things lately, which shows that they are sort of, uh, going to be a part of the decidedly be a part of the a ISI mean, we saw at Hot Chips last year, they announced, uh, that, uh, they were, uh, turbocharging the next generation of Z mainframe, uh, with the tell two processor and, uh, spray accelerators. Um, um, and those chips are coming out this year, hopefully.

Um, yeah. So it appears that they are vying for, uh, the top, not the top spot maybe, but at least be in a shoulder to shoulder with, uh, the big companies that are in the AI race. So, let me weigh in here.

It is interesting, John, you know, public perception and not just Silicon Valley public perception, but broader public perception. Let's compare three companies. You've got IBM, which is you said has about 110 years old.

You have Microsoft recently celebrated its 50th birthday. Apple is is about the same, isn't it? 50, yeah, 50 in April.

Yep. Apple is also 50. And let me just throw another one in for the, for grins and giggles.

Google, right? Google's probably, what about 2002? 2003, 2001, something like that.

Um, so let's say 25 years, half the age of the other two perception, Google is still perceived as an 800 pound gorilla controlling the markets. It plays in. And as an innovator, apple, apple is having an innovation problem, an innovation dilemma right now where the, the market is saying, where's the innovation?

We haven't really seen innovation since Steve Jobs passed away. Microsoft say what you want, but Satya Nadella has reenergized that company, and they are perceived, they, they were out in front with OpenAI. They, you know, that investment was probably the best 10 billion they ever put in.

Um, you know, and they, so they are, and they're, you know, second in cloud and all of these things. So even though they're 50 years old, they're, they, they've reinvented themselves a little bit. IBM as says punch cards, the birth of the pc.

The, the first time we started thinking of AI was real was Watson and the chess game, and all of these things. They have a hundred year history of leading innovation. Uh, the, the power PC chip, they don't get enough credit for that.

When we look at what ARM is today and all of that, it, I mean, look what they did for, for, for those chips, the non-Intel chips, uh, mid-range, you know, mid frame, mid-range computers, mini computers, so many innovations that come out of there. Exotic materials, quantum computing, there's still a leader there. But the mo, the MO is their first with these things.

They're out ahead because they do plow money into r and d and give them credit, and they do buy and acquire a lot of companies give them credit. But somewhere along the way, as Mike says, those accomplishments go outta the hype cycle, not necessarily into the trial of disillusionment, but they, they level out and you don't see them. And part of it is because they're not necessarily, like Broadcom does this too.

They're not necessarily looking for new customers. They just wanna go deeper into the customers they already have. And so the customers they already have say, Hey, do you have the IBM AI built into your stuff?

Yeah, I think so. My IBM guy put it in, or whatever, or, you know, they talked about it. So kudos to IBM for being able to kind of surf that wave all of these years.

But I think the key to their success is not necessarily surfing the fastest, the highest or the hardest. It's, it's staying right in the, you know, in the top, in the top right quadrant of the pack, but not necessarily in the lead. Now, I do want to talk a second about data stacks though.

'cause I'm a startup guy. And let's give a big shout out to the data stacks people you want to talk about pivoting and reinventing yourself, right? These were a big data company with, with Cassandra, right?

No sequel database. Jumped on the Vector database bandwagon early on when, you know, companies, frankly like Mongo, that had a Vector database solution, didn't realize they what to do with it. And, and they went that route with the Vector database and then took it the next step.

And now they're being sold here as a, an AI company. You know, there's OpenAI, there's, there's, uh, you know, anthropic and data stacks. Where did they become an AI company?

But I'm sure they got anyone with enough data as an AI company at this point. Exactly. Everybody's an AI company.

Like we're all AI engineers. So I didn't see what they paid for data stocks. I don't know if any of you have.

Yeah, but I didn't like here, you know, on the grapevine or anything, but I'm sure it was a pretty penny. This wasn't a, uh, a fire sale. And, um, congratulations to the Data Stacks team.

That's what startup culture is all about. Good for you guys. Now we'll see what happens to them as part of Big Deal.

So The one thing I, I would add to that, and I remember having this conversation with IBM marketers and I was like, why don't you market these platforms and these technologies? And, and they explained it this way and they said, fundamentally, we're marketing IBM people and expertise and all the other things are enablers for that. And so, but they lead with all, you know, if you're here in New York, you can't go anywhere without running into an IBM ad.

But they're all the same. They're all about, you know, somebody at IBM has some expertise that you need, But I wonder how much NDL has changed that, You know, I was gonna mention, can I mention something that, that, that happened with Genie Romit, Gina Jeanie Romit, um, just to give you an insight behind the curtains, when this company IBM was doing interesting things, as Mike said, they're almost treated like a consulting company out here. And again, maybe it's because they're an, an East Coast based company that seems to have some sort of humility, which is lacking out here.

But the one thing that was interesting was that Ginny Remit would always submit to USA today when I worked there as a tech editor, she would submit these columns to explain what they were doing because their marketing was kind of under, was kind of ho hum. And, and they had, they would try to work out a sweetheart deal with our editor in chief to, to run some of her commentary. And I would sometimes say, this is, you know, b******t.

This is propaganda. We ran it more often than not. But that gives you an idea that even they acknowledged that they weren't getting the message through.

So, ndl come back to that for a minute. 'cause it is significant, right? So when they spun out ndl, they really put all their like, tech support managed services stuff in there, but they kept IBM consulting with the main company, which allegedly is a quote unquote software company these days.

'cause it has higher valuations. But, you know, point of fact is the route to market is still through those consultants. Fair enough.

And Another another reason I feel like, uh, why it does not IBM does not come up as one of the most frequently named names, uh, at least in the AI conversation, is because, so they put like eight years behind Watson, but got eclipsed by Chad Chip. And also a bigger reason is that their share prices did not move much. At least, uh, their AI revenue was not, you know, through the roof or anything.

So that didn't get, No, they never figured out how to monetize Watson. I remember being at IBM think 10, 12, 10 years ago, and they were showing me like dating AppSec built on Watson that would find you better dates and stuff like that. But they just think they did it.

They, you know, they were out there and they, they kind of missed that one. But, hey, Hey, one last thing on that. You know, who else we talk about a lot less these days?

Who? Red Hat. Red Hat who?

Red Hat, who they've been, they've been, you know, bored. We will be assimilated. They've been assimilated, they're now Red Hats who wear red ties with blue suits.

Isn't that the uniform? Um, anyway, hey, let's take a break. We're gonna come back.

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Hey folks, we're back. And we're talking about a lawsuit actually involving Chegg, which is a publisher of medical information and they're suing Google over their AI summarization capabilities. And it's interesting, I'm not quite sure what the legal grounds are, but one of the claims that they're making is that this AI summarization capabilities hollowing out the internet and the knowledge thereof, because it's just summarizing everything.

And if you watched a previous episode of Textron Gang, we talked about whether or not AI was making us all stupid. And this is part of that kind of conversation. But the question then becomes, um, is this, Anne, we'll start with you, is this kind of shift here with these ai, uh, summarizations gonna ultimately wind up killing all the companies that create the content, and then therefore we won't have anything on the internet that's worth looking at anyway.

So, Well, great question. I would argue that content creators were already under siege. Monetizing based purely on traffic has been a business model that's been failing for some time.

I mean, you remember when people used to make money from ads, from banners, banner traffic, skyscraper ads, that, that's been leveled out. Um, I think it's interesting because to me, as an SEO keep in mind this is what I do all day every day. It's not really that different from Google answers, Google answers, you know, where it asks a question and it answers it.

The, this is sort of just a rehashing of that. Um, but I think that the, the, the crux of the lawsuit is that Google is eroding the demand for original content, which I don't actually agree with. I I don't think that AI generated summaries necessarily reduce the need for people to read and want more information.

Does it give them at a glance, does it give them a link? Yes. Um, undermining publishers, publishers' abilities to compete was another point, which I, I think is probably a fair point to make because they are essentially taking snippets of it and benefiting from it.

So I think that the perplexity model is a little more democratic, where they're brokering partnerships with New York Times and other big publishers and saying, Hey, let's, let's work out a financial arrangement. Google doesn't really do that. Um, any arrangements they make with Twitter, LinkedIn, um, you know, these social media sites that they've done for years have all been sort of quiet partnerships, right?

Uh, I like the fact that perplexity discloses, but you're talking about 120 million searches, uh, a month versus 130 billion, right? So, so the economies of scale aren't there. Um, but the other argument was that they're creating a hollowed out information ecosystem basically, that it's gonna lead to a decline in quality and trustworthy information.

Well, can we put that at Google's door? It wasn't that happening anyway, with disinformation and other things happening. Are they making it worse?

Probably. Um, I think that a lot of publishers are been outta shape because of the drop in traffic. Uh, but that could happen with an algorithm change that could happen with a lot of other things.

It just so happens that AI has become a boogeyman for these sites because their business models are failing. Are they justified? Probably.

Um, I do think that we need to value free and fair press. We need to value information and the ability to, to find good information. Do we want Google doing this for us?

No. But again, it's not that new. It feels new, but it's not, um, because of the Google answers that's been around for a long time, and this is just a sort of more prominent way of doing that.

It's a little more at a glance. You don't have to toggle it. Um, but I don't Think anybody Knew where Google answers was.

So that's, Yeah, Google answers are where you see it, it's question and then you click, yeah. So 30 to 50% of searches at this point in time, and it, it varies based on the study you read, 30 to 50% have AI overviews, so this isn't even rolled out to all searches. So we have to think about what is the impact gonna be once that full rollout happens and it, and they're adding countries every month.

Um, so what is that gonna do globally to information? I don't know. But it's something that's being very closely watched and studied.

And I don't think this is the last lawsuit we're gonna see. I think we're gonna see even more of these because it, it's essentially taking co-opting information that is not theirs and presenting it as theirs is essentially, I think really, really not untrue. I think that they were fair in stating that.

So let's cut the crop. This isn't about AI per se. This is about the M word monopoly.

Google has a strangle hold on, people searching for information on the internet. And for the 25 plus years that they've been doing it, they did it in conjunction with most content publishers in the world, including Textron. Because in exchange for their being able to spider our sites and we want all of our information, and we're gonna put it in as Google friendly of format as we can and publish site maps and all of these things so that Google can get all of that.

The quid pro quo there was then when people search certain terms that are germane to us, our sites would rank or would show up hopefully in the top three, if not the first page. And people would come to these sites to consume that content and get that information. They didn't get the information per se at Google.

They found out where to get the information from Google. And so companies, publishers, like a tech strong and, and similar, were getting 75, 80, 80 5% of their traffic from what we call organic search Google search. 'cause they rep represent 98% of the 99% of the market.

Now, starting with Google Answers, which was clunky and not as elegant maybe as the AI stuff is now Gemini, Google made a concerted effort to say, we don't wanna lose that traffic. We don't wanna send that traffic to other people's sites. We want to keep that traffic here so we can serve them ads so we could gather more information about them so we can do what we do to monetize these things.

Right? And it, this didn't start with ai Anne, you're right. We, we've seen a steady erosion of traffic from organic search for a couple years now.

Um, but the quid pro quo is still there. Well, if you are not gonna send me traffic, don't use my information because you are now monetizing my information without my permission. And the same way we're mad at OpenAI and we laugh at OpenAI talking about deep seek using open AI's information when OpenAI didn't pay for that information either.

Well, I got news for you. Google didn't either. I I would say Gen Z millennials, they're, they're less interested in using Google search.

Uh, You're right, TikTok and Instagram under, yeah, Yeah. The under 30 crowd is more statistically likely to search TikTok for local search than Google. And that's because that experience is better.

So there, there, the empire is crumbling a little bit, and this may be a move to counteract that. Uh, but they're still the giant, I mean, they're still the one that this book I wrote about SEO for O'Reilly is still, I mean, I say in the beginning, I hope it's not always about Google and that was 2017. And yet here we are still talking about Google.

So, so every action has an opposite reaction and everybody who creates content is gonna start putting up registration walls and putting up stuff to prevent you from getting to that content without actually going through then to get to it. And I, that's just gonna be the natural order of things. 'cause to Alan's point, the quid pro quo is gone.

So no quid, the pro is gonna go somewhere else. If you're making money from your content, it is generally going to be from something other than just directly people viewing said content. It's gonna be you talking about it on Instagram.

It's gonna be you using affiliate links as an influencer. If you're a stand, you know, a a rogue person like me, I have a business, right? I have an agency that I sell my services, right?

So I'm not monetizing directly from content I put out there. So that model, I dunno if That makes you rogue, Anne, that that's a harsh word. Well, I've worked for myself for 15 years, so I, I guess that's pretty rogue.

But, but the, the point is that making money from just putting out good content as an individual, as a small outfit, there's some concession you have to give, you have to do conferences, you have to do, you know, just making it on its own is not something that has been viable for a minute. And we can blame Google for that, I think to a large extent. But, um, I don't know, can we put the, all of this there at their door?

I don't know. Yeah, it Just seemed all Inev inev, um, go ahead, sag Now. Um, yeah, I was saying that it's really not new.

'cause every time Google changes its algorithm sites get pushed to the back pages, some even get indexed, and then there's this obvious drop in engagement and traffic. But, uh, what I think is really harting some of these publishing companies is the fact that, uh, with the Google over AI overview, so the, the key purpose of AI overview is to provide quick answers and save, uh, users browsing time. And so that way com uh, users would just simply, uh, read, like, browse through whatever the AI summaries are and probably would not go to the page that actually has the original information.

But to make matters worse, these answers are unverified and often inaccurate. We, we all remember the, the glue on pizza and Roday keeps a doctor away answers from last year. And uh, yes, Google has done a series of changes.

And, uh, to be fair, Google AI alone is not Jan. You know, Chad Chip wasn't that great either early on. Uh, but the key issue here is that Google or o OpenAI or whatever company is doing AI search, they're harnessing publishers original content who, uh, which they put money and years into to create, uh, uh, to generate these summaries that are not even reliable.

So that going forward is definitely going to be a problem. And, uh, that's probably what their point is. Uh, the publishers who invite you to go Google in 2023.

And, uh, there has been a slew of, uh, litigations lately based on, in and around this, uh, area. I absolutely, you're correct. And I think if I could make a prediction here, I think, you know, the reason I always bring up perplexity is that it is time-based.

It is reputation based. It's LLM plus index. The future of search is not going to be indexed as Google has so heavily relied upon.

And so this is a sort of clunky way that they're trying to essentially enter LLM into index and to mix them. And, and the mix isn't necessarily good, but I think the future of search is absolutely going to be, uh, coming from AI agents. I think we're gonna see more and more search.

I'm seeing search G-G-G-P-T, I'm seeing Bing show up in the top 10 and sites that I'm optimizing. That's never happened. And that's exciting to me.

So there, there's hope. No there isn't. Plexity has just given me a citation.

It doesn't drive any traffic to me. It's a very nice little salute as they drive by and steal my content. So they're known better than anybody else just because they waved at me and said, thank you.

They do chain of thought, though. They do show you how they get to the conclusion, which is helpful. You, you know, we talked about legacy, going back to IBM, we talked about legacy and the legacy of, of Google was always to not be like IBM and to do know evil.

And as Alan mentioned earlier, the M word monopoly. I mean, this is no, not surprising what happened with the algorithm changes at the expense of content creators. I mean, there's a duopoly between Google and Meta in terms of advertising, which is all but killed the fourth estate.

So, you know, this is part of their leg, this is part of their legacy and it needs to be put out there. Uh, I'll tell you what I am looking forward to, that I will no longer have to care about. It's called SEOA lot of time and effort spent on optimizing sites for Google traffic that I'm not, probably not gonna spend nearly as much time being worried about.

If you're only thinking about Google, you've already lost searches everywhere. Searches, searches in everything we do on every platform we use. Spoken like a true SCO, rogue Warrior.

Rogue Warrior, SEO, battlefield, TSEO, battlefield. Thank you, Anne. All right, let's take a break.

We're gonna come back and, and handle our third block today. Uh, some surprising resignations over at Doge. Is it Doge or do, do, uh, who the hell knows you are watching?

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Hey folks, we're back in this. Alan alluded to, there are some conscientious objectors have emerged that dos, which I'm kind of surprised about. I thought that they'd all been weeded out.

But, uh, a couple of federal employees with technical expertise basically put out a joint letter saying that they would no longer quote unquote, participate in the dismantling of democracy in its services. Alan, I know we've talked about this subject in the past, but is this gonna be a larger trend? Will other government agent employees kind of stand up and say, you know what, we're not doing this either, and maybe we're on the verge of something that feels like a general strike.

I don't know. Viva La France. Um, so first of all, I thought they checked that you can only have a black heart if you worked at dots.

You, you couldn't have a conscience. I guess not. They must have inherited some legacy folks.

They did. They did. These, these people were, were already there as USDS employees and they had come from Amazon and Google.

So I just wanted, can I just put that out there? Because these people are actually trying to do their job and they just got, they're basically felt like they were forced out. Yeah, I mean, look, we see what's going on here, guys, right?

You, you don't use a blunt instrument where you need a scalpel. And so when you do things like that, the, the results are what the results are going be here. And I do think it's only a matter of time.

You know, I was reading an article today, you know, the governorship in Virginia is up for election this year in November, right? Lot of federal folks down in Virginia losing their jobs and feeling this pain. Not that the governor of Virginia has done such a great job.

What's his name? Helen Kin or whatever. Um, I think we are gonna start seeing the manifestations of this chaos, of this dismantling of America, right?

We're gonna start seeing when people start voting. Yeah, I would say that, uh, to give credit on the other side of that governor conversation, the governor of New York said she's excited that there's a bigger pool of talent to hire from. And she's inviting all those doge people and laid off government workers to apply for jobs in the state of New York.

Yeah, these were, uh, engineers, data scientists, product managers, designers, they're talented people. Um, and they got thrown under the, the ages of, of Musk, who, you know, is the worst boss ever. So, uh, more power to them, you know, they also were at reacting to, uh, layoffs of, of their peers.

There were 40 layoffs just before that. And plus these individuals were being questioned about their political loyalties as part of their job, which is just absolutely absurd. But then again, we are, we're used to this Now It's almost hys, isn't it?

So in a, in a lot of ways though, this kinda resembles how layoffs often get handled in private companies, right? What typically happens in a lot of organizations, especially the larger ones, is somebody comes up with a number and says, we're gonna cut 5%. And then, you know, who gets cut is just generally Time out, not time out, time out.

Don don't even go there. Don't go, this is not a 5% cut. These are people doing searches looking for things like diversity or inclusion.

And if it has that word in it, they cut you out. Whether it's 2%, 5% or 50% has nothing to do with that. They are, they are.

This is a political hit list kind of, uh, campaign here, right? Is, this is not your company wide, we gotta cut 10%. They're, they're targeting specific enemy list and specific kinds of programs that they deem not in, in line with their worldview.

Let, let's not, let's not give them the dignity of, of comparing it to something like that. This is a, this is a hack with a machete, right? This is This.

Yep. So This is a political cut that has To have no doubt about it. Claiming is their number.

Right? Right. What take the, the USAID thing, you think there was a percentage they wanted to cut outta that?

No, they think that we're done giving food to people and, and, and, you know, and they cover it by telling us it was all based on condoms for Palestine or whatever. Come on. It is nonsense.

It's nonsense. This is a political hatchet job. And when the people wake up must, I mean, he, go ahead.

I'm sorry, John. He's using The Yeah, he, he Musk is using the same playbook that he did at Twitter, right? He gets, gets rid of the people that he thinks are politically infused.

Uh, he, but in this case, I, I sometimes think you give him too much credit. I think they're just blindly cutting like wild. I mean, it's, it is precise in terms of certain people, but I also think they're not, this is just like a wild free for all and slashing, right?

I don't think they're putting a lot of thought. I forgot what agency it is, but they cut 'em one week and had to hire 'em back the next week. 'cause they figured, Oh no, there was nothing important.

It was just the nuclear engineers, no big deal. I Mean, they, you got, they got, they got so drunk with power that they, they've cut so many people that they realize, oh, wait a second, we can't run that operation now. And then you're seeing this in these town hall meetings.

It's just incredible pushback because services are being denied. But I mean, this is part and parcel of, of their crazy plan. And then they're not complying, you know, the, the courts are saying, no, you have to do these things and they're not doing it.

Look, I mean, there's 14 states pushing legislation to stop Elon and what he's doing. I don't know how successful they will be, but I expect after an attack, there will be a counter attack. This is America.

We're not gonna take this lying down. We're gonna fight for what we believe in. And, and yes, it's gross, and yes, it, it's undignified, but it's also part of the democratic process.

And I think democracy is going to see the greatest test seen, you know, since its inception. I, I really do. And, and I'm ready to fight for what I believe in.

You know, I'm not gonna just sit and read news and get mad. I'm gonna do something about it. I'm gonna lobby, I'm gonna, I'm gonna maybe even go to a demonstration.

I don't know, I'm kind of scared of public anything. So I, I was in New York get cut. I was in New York, I'm gonna do what I can Do.

Yeah, no, I was in New York this week and down Broadway, and it was freezing out. But down Broadway came a demonstration of hundreds of people chanting, Hey, hey, ho ho, Eric Adams must go. Right?

And, and stopped the immigration. And because what happened there was a travesty. I, you know, I've had friends reach out to me and say, Hey, on Textron gangster, we talk about politics or politically charged subjects.

And I think we have adu and to your point, we have a duty to, because history shows us, if you sit back quietly and as you say, read the news, you're a collaborator at Nuremberg. The, I was following orders, defense didn't hold water. And I'm not saying these are Nazis, so we're not going there right now yet.

But you can't sit by quietly. You, if you are a patriot, you have a duty to speak up for what you believe in. John.

Oh, I don't think we have a choice, actually, because the people that we cover are part of this movement. They are part and parcel of aiding and abetting what's going on. And they are, uh, enriching themselves.

And in the process, we don't have a choice. We have to write about This has Its accurately. Yeah.

Tech has its mitts all over this big tech does. Oh my God. Yes.

It's all the, the oligarchs are, are, you know, they're leading the, this, this anti revolution. They're, they're, they're is engorging themselves, Right? So part of the issue, though, and there was a good report on this in CBS news two days ago, and they went and they interviewed a bunch of folks in various small towns, and they were all convinced that, you know, the government was inefficient, it was wasteful, and they didn't have a lot of sympathy for these people being cut.

So it wasn't something that they were riled up about. And I have to wonder if part of that is maybe the government agencies just need to do a better job of explaining what they do to people so they understand and they value it. Because right Now, no, but you know what, Mike, this is the opposite of NIMBYs.

Until it's in their backyard, they don't give a crap. But when their daughter got fi gets laid off, or their, or their son all of a sudden can't go to school, or, or their milk goes bad, or their farms go bad in the field, then all of a sudden stuff hits the fan. Now what the heck's going on?

Right? That's, that's the nature of the beast until it hits home, it's always good to point to the next guy. Oh, yeah.

Those people are inefficient. Is government inefficient? Yeah.

Is it almost by design? Yes. Is it the best of the worst form of government that we've ever had on this planet?

Yes. Right. And so you, you know, you, if you're okay throwing babies out with bath water, go ahead.

Right? But that's, that's what's going on here. So, and, and, and, you know, we'll, we shall see where the chips fall to Anne's point, right?

This is still America, I think. And I think we still Have democracy. We still have checks and balances.

It does not, people in, I don't care what map they show you, all of those people in those little towns don't equal all those people in cities and suburbs and so forth, where, where most of 80% of our population lives. And, and as a wise man once said, you know, just throw stones. Make sure that, that you're not living in that glass house because they'll come back the other way.

I always, I have to think about what my late father, he used to always say in these situations, pigs get fat, hogs get slaughtered. Yeah. Yes.

All right. But hey, more power to those conscientious folks who, who showed they do have a conscience and a heart and, and stood up for what's right. So we need more of that in America.

Um, guys, if that's it, I think we're going to call a wrap on this version of the Textron Gang. I can't wait to see what we talk about tomorrow. It's Friday.

Um, and Sagner, John, Mike, thanks for joining me. I'm Alan Shimel. You've just watched Textron Gang.

Stay tuned. We have a full text on TV schedule for you coming right up till then We're out. This is Techstrong tv.

Hey everyone. You know, one of the nice things about doing what I do at Techstrong and a Techstrong TV is, yeah, I've had the chance to be in this industry, whether it's through Techstrong or some of the companies I've worked with are co-founded for a really long time. And along the way I've had the opportunity and the pleasure of meeting some real gentlemen, some really fine people, whether they're men, women, what have you.

Uh, this next guest is, is one of those people. He is my friend, Roger Barranco. Roger.

Roger. And I know each other probably 10 years or more, uh, maybe more thinking back. And, uh, then all that time as I, as I say, he's been one of the fine people you meet in the, in this, in the industry, in the cyber world, currently Vice president, global security operations with Akamai.

And he's, he's probably been at Akamai now, always 10, 12 years. I'll ask him. Let me introduce you to Roger.

Hey, Roger, Barranco, how are you man? It's great to have you on Again, Alan, it's so good to see you again, buddy. You know, I, I, It's been too Long.

It has been. I I remember walking through data centers with you and saying, this is the cloud, right? Essentially, uh, when it was, you know, what, 15 plus years ago, even, uh, when that was, uh, in is comparative infancy right in around It.

Yes, it was, it was private cloud and it was just, you know, you were running things in VMware, multi-tenant VMware. That was, that was basically it. That Roger, how long are you at Akamai now?

It's gotta be 12 years. No. Yeah.

You know, if you include the acquisition of Prolexic from, uh, my, uh, it's a little over 12 years. That's 'cause I, of course, we knew Prolexic. I remember Akamai buying it.

For those who don't know, Prolexic at the time of their acquisition by Akamai was probably the preeminent DDoS protection Cool. And company in the world. And, and Akamai bought them.

And they've been thwarting some of the biggest DDoS attacks ever since. Um, now of course, Roger, you moved above and beyond that, as I said, global, uh, security operations vp, you know, Roger. But give people a sense of, I mean, you've had a distinguished career.

Give them an idea of, of where you've been and how you got here. Yeah, sure. You know, um, for anybody on here that's looking at security, wow, it's still cutting edge.

Uh, how do you differentiate yourself? If you're looking for a job at a career, it's clearly security. It's always changing, it's always exciting.

Uh, it's invigorating to think, Hey, you know, we're, we're protecting the world's most critical infrastructure from nation state actors from, you know, really well e equipped, uh, cyber criminals, uh, across the board. So, you know, uh, if you're into an environment that's always changing and interesting, uh, this is it. So, Roger, I'm gonna ask you to do a little Akamai kind of setting the, the field a bit.

A lot of people out here think of Akamai and I, I think they fall in two camps. Some people say, oh, Akamai, they're a security company. Right?

Probably the minority of people, though I think most people still think of Akamai, and it's part of their original mission, if you will, which was, you know, current commonly CDN content delivery network. They, and of course, and, and, and I don't wanna ppo CDNs, right? Right.

In a world where latency counts, and if we can get you to the edge next to where you're gonna access, if we can get information and, you know, content to the edge where you're gonna access it quicker, that's a huge plus. And that's a very, very important mission. But Akamai is so much more than a CDN security is, but one of of many things that Akamai delivers today.

How would you describe Akamai? So you're right. The, the CDN is the foundation from which many of our solutions sit on top of it, which makes it very powerful because of the size and capacity of the platform and how close we are to the actual end user that needs those services.

So, mixed in with security, you get great performance. It's really rare to have those two things together in the same package, right? So, but you're absolutely right.

Um, the fact that the foundation is CDN, the reality is that well over 50% of Akamai's revenue is security. And it's security across a plethora of products. From API to bot management to DDoS, like you mentioned before, clearly waf, uh, it, it's extremely deep and broad, uh, which is sometimes one of the challenges, right?

It's to think of, well, what are all the different situations and challenges that we can help with? But layering it in with the right tool for the job Is, is key to it. And that, you know, not to be flippant, but as you get older, you learn it's all about having the right tool for the job, right?

It really is. It makes life a lot easier all around. Um, so we've, we've laid out sort of the Akamai story.

Roger, you guys recently came out with the Defender's Guide, right? Right. Give a, and, and over the years we've featured Akamai security research and you know, our friend Martin McKay for many years was writing the, uh, Akamai reports.

Martin, of course, has moved on stuff now, but, uh, what's this defender's guide? Is it the latest incarnation of this? Tell us about it.

I I really like the evolution of the Defender's Guide. So we used to call it the Sodi, the state of the Internet. It was a wonderful document that contained a lot of metrics in what we're seeing, and we do see the bulk of the world's internet traffic that's clean.

Uh, so we're well positioned to talk to these data points from our findings quite literally along the way. But the, um, so d has evolved to the Defender's Guide because we said, Hey, we wanna make this more actionable. We, it just doesn't, you know, we don't wanna just contribute to the standard, you know, a lot of people or do the fear, uncertainty, doubt type discussions.

That's not who we are. We really wanna say, this is what we're seeing and this is how you can help yourself. And if you go to the Akamai website, it's, it's very prominent on there.

Uh, you can download that guide and it will talk to what we're seeing prominently from a cyber concern perspective and look quite literally what you can do to protect yourself along the way. Okay. Um, so give us, I mean, Roger highlights high, you know, yeah.

We only have 15 minutes and we've probably used seven of them already, Uhhuh. Sure. But, you know, arm people here.

What, what, what are the kinds of things they should be really digging into? One thing that I see all the time is that it, and it's exampled by the fact that the number one attack source is very consistently the us. So the attacker, the bad actors might be in Eastern Europe or somewhere in Asia or wherever that happens to be.

Why is that? Because the Americas are typically behind on patching. It's just that simple.

So just doing the basics, like patching is incredibly important. And I know it's really tempting to have deep discussions about Redtail, which is, you know, a malware that goes in and it takes over an infrastructure to, in a very intelligent way, um, participate in crypto mining, right? But the reality is, if you have a really good zero trust micro-segmentation environment in place, you're gonna be protected.

Uh, if in a very significant way. If you have strong API protections in place, aside from WAF protections, very different security protocol, you're gonna be a much better place to pull those items together. So what have we seen out there?

You know, it's pretty stunning to me that d believe it or not, Alan, I don't know if this is gonna surprise you or not. DNS attacks still make up 60% of DDoS Not, not surprised at all. Yeah.

9999% of the time. Right. I always leave a little sliver there, because there's always that super smart native state Actor something right Out there.

But, you know, I I, it's funny, the interview I did before you, Roger, was with a company that specializes, they're all former special spec ops people, Uhhuh digital, and they specialize in protecting high net worth individuals, celebrities, et cetera. And we were ta having this discussion. Some things never change in security.

And one of those things is, is that unfortunately people don't get religion until after the calamity happens. Right? Then all of a sudden they're looking for miracles, or they're looking for solutions and d os protection.

Today's a perfect example. You know, until, until you've been a victim, you just think it's fine being the zebra in the herd. They're never gonna pick on me.

And then one day that lion grab grabs you and it's like, oh, I should have done this. Right? Right.

And I don't know, I mean, maybe guides like this telling people sharing real world incidents, I don't know what it'll take for people to say, Hey, we've gotta be proactive about, because you're right. A DNS based DDoS attack today is, you know, that's like getting hit with a, with not even a bow and arrow, maybe a cross bow, right? It's, it could be lethal to your business, but there's really no reason in today's world that you should be susceptible to that, You know, the solutions are very inexpensive.

First of all. It's not like you need some massive infrastructure on that. There are some great people out there that, you know, can help with that solution.

Um, it, it, it, like I said, it's just, there's no excuse for it. And to, Alan, to your point, goes back to patching a little bit, is that the, to be a good internet citizen is critical because those are DNS servers that are being com not compromised, but taken advantage of. And that can be modified, you can change your settings, but very specifically, uh, you know, on the DDoS front where you're going, we just had a lot of customers from the, uh, Australia, New Zealand region, get absolutely hammered because of a political support statement they made, uh, related to the Israeli Palestinian, um, conflict.

And there were a lot of, uh, entities that were knocked over and absolutely crushed. And to your point, they, unfortunately, several of them, uh, for lack of a better description, had to learn the hard way. And they, they'd come to us and say, help us out, because this very fine product that they had in place with very strong AI and ML and, you know, language models and everything, did a good job on 99%, that 1% that it didn't do such a great job on it had no solution for.

So if I give advice to anybody, it's gonna be, Hey, you know, challenge your vendors and make sure that they have that human overlay that's absolutely critical for that consultative engagement to handle that 1%. Because in today's world where it's much less brick and mortar, wow is 1% is crushing. It's all Bottom line, all it takes, it's all it takes.

You know, you mentioned the magic word there with ai. I mean, you know, when I look at AI from a security point of view, it truly is a double-edged sword. Absolutely.

There's so many things we can do with AI that can make us better security pros that can raise our level of security posture, make us better protected. But at the same time, you know, it's the old story. The bad guys are not dummies, and they use it too.

And they're using it to be more effective to, to have better attacks, you know, find more attack surface. And any advice on that, Roger? Yeah.

You know, so two things. You're absolutely right because we see it all the time. The, the rate at which attacks shift when you put a mitigation in place is stunning.

Which is why the soc, the security operations team, has had to evolve and add people like data scientists and threat researchers directly into the security operations team. 'cause you don't have the time to escalate to engineering to see about background investigations anymore. No.

When you're protecting a customer. But the AI is making it, uh, very interesting. But I will tell you, Alan, at the end of the day, it's rare to find a truly novel, traditional attack.

It's always some variance of a line injection or a SQL injection or an API attack. If you put the basics in place to protect you, you will be in really good shape. And very quickly, every customer we have that spends a lot of time with us during peace time, when it does move to war time and they're under attack, it ends up being a really good situation for them.

5 terabit attack and here's all the detail on it, and they didn't even know they were attacked. That's perfect. That only happens because we're testing with them and working with them during peace time to prepare for that bad day.

Agreed. Agreed. Roger, we're about out of time, but for people who maybe want to grab the guys and, and, you know, get into it, what, what would, what's your best advice?

I know it's a long URL, we're not going give it to you 'cause no one's writing it down. But how, what's the best way to navigate to it? com, it'll be prominent on the homepage, just click on it and it'll gl guide them through.

It's really easy to access it and a wealth of actionable information. It always is. It's been one of the best reports on the internet for years and years.

Matt, Roger, next time you come up here, we'll do this in person in the studio, please. I'd like that very much. We're, we're 15 minutes from feno?

Yeah. Awesome. All right.

Vent. Roger Barranco, VP Global Security Operations, Akamai Technologies here on Techstrong tv. We'll be back with more interest a minute.

Stay tuned. ai video series. I'm your host, Mike Vizard.

Today we're with Arthur O’Connor, who's academic director for data Science at the City University of New York from the Professional studies organization as I understand it. And we are gonna be talking about, well, what's going on with all these AI models in particular, deep seek, which seems to have set everybody back, but no one's quite sure what's real and not real here. But Arthur, welcome to the show.

Thank you. Thank you for having me. As I understand it, deep seek, at least the folks who, uh, are behind the model claim that they found a less expensive way to train that model.

And, um, but also folks are saying that some of the guardrails were bypassed and some of the outputs are a little more, um, shaky than others. So what's your assessment of what's really going on here? Well, the, I think the development is a kind of a useful reminder of, uh, to all of us that, that, you know, artificial intelligence, particularly generative artificial intelligence, is not just about the number of parameters the size of the training data set, and the, you know, how many GPUs, uh, are you using in a enormous server farm that's consuming all kinds of energy.

It's really about how smart you are and how creative you are in designing, uh, the data. And certainly a lot of the, what is called these distilled models that, uh, R one represents is really about not just the size of the training data set, but the quality and the relevance of the dataset instead of scraping the whole internet. Yes, it's useful in learning the constructs of diction and language and how to form human-like sentences, but it's not particularly, the web is not particularly, uh, good at explaining, uh, complex logic or solving math equations.

Um, uh, and that's where if you start to focus on certain data sets are very high quality to use those design your parameters and your test timing through what's something called interference training, um, in addition to the initial supervised fine training and, uh, reinforcement learning, that that really can improve the quality of the output. So do you think for most organizations, they're gonna wind up focused more on these distilled models that are narrowly aimed at a particular use case, rather than everybody trying to make use of the largest language models in the world because, well, that's just a more expensive approach every time you invoke one of those directly, It's more expensive for the people developing the models. Uh, the, you know, the, the, there are literally hundreds and thousands of open source variants out there, which you can find on me, meite, such as HuggingFace, the real challenge for most organizations just to find out what's available, how they work, and most importantly, how they can be safely and effectively applied in their business process.

And that remains a major challenge because, um, you know, unlike, for example, data science, which is almost universally, uh, can be applied to just about any kind of field. So far, the current generation of, uh, generative AI tools have really been, you know, they perform some neat tricks and have been really good at certain things like visual creation or editing or writing code snippets, but it's been fairly limited to a, you know, mean a dozen or so use cases or business models, what have you. So it's really gonna take, uh, organizations some, uh, getting up to speed on kinda what's out there, what did they do, how much they cost, and how do you mitigate the risks of using these tools.

Things too that everybody's obsessing about is the GPUs that we use to train this model are maybe not the most costly GPUs in the world. And we're also starting to see people talk about things other than GPUs for both training and inference. So do we need to be smarter about what classes of processors we're using to train various types of models?

The success and the performance of R one, uh, that's the deep seek, uh, uh, model certainly confirms that, that it's, you know, not just about size, it's also about, you know, quality and creativity, creativity, how you use those things and how you architect that solution. How much expertise do we have about those types of, um, more advanced uses? I, I would say, but it seems to me a lot of the data science teams that I talk to, they kind of just run right to the most expensive GPUs and processors they can find.

And they have maybe a particular model and they're not really thinking through the implications of running this thing in a production environment. So who's gonna be smart enough in these organizations to kinda sort all this out? Well, Michael, you've hit upon one of the more interesting structural and cultural implications of the whole solution.

And that is that in most organizations, uh, are basically structured around the previous digital revolution. And so you have data science expertise sequestered in these, uh, centralized in these IT organizations that kind of have their own mysterious language and processes that are removed from the main line, uh, and the main business units. Um, and this generative AI revolution's really gonna require data science expertise to be mo far more diffused to not only maximize the benefit of using these tools, but also minimize the rather significant risks, uh, of, of the, of such tools.

And you are correct in the Silicon Valley high tech mindset that, you know, bigger and better and faster and more powerful is, you know, necessarily what you're going for. And in many cases, uh, it's not, there's lots of, uh, business people that, um, are, uh, IT people who are overwhelmed by the business unit saying, I want a large language model to do this, to do that. And it turns out that the business case would be far easier, better, and more cheaply solved by, you know, for example, a collaborative fil filtering model for personalization.

But everyone's wrapped up in this gen AI large language model, uh, that those important distinctions in that important knowledge is not sufficiently diffused in the organization. We need to rethink how those IT teams are organized then. 'cause historically we have yes, um, infrastructure and software developers, and now I'm throwing in a bunch of data scientists and there's security people and it takes a village to do anything.

So, um, how should the village be organized? Well, if it, it has to be, uh, sort of centralized and decentralized. So, uh, the expertise and the knowledge of understanding what data science techniques or what generative AI techniques works best for what use cases and at what cost and at what, you know, ROI, that needs to be more, that has to be ha decentralized.

Uh, but what needs to be centralized is this policies, procedures, and the architectural standards. Uh, because as, as mentioned before, you know, a lot can go wrong. Uh, you can some well-meaning individual trying to, you know, fine tune a model can wind up, uh, training the model, uh, on proprietary information that now is part of the model and part of the, you know, public, uh, knowledge base.

So there's some important guardrails to be put in. Uh, but as you probably know, most organizations still don't have policies and procedures. It's, it's, as I noted in my book, it's, it's kind of wally world.

And in that regard also, I don't think people really understand the degree to which maybe these models might drift over time and that which seems to be working perfectly fine, suddenly six months later is not. And do we have a process for kind of observing that, monitoring that and updating and replacing models when necessary? Sure.

Answer is no. Uh, on one hand, I think most users don't realize how powerful these models are. They still use them for, you know, summarization or text generation.

They don't realize that you can assign a role and you can ask it to figure out fairly complicated things with a fairly high degree of accuracy. But because they're not, you know, super users, they don't quite appreciate that. And at the same time, you have this sort of naive a or ignorance on just what you should put in a model and what you really shouldn't.

Or if you're gonna put in proprietary information, how do you use it in, for example, there's a concept called in context learning where you, uh, sequester that private information from the public domain. Well, maybe you have some insights, 'cause we've been talking about this in other interviews, but it seems like people are struggling a little bit with, um, a lot of the business processes that they want to use AI in are essentially deterministic. They need to be done the same way every time.

And gen AI does things differently almost every time. So that's a probabilistic outcome. How do I insert something that is probabilistic into a business process that is deterministic?

We're still trying to figure that out. Uh, all we know right now is that we have organizational structures and performance indicators for employees that are based on things like expertise and credentials in seniority. Whereas this revolution is all about the democratization of expertise so that, you know, the junior, uh, uh, user or employee can potentially have the same amount of expertise, subject matter expertise as the senior, uh, person.

And so this is really gonna upend the whole performance hierarchy in organizations at least has the potential to. And so we don't quite have the tools or structure in place to, to handle that. And, uh, I would point out a recent, um, art study issued this month actually in February, 2025 by, um, Microsoft and Carnegie Mellon.

And it did this study of these three hundreds or so knowledge workers and the results find that it, IM, you know, the ability to, they call it AI whisperer, the ability to know how to quite prompt or interrogate these models is actually becoming just as important as actual subject matter expertise. And it also finding that, that the use of these models actually decrease the employee, uh, critical thinking skills. Uh, so because of this phenomenon called cognitive offloading, meaning it's the risk of using GGI as is the calculator has done to our arithmetic skills as the smartphone has done to our memory of the phone numbers of our loved ones or what GPS tracking is doing to our sense of direction.

I'm not entirely sure whether that's a good thing or a bad thing. 'cause I could probably interview. Yeah.

Um, so how do I kind of navigate this all with some reasonable expectations? 'cause you see, there seems to be a disconnect. Every COI talk to is like, AI is gonna be awesome, change the world, and we're gonna be more profitable than ever.

And then when I get into the middle managers, they're kinda like, well, maybe, yeah, but it's sure not easy to operationalize this thing. Yeah, I I would not wanna be a CEO or, or a CTO, uh, of a large organization right now because, uh, they're, they're overwhelmed. They're, they're being, uh, you know, they're getting calls from the board of directors saying, well, why aren't we doing ai?

And, um, from people whose, you know, enthusiasm, um, and interest in, in the business model is, is certainly commendable, but whose knowledge of data science may not be quite up to snuff. And so they're put in the un envious position of explaining all this stuff. Uh, and we don't have an infrastructure, we don't have an organizational structure, and we don't have a performance employee performance metric, uh, to measure creativity and adaptability.

Uh, and so we're just sort of foundering right now. So what's your best advice to folks then about how to do this? Should I take everybody and put 'em on some sort of corporate retreat and say, this is what's real and not real?

Or are we just gonna stumble our way through this? Uh, both, uh, uh, we, we, we need to certainly most employees seriously need to upskill, uh, and, and get smarter and more knowledgeable about what these models can do. And I think for the average users, they'd be shocked at, at the level of sophistication, um, these models can achieve.

I mean, it's, remember Michael, that this was, you know, this wasn't really expected when the first transformer models, uh, uh, arrived. You know, they called it an emergent capability, meaning that they had no idea it could do this stuff. And so we're still on that path of discovery, and particularly when you start talking about, uh, these reasoning models, uh, and intelligent autonomous agents, um, it gets really interesting and it's going to take, um, a keen eye and a cool head to figure all this out.

Uh, and it is going to have major impacts on the future of work. Um, and, uh, there, as you said, there are a few guidelines right now, but, uh, I would say stay flexible, get smart, and, um, slowly, uh, you know, don't forget the, while it's important to figure out and understand new technologies, don't forget what is permanent and what is universal. I'm thinking of a quote from Jeff Bezos, uh, you know, who was talked about, people talked about, you know, Amazon and what the new technology was that enabled this business model.

They said the important thing is to focus on what doesn't change. And what doesn't change is people want choice. People want convenience.

People want low cost. And it, it's very important to remember those things when you embark on these grand ideas of artificial intelligence. You used the phrase knowledge worker earlier, and I'm scratching my head sometimes about that term because I wonder if we're evolving into not knowledge workers, but maybe knowledge supervisors, and we're gonna have all these AI agents that are kind of gonna be repositories of knowledge that we're gonna have to figure out how to orchestrate.

Is that where we're headed? Well, that's certainly the finding of this, the Carnegie Mellon Microsoft study in, in, uh, this month was that, um, the nature of work is changing. So you're overseeing, uh, and curating a knowledge process rather than doing a knowledge yourself.

And, um, you know, Michael, when you think of it, you know, a lot of what you and I and millions of other people do is we sit at desks and we respond to emails and we synthesize information. Uh, and that's exactly what these models do. So, um, uh, anyone tell you that, oh, they're just word calculators that they, they can't possibly threaten what I do.

Uh, they may be mistaken. Arthur, you mentioned your book. What's the title and where do I find it again?

It's on Amazon. It's called Organi, seeing for the New Productivity Revolution. Um, uh, it was out, uh, in December of last year.

Uh, and it just goes through a lot of these steps and a lot, lot of these tips on how you organize around this new technology and how you make the best of it, and how you get your data in line to optimize, uh, the outputs and minimize the risks. Right. Folks here heard it here.

Hey, even in the IH you should look before you leap and there's a whole book about it. Absolutely. Arthur, thanks for being on the show.

You're very welcome. Glad to have it. And thank you all for watching the latest episode of the Textron AI series.

You can find this episode and others on our website. Until then, we'll see you next time. Hello, this is Dion Hinchcliffe.

com. And here are my analyst predictions for 2025. I've got three of them.

We're now moving into a new domain called agent-based ai, and this is the next big wave in generative ai. And instead of generating content for you, it's this AI that takes direct action on your behalf. So actually getting work done and, uh, using a browser or using applications and actually accomplishing tasks autonomously across multiple applications.

And it can be multi-step tasks and it can be for a long period of time. And so this has implications for the digital labor market very significantly, a large, uh, percentage, and by our estimates, about 4 trillion globally and labor can be automated in this fashion. So a a lot of rote tasks that before might've had AI advising you or, or telling you how to best complete that task using content.

Now the AI can just go actually do it for you. That has major significance in terms of how CIOs are gonna automate in the future. We've been following all the latest Agentic AI product announcements from the top enterprise vendors.

Uh, we have a report coming out in a few weeks that we'll cover them, but, uh, what organizations have to be doing is getting experience now and making, uh, AI perform and do it safely with guardrails. My next prediction is also about ai, something called super intelligence. Then the next step beyond that, uh, we may reach, which is artificial general intelligence.

And this is a conversation I, I don't see enough people focusing on because it has major strategic impact to our organizations. And this is the top vendors like OpenAI or Anthropic who are, have the stated goal of eventually getting to the most advanced type of ai that's the A GII just mentioned. But on the way, and we're seeing signs that we're actually starting to reach it is this concept that's super intelligence, which is AI that is smarter than our best PhDs, uh, smarter than our best geniuses who can do things.

They can solve problems that humans cannot have not been able to solve so far. And this is we're seeing as, uh, the AI models climb the IQ benchmarks, you know, run every day on all the new models that are being released, uh, new versions of models that are being released all the time. We're seeing that, uh, they're closing in on that super intelligence and should be in the lab by the end of the year.

And that's something organizations have to be contending with, uh, preparing for because, uh, these super intelligence can allow your organization to do things your competitors can't. It's very significant. Uh, and this, this, um, milestone will be reached here shortly.

Um, and it'll be in production and available to, to all enterprises sometime next year. So definitely have to prepare for that. And my last prediction has to do with the cloud modernizing existing workloads and moving new workloads out to the public cloud.

And that now is because of the cost of, of these new types of workloads, AI workloads are always on. Uh, we also have a lot more, uh, compliance and regulatory issues, data residency we have to deal with. And so private cloud is return to the conversation using the same technologies, but running inside co-location or inside a enterprise data center to really manage costs or optimize performance or do deliver on constraints like data residency, um, that can't be delivered easily any other way.

And so private cloud is not not gonna be the next new destination. Public cloud is still the primary destination, but we see private cloud emerging as a major Alternative for certain types of workloads. So it's always on, it was highly perform at those, uh, things like AI training, it'd have to be run for months, uh, often makes sense just to, to, to cut out the middleman and, and, and there's, there was significant cost savings in, in that regard.

And so see, private cloud is really being added to the mix. So the whole spectrum of the cloud computing conversation, uh, it's part of a continuum, uh, where before we only saw public cloud, so that's a, it is a major shift. 71% of CIOs say they're reconsidering where we're gonna run their workloads this year.

So that shows you how, how big a trend. Uh, so I predict our organizations will be adding a lot more to the mix going forward. And so those are my, my analyst predictions really focused on the CIO for 2025.

com. Hello everyone. Alex Smith here with the Futurum Group.

And today we're gonna be sharing with you some of our predictions going into 2025. And I'm specifically gonna be talking about cloud marketplaces and the role that we expect them to have in the technology industry. In Fact, we think cloud marketplaces will become as important as a route to market for the software industry as traditional distribution has been for the hardware industry.

And there's really three main reasons why that's the case. The first has to do with marketplace fees, which have been coming down over the past decade. You go back a number of years when marketplaces first came on the scene and fees were around 20% north of 20%.

Now they're around 3% for many as standard and even as low as one and a half percent, uh, depending on marketplace, depending on scenario. And in this price point, they're operating in a similar margin stack to what, uh, traditional distributors would offer for their customers. So overall, it is becoming a more cost effective route to market.

And vendors can bake this fee into their pricing. They can offer their sales force comp neutrality, many do. And that again, makes it overall a more cost effective, uh, route to market, uh, compared to what it was in the past.

So that's driving some momentum. The second factor has to do with cloud commits. And by this we mean, uh, long-term commitments that customers make to spend in the hyperscaler environments.

And increasingly, this part of this c commit can be used on third party software products that exist in the cloud marketplace. So that is an additional way for customers to burn down these long-term commits. And this commit amount continues to grow across the three leading hyperscalers.

That number now stands north of $400 billion. So what you see here effectively is a, a ready made economy for software companies to be able to tap into because they are dollars that have already been committed to spend. And in many cases, if they cannot spend it on their compute needs with the hyperscalers, then they're looking to spend that on their software needs through that same same vehicle.

And the way to tap into that is through these marketplaces. And I think what you'll see now is the next evolution of that, where when the hyperscalers are going to discuss their commit contracts, they will not only be talking about the, the compute and storage needs that they're providing, but they'll also be talking about the software needs that that customer has too, and saying why you break, bake that into your, uh, commit plans going forward. So I think that will be more tailwind for the cloud marketplaces as well going forward.

And then the final factor has to do with the role of channel partners. And increasingly what you're seeing is that the hyperscaler marketplaces are creating programs and policies and other forms of enablement to allow channel partners to be a part of this overall marketplace engine. Right?

We mentioned earlier that as the overall marketplace fees come down, that leaves more room again in the margin stack for the channel partners to, to be involved as well. In fact, you're seeing now north of a third of all marketplace deals involving some kind of channel partner. Some marketplaces leaning much more heavily into that motion than others.

And this also means that the software vendors themselves can include their traditional partners as part of their overall marketplace strategy so that the partners are not competing with what they wanna do on the marketplace front. So we expect channel partners to play an increasingly important role in marketplaces going forward as well. So again, the three drivers fees coming down, the growth of committed spend and the increasing role of channel partners will all drive cloud marketplaces good going forward.

And so a call to action to the vendors out there, uh, that might be watching this is as you were thinking about your, uh, go to market strategy overall, really consider the, the role and the importance that you place, um, on the hyperscaler marketplaces as well as the role that your traditional partners will play as part of that marketplace, uh, strategy. Because really they will go hand in hand, um, to be one of the fastest growing route to markets, um, collectively for the software industry overall. Hi everyone.

I'm Mitch Ashley, VP and practice lead for DevOps and application development with the RUM Group. These are my predictions for 2025. First 2025 is go time for AI in production.

A lot of AI projects have been stuck in the pilot and prototype phases. Matter of fact, some estimates say that only a third of those have made into production so far. This is the year where AI has to get real and start demonstrating value that impacts how we develop traditional software as well.

We will see vendors introduce capabilities that help us start to blend and coordinate workflows and pipelines across DevOps for both traditional software as well as AI projects, which tend to have some differences in how the workflows are performed. So look for those features maybe later in 2025. Prediction number two, built in AI rather than bolt on AI across the software development lifecycle.

Much of the AI we use, particularly generative AI today, are things that are bolt on. They're chatbots, they're natural language interface to it. They may be an IDE plugin that helps us, uh, generate code or get access to a code base.

Increasingly we'll see more AI that is just a part of the products and the tools and the workflows, the tool chains that we use for creating software rather than an adjunct or separate thing. I think we'll see a lot more productivity as more AI is really integrated into how we work rather than a feature of a product or a separate product. Kubernetes dominance.

That's the next prediction. And we tend to think of Kubernetes as the cloud native container orchestration software. Of course, that's what it is.

We use it with microservices, containerized AppSec, all kinds of workloads. But that's the point is that Kubernetes has really expanded its use across virtually any kind of product and service that we may use. We may be provided by a third party a service in the cloud.

Uh, it could be even on hardware, you know, integrated hardware and software to use for storage solutions or an ED solutions. Kubernetes truly is ED everywhere and has become the workload system for any kind of application or service. With that comes though, we need to up our skills in Kubernetes operational capabilities.

It is complex, it's getting simpler. We're offloading more of that to third parties, but we'll also see AI help us here with operationalizing Kubernetes, reducing some of the complexity and improving our overall ability to run it effectively. Well, thank you for joining me for these predictions around DevOps and application development.

I hope you'll check out the full ebook of all the predictions by the Futurum group analysts. We cover a number of areas, whether it be enterprise applications, ai, of course, infrastructure, security, you name it. com.

Thank you. Hey everybody, thanks for joining us for another episode of Techstrong Women, where we feature amazing women doing amazing things in tech. I'm Jodi Ashley, executive producer here at Techstrong, and I'm here with my co-host Tracy Ragan, creator and CEO of Deploy hub and busy, busy lady working with the Linux Foundation.

Before I introduce today's guest, I just wanna give you a quick update about what's going on on Techstrong. com, so be sure to go check that out. We have some virtual events coming up.

We're gonna be at RSA, we're gonna be at CubeCon in London, so we got a busy start to the year. So please be sure and check us out there, stop by and say hello or reach out to our team and maybe we can do an interview with you. com and be sure to tune into Textron TV every day for great shows and interviews.

Alright, Tracy, what's on your mind today? Well, first of all, I think the platform engineering is gonna be a very interesting topic. So, uh, I think I'll be watching that, um, for a while.

Now, this, you know, we get new topics all the time, but I think the platform engineering one's an interesting one, but that's not what's on my mind. Um, I, this is from an article that was on DevOps, um, I think Mike Bazar may have written it, and it's about fake stars on GitHub. So I can't tell you from being a, being in a, an open source, uh, contributor and a community organizer around orus, we worked really hard for the, you know, just shy of 400 stars that we have really hard, every single one of them we worked for.

So it's really irritating to think that somebody would just buy stars and that there's ways to buy stars. So what I wanna say about that is sometimes if you look at something and it's too good to be true, it probably isn't true. So if there's a, if there's a open source project out there that you're thinking, well, this would be really cool to use or download and use this package in my code and it's got thousands of stars on it and one or two, uh, contributors, it's probably not real buyer beware.

So we have fake news now, we have fake stars and it really makes me sad that this, this culture that we find ourselves in has infiltrated into the open source world because the open source world is, in the past, has been a place where people are sincerely writing code that they want to share and the stars are like likes. And it gives us an idea of if maybe we should or shouldn't use that code. So buyer beware, download or beware.

Fake stars exist. I dunno, that's crazy. It's like people buying views on YouTube and all that kind of stuff and Exactly.

And you jump on something 'cause you think everybody else liked it, and then you get in there and you're like, meh. Yeah. And in the case of open source, you download it and all, there's a bunch of nefarious code in it.

Well, yeah, that's the thing. Nefarious code. Yeah.

Yeah. All right, well we got that in for today. I agree.

That's, that sucks. It sucks to whoever's doing it. If you, if you're doing fake stars, you suck.

You suck. Alright, uh, I'm ready to introduce our guest to all of you today. We're really excited to have Caroline back.

She's been with us before, but we're gonna have a great, uh, kind of start of the year conversation that I think is really important for us to have. And, um, I'm looking forward to it. Caroline Wong, why don't you go ahead and introduce yourself to us and, and we'll get started.

I'm Caroline, I'm a cybersecurity person. I've been on in-house security teams, vendor security teams, startup consulting product. Um, and that's given me a really sort of well-rounded view on cybersecurity and the problems that we face.

I think the most important and most interesting part about cybersecurity is the people. Um, I have hosted a, a podcast called Humans of InfoSec. Um, and yeah, I'm also a writer.

I wrote a book called Security Metrics, A Beginner's Guide. That book was inducted into the cybersecurity Canon Hall of Fame in 2022. And I'm currently offering a new book with Wiley about AI and cybersecurity resilience.

Ooh, that's so awesome. Tracy's gonna be putting that on her to read the her share. So when, when are you gonna get that finished?

So tentatively scheduled for publishing in the spring of 2026. So beautiful. Just a few short months away.

And by the way, Textron is picking up Caroline's podcast. I'm gonna be producing that for her shortly. We're in the process of getting that rolling, so I'm pretty excited about that.

We're all pretty excited about that here, so, yay. More fun stuff coming. All right, ladies, let's dive in.

Caroline's had a fun end of year, start of year. You wanna tell us a little bit about what happened? Sure.

I have been job searching. I have spent about three months or so at the end of 2024, job searching. And you know, Jody and I were talking the other day and I was saying I am the primary breadwinner in my family.

Um, I've got kiddos, uh, the way that our household constellation works. I've got in-laws, um, and we've got dogs and cats and chickens, and there's a lot of literal mouths to feed. Um, and I take my role in our family as a provider very, very seriously.

Um, and so naturally job searching, there's a lot of anxiety, there's a lot of stress, there's a lot of pressure. Um, and for folks who work in cybersecurity, for folks who work in tech, the experience is you see a job posting and within 24 hours there's 500 applicants. Within three days, there's 1500 applicants, and they've shut down the job posting because it's just full recruiters literally cannot go through that many resumes.

Um, and it's tough, you know? Um, and I think that for me, going through an experience like that, it taught me so much about myself. It gave me some really important time to reflect and think about what's truly important to me.

Um, getting a break is also a gift. Um, and yeah, so I'm, I'm thrilled to be here sharing my story. Um, I think that fortunately and unfortunately, jump searching is something that many of us, uh, can relate to.

Um, and so I'd also really like to share some different practices that I used during my job search to try and take care of myself. You know, this is an interesting time for this topic. Um, just at the end of the year, last year at our last, uh, TIUs outreach, um, meeting, we talked about what we might wanna do in 2025.

And the number one thing that came up was a job seekers webinar series that goes what it's like to be a job seeker in this climate that you just described, that tooling how to use keywords, how to try to basically beat the system. And I feel like as you described, there are so many people applying for these jobs that they use AI to filter it out. And basically they're just doing, you know, matching on keywords.

So people are having to add keywords to try to make it work when they shouldn't be. There's gotta be a better way to do this. We heard a little bit about this when we had the woman from manpower on.

Um, we chatted a little bit, and that was early last year. But I think over the course of this la this, this year, more people have complained or more people have struggled with that. Can, can you tell us a little bit about when you first started, uh, noticing this trend and you were sending out resumes, what were the kinds of jobs that you were sending resumes to, you know, at what level you know of, and do you think that you, that you maybe targeted jobs that were under what you were able to do and you were overqualified, did that come into the play?

Because certainly a person with your skills, I would've thought would've been picked up almost immediately. Thank you so much, Tracy. You know, I, I am so fortunate to have had such an incredibly rich career and my most recent role prior to the new job that I just started, I was a C-level executive with 20 years of cybersecurity experience.

And even so, it's tough, you know, and I felt so fortunate. I was able to engage in a lot of different interviews. Um, at least five of the interview processes that I engaged in, several of which I made to the last round.

A recruiter or a panelist or a hiring manager would just look at me and say, Caroline, let's just address the elephant in the room. Why are you applying to this job? You are overqualified.

And the actual reality is, my first responsibility is to my family. And I also, I don't have a ton of ego about the work that I do. One of the things that I admire in people that I've worked with, that I really respect is that when stuff's gotta get done, stuff's gotta get done.

And who cares? Who's got what sorts of title. You know, as long as you're delighting customers, creating value, making a positive impact, whatever needs to get done, I'm happy to do.

The, the way that I phrased it in a lot of these conversations though, was I said, and this is true as well, I said, you know, it's been a little while since I've been and on keyboard and really close to solving the problem. Um, and I really got into a mindset where I thought I could do this, you know? Yeah.

Um, and sometimes I'd go through an entire, uh, series of interviews and make it to the end, and then you kind of wait, you know, to get a callback from a recruiter. And if it doesn't happen sort of right away, then you wait another day, you wait another day, you know, and, and it's just tough. You know, at the end of the day, there are thousands of people, many of whom are extremely qualified.

I can't tell you about the number of friends and colleagues and people that I've met who are extremely qualified and on the market right now. It is a simple supply and demand situation. There just are less jobs on the market at this moment.

I spoke with the recruiter in Q2, Q4 of 2024, a CSO recruiter. Um, something that happened to work really well for me, which I know is hard for others, is that I never wanna be a cso. That's a job.

That's a job that I'm simply not interested in. Um, I'm very interested in all sorts of adjacent jobs to the ciso, but CISO is not the job for me. I spoke with a recruiter and this person said, Caroline, typically in Q4, you'll see 20 to 25 big CISO jumps on the market.

And this person said to me, and this was for Q4 2024, right now there's 10 to 15, significantly less than usual. And I had been in my previous role for eight years, which in tech is like multiple lifetimes. I mean, we're talking like Mesozoic era at the time of being at the same company.

Um, and it was actually so much fun because one of the things that I love to do is I love to learn. And so for each and every single company that I was interested in, I did so much research and I watched so many videos and I learned so much about what these organizations are doing. Um, in some cases, you know, a lot of my search was gonna be in cybersecurity, was gonna be in tech, but I also branched out to pharmaceutical and healthcare and, um, energy, uh, renewable energy.

Um, and there was just so much to learn. And that was really fun. And I actually really did enjoy the exercise of imagining what my next career chapter could be.

That was really, really fun. And did you, when, when you were going through that imagining, um, did you work with a, a recruiter that helped you imagine that? Sometimes it's hard to see ourselves.

It is so hard to see ourselves, and I just celebrated my 10th wedding anniversary, and I remember when I was dating on the AppSec, and I think it's really hard to write a profile for oneself on a dating app. Similarly, I actually think it's kind of hard to write a resume. I think it's kind of hard to write one's LinkedIn, uh, page.

Um, and as far as these things go, I have throughout my career in been intentional about my brand and about my sort of external presence. And even so, I knew that I wasn't quite hitting the mark. Um, and I spoke with many different recruiters, um, and I happened to come across one extraordinary recruiter.

His name's Darren. And if anyone's interested in being contacted with Darren, uh, just shoot me a note on LinkedIn and I'll connect you. He helped me to really refresh my LinkedIn page in a way that I felt was very meaningful.

He also helped me write my resume. Writing a resume can be, there can be these emotional and these mental blocks to doing that type of an activity. It's a hard thing to do.

Um, and I really found, and I'm the type of person whom I just love coaches. I've worked with personal trainers, I've worked with nutrition coaches, I've worked with finance coaches. You know, why not work with a resume coach, a LinkedIn coach?

Um, I've been in therapy for more than 10 years, you know, so I'm all about the coaching. Um, and for me that helped enormously because I was in a position where I could tell my story to this person that I trust and they could help me tell my story to others. Well, and we don't, we don't, as women, you know, lift our own self up when we write resumes and, you know, talk ourselves up necessarily like we see our counterparts in the world do.

And I also think it's, it's really tough to to be you don't, like, I, when I kind of looked at mine last year and I was like, wait, there's this, I talked with, with someone that I knew and it was like, well, you could be doing this and this and this. And they were things I never even thought about. I'm like, wait, I guess I, oh wow, I could do that.

I do have qualifications for that. And it, it was super duper eye-opening and as, as part of just kind of evaluating what that would look like. So I think we also, it's always good to get someone else with a clear picture of us into the conversation to, to give us, you know, a very objective look at things, both positive and negative.

And I would imagine after nine years, I mean, resume writing is totally different. It's totally different. It's just different, different what You know.

So to put the right words in and not too much, you know, the right, it's just totally different. And What the things, right. Do you, do you write it in first person?

Do you write it in third person? What tense do you use? You know, these are all things that yeah, we spend relatively little time in our careers doing these activities, right?

And we don't often have time to become experts at applying for jobs. It's a different thing. And I, and I, you know, something's occurring to me that's really important to share, which is that there were people in my network who were so kind and so generous with their time, with their, um, generosity in terms of, sure, I'd be happy to introduce you to this person.

I'd be happy to provide a reference for you. Um, and just for me, going through some of those mental and emotional challenges that are natural in a process like this, I will never forget each and every single person who reached out to me and said, Hey, if you wanna talk, I'm here to listen. That's awesome.

That was really meaningful to me. Tracy, what were you gonna say? So, resumes traditionally have been written to say what we have done in the past.

Yeah. It, and it doesn't tell us, a resume doesn't tell us what the person can do, right? Mm-hmm.

It doesn't give a good insight on what they can do. Now, in reviewing resumes, I can say that guys are much more willing to cater a resume to what they can do, where women want to outline what they have done. Interesting.

So for ex example, first, so for example, let's say that you, um, you were a, you know, you've been outta the market or you hadn't looked at putting a resume together for eight years. Uh, you've been a, you know, a cc plus plus programmer and you know, you know how to write Java, but none of your jobs ever required it. 'cause you, they had you doing c and c plus plus.

What are you gonna, you're, you're not gonna get a, a job because JavaScript is what everybody's using, or Python. But I can promise you if you have written code in C or c plus plus, Python will be a breeze, right? So resumes have to be able to reflect what our abilities are, and they don't.

And this is the, this is the struggle that so many people are having. So you begin seeing resumes with a lot of bullet points, a lot of keywords, because these new ways of finding, um, you know, going through a job board, which most of us would have to do, they're gonna look for specific keywords and they wanna get like an 80 to 90% match on the keywords they have in their job description to what you have in your resume. And they're using an AI tool.

They don't even look at it themselves. It doesn't even get a human viewing it. They use the ai and then if it's not at like 80%, then poof, it's gone.

So for example, you know, building AI code, right? How many of us really have out, out there working on LLMs? Not that many people, but how many developers and people who are technical could achieve it if they have the opportunity to work on it most, right?

But they, so somehow you have to get this kind of experience on your resume and you don't have it in a job description. So how do you go about doing that without embellishing on your resume? This is the problem with the tools.

It's not what we have done, it's what we can do. So bullet pointing and being involved in, um, open source communities, um, putting together, let's say you, you start working on an open source community and you say, I wanna focus on seeing how an LLM will work with Artelia, for example. Then you can add that to your resume because it's what you are looking at doing and you're contributing to the community at large.

So we have to get a lot smarter about how to present ourselves in resumes. And it's all about the future, not the past. And resumes reflect only on the past.

This is a hard thing for women to get over, is how do you embellish, how do you work on that? How do you build that, that, uh, that profile and that brand without having to had a wor a job that had you do it? Which is sort of ridiculous to be quite honest, right?

And there's a lot of great people out there you can hire to help you, but not everybody has those resources. So a lot of people jump in and AI their resume and you can just tell when you read someone's resume that they threw it into AI and let AI do all the work. So that's not helpful.

Not a good idea. It's gotta be hard. And I think, you know, you can't, can't forget how important networking is.

And obviously Caroline spoke to that. Knowing people is so important, right? Being connected with people and, and, and being willing to, like, I know you Caroline pretty well.

I know your story. I know I know a lot about you and, and you're, you gotta be open to not be like, I don't have a job. You gotta be like, Hey, I'm looking for a job.

Because you, and, and that's hard to do when you leave that place. I've been in that place a couple times and you just kind of wanna be like, Ugh, I don't wanna tell anybody but you, but you, you gotta, because that's what's gonna get you to the next job. People can only help you if they know that you need help.

Absolutely. And we live in this super weird culture where so much of our identities are tied up in having our jobs. And so if there's a moment where we don't have a job, it's jarring.

You know? And that is not because of any of us as individuals. That is because of the culture that we live in.

That is because of the society and what society has deemed to be valuable. And so this is something that's really, I think, important for any of us to consider. Whether we're job searching, whether we're happily integral.

There's, there's a book that I really like that I listen to quite a lot during this search, and it's called Strength to Strength. And it talks about, uh, for folks who at one point in their careers have been extremely successful professionally, and then what happens next? And it kind of gives these ideas for other parts of one's life to invest in things like family, extended, family, friends, spirituality of that sort kind of thing.

You know, different exercise and nutrition and just all these different parts of our world that are our real lives that exist in addition to work. Yes. And we know, again, if I go back to the resume, we used to look at some of that, you know, I used to always make sure, um, and I still do for the most part that any profile I have, I point out that I have a black belt.

Why? Because it makes you a more interesting person, right? How did I miss that?

I'm gonna be nicer to you when I'm in person, you know, or that I like to ride big horses. You know, just what is it that makes this person interesting? And you know what?

Our resume systems now, they don't even care if you're an interesting person or not, which is horrible. It's, you know, because it takes the human out of the equation. We have taken the human factor out of the, the, the job, the, um, the head hunter's job.

And all we're doing is looking to match keywords. So Carolyn, did you use any kind of tool to Uh, absolutely. And I have, here's, here's one thing that I recommend for every job that I applied to, I would take my resume and I would take the job description and I would say, chat.

TPT write me a draft cover letter. And I would use that as a starting point. And I would look at it and I would take the bits that I liked and I would change the bits.

Um, but I would use it as a starting point. I know that for me, sometimes it's awfully intimidating. I'm facing this a lot lately, lately 'cause I'm writing a book about cyber security and ai, but there could be something so intimidating about like a blank word document.

Um, but a draft, I can do something with a draft, I can, you know, get my eyeballs on a draft and immediately iterate. Um, and that's, that was something that I found to be really helpful. I'm the same way.

The blank paper just terrifies me before I have something to, but I could have something to start from. It makes such a huge difference. Yeah.

Yeah. There was a tool that my niece was using and I was watching her use, I didn't, I don't remember the name of it, but you could put in a job description and it would look at your existing resume and enhance it to match the job description. Now, is everything accurate in what you did in the past?

Maybe, or maybe not. But the problem, the point is, everybody's doing this now, right? Right.

So we don't, we, we have to get past what we used to think of as embellishing on a resume. And I'm not telling people to lie, but you've, you have to be able to pivot yourself. When I first started, you know, when I, I was a California girl and I graduated from college, and five years later I decided I didn't wanna be in California anymore.

And I moved to New York and decided to become a Wall Street consultant. I had never, ever, ever worked on OS two before, but everybody needed OS two consultants. So I sit down and I read the big IBM red book on OS two, and I put it all over my resume and I got a job almost instantly.

I became one of the IBM's primary OS two consultants as a result. But again, it was what I could do and I was marketing myself. And marketing is never completely honest.

And I just wanna tell women out there that you, I don't wanna tell, I, I don't wanna say just lie and creative jobs, but you have to be able to express what your abilities are. And you ha go ahead and start using those bullet points to say, here are some of the tools that I know I can use. Here are the skills that I have.

So that you start matching on those, uh, those jobs. It is, it is, it's unfortunate that we've gotten to this point, but this is where we are. This is how, this is where we are in this world of AI matching, you know, humans to jobs and taking out the human factor.

So it's okay to say what you can do, not just what you did And ask people for references and recommendations. Um, this time around, I was not shy about reaching out to folks that I'd worked with before and saying, Hey, would you consider taking a few minutes to write me a recommendation? And I would read through them myself when I was having a tough moment or a tough day.

Nice. Um, and it was actually just a beautiful gift to be able to be myself through the eyes of somebody that I know or somebody that I've worked with. Um, and that was really helpful for me.

Um, and I encourage folks to do that, you know, and I think that it doesn't matter how much time has gone by, you know, if you worked with someone 10 years ago, and, and the two of you did really great work together, reach out and ask. You know, the worst they can do is say no or ignore you. There's, there's really no downside.

So this is so, such an important conversation because, um, when we spoke with the woman from Manpower, she talked about how women really lost a substantial amount of traction in the tech industry during Covid. Yeah. Because they were the ones who had to leave their jobs because the kids were at home and they had to do homeschooling, or at least babysit them as they sat in front of a, in a Zoom session for school.

And they could not do both. They couldn't do a eight hour job and take care of their kids as well. And what happened was that those, you know, in four years time, or two years time, or even a year's time, our industry changes so quickly that if you're out of work for that period of time, you probably would look at yourself and say, I'm no longer qualified for these jobs.

I don't know Python. Right. I've not had an opportunity to code in Python, so I can't talk about saying that.

I do know Python. And that keeps women from going back into, in even not just a three month break as you had, uh, Caroline, but an eight month break, you know, after having a baby. How do you get back into work after time off like that?

And how do you start pivoting yourself and rebranding yourself as a person who is relevant for today's market? Not the market that you left eight months ago, or even three months ago. We had another person who, um, Jody and I love very much.

Um, she was in the dev rail space and lost her job. And I don't think she found another job for Al I think it was close to six or seven months. You know, we were all just sweating it out for her.

'cause she's also the primary breadwinner in her family. And it was shocking to me that this, you know, that this was happening. And when I started looking into, you know, watching a a, a college graduate go through the process and how the tools now are matching people to jobs.

It is not, uh, uh, it is not good. It does not find the best, uh, most qualified person. It only finds the best match of words.

And how is that helpful for anybody? How do you know that person's gonna be decent? How do you know anything about that person?

If you really want to interview them, you don't. So it's, I get, I, it, it's sad to me, it really is that we can't find a better way to do it. If AI is supposed to be so great, how come in this specific particular area, it's making our lives harder, not easier.

There were a few, um, interview processes that I engaged in that I thought the company did a really cool thing. The company said, we're doing a case study. Caroline hears basically an assignment for you.

Um, we expect you to put together, you know, X number of slides, you know, to write, you know, y number of words and to present it. Um, and I thought that was really cool, you know, because in the job interview process, um, in those cases, I, and any of the other candidates would've really been given an opportunity to kinda show our stuff. Um, so I thought that was pretty cool.

And I also wanna say, you know, when you're job searching, of course you want a job, but it's also extremely important to pay attention to what it feels like when you're talking to these people. 'cause say you get the job, then you're stuck working with them, and hopefully you like them and hopefully you respect them and hopefully you can learn from them. Um, so make sure that you are evaluating the company as much as they are evaluating you, and don't hesitate to ask any questions that you have, Which is so much harder to do remotely.

Right? You get pulled into an office, you maybe sit around a table with people. You, you know, that physical in Personness is very different in an interview situation.

You know, I'm curious, Caroline, how many of your interviews were in person? Zero. Yeah.

Zero interviews, you know, and it's really funny because some of the companies, their HR interview processes, they're virtual, but they've got these like, uh, names that were clearly from a couple of years ago. So, you know, such and such organization would say, and for the next stage, you're gonna do a virtual onsite or for the next stage, you're gonna do an onsite. And I was like, okay, well, you know, do you need me to fly somewhere?

Are we gonna do 'em all in one day? And they said, no, you know, it's, it's virtual and we can just space 'em out, you know, depending on people's availability. And it was just, it was just a fascinating thing, you know?

Um, but, you know, one of the things that I think has become very important, uh, is being able to effectively communicate like this, you know, to really be able to, uh, demonstrate, uh, one skill via a Zoom video. Um, and that's not easy for everyone. That's not natural for everyone, you know?

But if, if any of us, um, have any troubles with it, you know, it's, it's worth practicing. It's worth asking for advice. It's worth, you know, getting a little bit of support, uh, 'cause that that is a really big part of it.

Yeah. You don't think about that feeling like the three of us, we do this all the time, so it, it's not a big deal to jump in. But people who are coding all day and, you know, they're doing their thing and their heads down, and they're not interacting on Zoom calls unless it's like a company meeting, having an interview situation would be very different.

Absolutely. I about that. I was just gonna say that, Jody, not everybody's on, you know, a text on gang or doing presentations like Caroline and yourself are doing.

Right. Um, it's a, it's a different world, the zoom world, and to be able to come across and be comfortable and be yourself is really, really challenging for some people. Again, the human factors being taken out.

I'm surprised you didn't get EE even after your offer. They didn't have you come in and meet you in person. That's amazing to me.

It's wild. I, I literally thought, you know, I kind of assumed, um, like, okay, like, we're gonna do this. Like, naturally I'll, I'll fly to you or you're gonna fly to me, or we're gonna meet up and we're gonna hang out for a week and we're gonna, and it just wasn't like that, you know?

And part of it is travel and expense budgets. Um, and part of it is, you know, one of the things that I love about my new job is everyone is so remote competent. It is amazing how remote competent these people are.

Um, it just, you know, everyone just gets it, it all just makes sense. Um, and that is, that's really, really nice. And after we've developed all these remote competent skills, you know, we have a potentially a, a new administration coming in saying, everybody needs to go back to the office.

And, you know, I heard, I heard that Amazon was having folks come into the office. Mm-hmm. And, uh, and then I read a newspaper, um, article that said that the office weren't ready to accommodate everyone.

So I think they had to, I think they had to delay it. So that's also been a really interesting thing, you know, and I think that for any job seeker, you know, there are ways in which you can broaden your search and you can design, you know, uh, for folks who are really intent on a csso CSO job, you know, maybe consider a job where you are reporting to a CISO or adjacent to a ciso. You know, for folks who are okay with going into the office, you know, if you happen to live near an office and they want folks in the office that will, um, expand, uh, your possibilities.

So it, it's really so much about whatever people are looking for in the moment. And I do think that right now, one of the things that I noticed is they are looking for deep expertise in a particular area. It was, it was interesting for me 'cause I'm a little bit of a generalist.

Um, some of my superpowers are not straight engineering. They're not straight sales, they're not 20 years of product management. Um, but, you know, I just want folks to know, just like, keep on going, keep your head up, keep on going, and, you know, just keep going because, uh, you know, it's, it's worth trying.

Um, and just learning along the way. I can't discount though how important your LinkedIn profile is, though. It's A big one.

It's People, People do look at it. People look At it. That's the first thing they go to.

Mm-hmm. They see your resume and they go right out to LinkedIn and then they Google you. And see, that's why we have to teach our younger generation about what they put on the internet, because employers aren't gonna find it people, and it may not do you any service for them to see it.

So, yeah, I mean, it's, it's super important. I think LinkedIn is, LinkedIn has become the online resume for so many people. Absolutely.

And the problem because is as you're trying to apply for these different jobs, you're gonna tweak your resume for each of those jobs. So how do you have a LinkedIn profile that matches exactly what each of those different jobs you've applied for represents? Because as for the game we're playing, right?

We don't just have a one resume and a LinkedIn profile that reflects what that resume would say. Instead, what we have are multiple resumes, like the tools that you can use. It says, here's my original resume, here's the job description, rewrite this, uh, you know, to match this and get my 80% or 90% match in order to get my, to get maybe a, a phone call, right?

Because that's what you're hoping for is a phone call. So that, that, that becomes a challenge too. So in your, in your endorsements and, um, in LinkedIn, your endorsements are important.

Your skills are important. If you're looking for work and you're seeing something that continues to come up as potential, um, a a skill that you need, be sure that you reflect that in LinkedIn. So you may have a lot of stuff in LinkedIn that you're like, wow, I've, I guess I could say I could do all that.

But yes, you can. Women, you can do this. This is something you can do.

So Carol and I, I have another question before we, we have to wrap up. But you go through this process and obviously, you know, you and I talked about it while you were going through it, and, um, you know, what do you do for yourself? What kind of self care do you do when you're the breadwinner?

You have children, you have extended family there, you know, and there's the stress of that on top. What did, what would you recommend as far as just finding a happy place when you're in a really stressful world, especially the holidays on top of it? Ah, you know, totally.

It's a crappy type of beer on top of it. You know, we have to learn how to take care of ourselves and the time. I think that it's most important for us to learn how to take care of ourselves is when we're going through tough times.

Um, one of the things that I've started doing, and I actually love it, kind of just around the same time that I began my job search. My husband installed a cold plunge, uh, in our backyard. And I love it.

It is not for everyone. You know, not everyone is super excited to dunk their body and polar barefoot, 42 degree, you know, water for 10 minutes. Um, mm-hmm.

But I, it just, I just love it. It's exhilarating. Um, so, you know, whatever your thing is, if it's spin classes, if you love knitting, if you love journaling, if you love going for walks in nature, like really make sure you're getting what you need.

I really need sleep. So I prioritized my sleep. I also had a really good friend recommend to me, um, that I should, uh, you know, go on a little trip by myself and for myself.

And I'm very fortunate that I have the resources to do something like that. I booked an Airbnb for myself 25 minutes away from where I live, and I just lit some candles and sat in a hot tub and, you know, did some writing, did some thinking, did some reading. Um, and so we really do have to take care of ourselves.

Um, that I think is what's gonna keep us going. I also think that any, any rejection, any time you are ignored, I really wanna encourage people not to take it personally, because there really are just so many factors way outside of your control. And so what we can control is we can keep going, you can keep searching, you can try and apply for the job on the first day that it's posted.

You can, you can just keep on going, you know? Um, but you know, it, it's okay to be sad and it's okay to be disappointed. Um, but to the extent that we can allow ourselves to feel those feelings and then move through and move on, um, I think that's a really important skill to develop as well.

That is so helpful. Tracy, are you gonna ask her your question? I think she already gave us something to read, but you have to ask it anyway.

Tracy always asks This. I think That's a good question. Did you ever did, while you were going through this, did, were there any books that you picked up on on being a job seeker?

For me, I read a, so, okay, here's another thing actually. So I talked about strength to strength, which I highly recommend. Um, and then another thing that I love doing is I love reading for fun.

I love reading mm-hmm. Fiction. Um, and I came across this great Netflix show.

So here's something I think that is actually equally important as bleep as, you know, if you have a particular comfort food that you really enjoy, give it to yourself, you know? Um, but I, I came across this Netflix show called A Discovery of Witches on Netflix, and I just love it. And then, so lucky for me, there's three seasons, so there's a ton of really great content.

It's a lot of time to relax into, you know, and I happen to have these three enormous dogs. We've got two English Mastiffs and a Rottweiler mix. And so I'm just chilling on the couch with these dogs.

And then even now, the series was based on a set of books. And so I'm actually in the middle of reading, uh, book number two out of three. So I think that it's also really important just to figure out, like, what is it that helps us to feel good and to also take breaks from the hard stuff, because our brains need breaks too.

Our brains need a little bit of fun too. Our brains need a little bit of relaxation. What great advice, what a great way to wrap up this episode.

Thank you so much for being here. I just, I think this is so important. And, uh, it's, it's a topic we we need to dive into every now and then for sure.

And hear different stories. So I really appreciate you being here, Tre. Caroline, congratulations on the, the new job.

I can't wait to hear about it. Thank you. I love it so much, and I'm so happy.

Um, and I really appreciate you inviting me here to share my story. Thank you so much. Yeah.

I'm glad you were, you came. Thank you very much. Hey, everybody, um, that wraps up the, our latest episode of Techstrong Women.

Thanks for tuning in today and be sure and tune in for our next episode. And again, head to Techstrong TV and check out all of our great content every day. Thanks a lot.

Thanks you guys. It was great to have you today. Hi, everyone.

I'm Guy Coer. I'm an analyst at the Futurum Group. I'm also CTO of Visible Impact, which is one of the divisions at Futurum Group.

And I'm so pleased to be here with you for this live session at Predict 2025 from Techstrong. 2025 will be the year of the fragile app. I think the 2025 will be the year of the fragile app.

And joining me to talk about this are two terrific and dynamic experts having to do with app construction and delivery and platforms and so forth. Starting with Hope Lynch Hope, say hi and introduce yourself. Hi.

Hello everyone. Happy to be here to have this discussion today. And my bias, as you will see as the conversation evolves, is to our platforms, uh, many years in, uh, technology industry, platform engineering, systems engineering, just another name sometimes for platforms, um, CI/CD, just technology currently.

Um, a lot of technology consulting and enjoying it and looking forward to this conversation. Uh, I'll pitch it to you, Amanda. Thank you so much.

And I see we both decided to wear green today coordinating. I know. Yeah.

Neither of you told me. So is gonna be today, you're Coordinated. So, hi everyone, I'm Amanda Ani, and I'm the managing editor for Textron Group and a podcast host, and I'm excited to be here.

I, uh, see a lot of articles around this topic, and I've got, uh, a lot pulled up to reference today to back, back up some things that we say. So I'm excited to get going. Mm-hmm.

Great. Uh, so fragile app, I thought when I thought of this, um, when I was thinking about 2025, I thought I had invented it, but Amanda helpfully found someone else who's been talking about that app fragility as well. Anyway, it's a, it's a common concept, but why would 2025 be the year of app fragility?

There's two possibilities. The AppSec are gonna be, uh, no more or less fragile than they, than they have been, at least for the past several years. But it will become more noticed and more discussed.

The other possibility is that AppSec are becoming increasingly fragile, and that will reach a point in 2025 where it will start to get noticed and discussed. In other words, either things haven't changed, but it's gonna be become a meme and a thing where things are changing, and that's why it'll become a meme and a thing. And I definitely am in the latter camp, I think 20, 24 alone already.

Um, could have been, uh, seen as, you know, uh, a year where the fragile app was talked about and became a thing. The CrowdStrike example is probably the biggest example that everyone has talked about because of how global and pervasive it well it is. And CrowdStrike was already a well-known brand, um, and vendor, you know, even outside of the, even outside of the business community.

Um, but, uh, I don't think that the fra, I think the fragile app has emerged as a topic more amongst, uh, those of us who are studying and looking at the market. I think it will become widely known as more and more people start to have poor experiences using or releasing AppSec and trying to figure out why. Mm-hmm.

I, I agree. And in, in line with what you're saying, I think it's, it's, um, you know, two lines that have now hit, hit a hit an inflection point. Um, if you go to certain stores now, it'll say, you know, no checks, no cash, right?

Credit card only people are gonna pay by phone. The more people who pay by phone, the more people who are gonna notice, Hmm, this app isn't working properly. It's not starting something, you know, something is going wrong.

Um, the more devices, the more different systems that those AppSec encounter, uh, the more, the more problems they, they just, I think, are going to have, and, and this is probably yes, a good year for some of those problems to start showing up. Yeah, absolutely. I mean, we're seeing a lot of those problems.

Uh, just today I published an article by Mike Vizard, um, so you can find it on text drawing, ITSM. Uh, so our IT service management teams are really struggling here, but, um, it says, survey surfaces a raft of patch management challenges. Um, a survey of 252 security and IT professionals published today finds more than 77% require more than a week to apply a patch to software running in IT environments.

And those patches are becoming more and more so you're having some IT burnout, um, just trying to keep up with all these problems. Yeah. So there's an incident and there's a huge lag.

I mean, a week, uh, one of our correspondence, uh, um, Tracy Ragan, who's been really helpful in helping me recognize this acceptable or should be unacceptable in, uh, you know, in, in today's environment. I think though, is it gonna reach the point, like, I think where it becomes like a, like I put it earlier, a meme, a theme, you know, uh, we've witnessed all these themes over the, over the years. Um, and I think that when things become a meme or a theme, that's when honestly, vendors start jumping in.

I mean, obviously the biggest meme right now is ai. This would be a different meme. That's where vendors start to jump in and market themselves to this problem.

And I think that's really what I'm talking about when I'm talking about 2025 being the year, the fragile app. Everybody already has to deal with fragile AppSec. If they are building and producing them, that has not changed.

Mm-hmm. Um, there are tools out there to help, um, strategies and vendors to turn to and consultants and so forth. Um, but whether it gets the attention sort of at the corporate level or the budget holding level, that's the difference.

And I think that will start to mount just this year. A lot of other articles I'm seeing are showing, um, part of the problem is of course, as we are incorporating ai, we're, we're hitting even more struggles as we're integrating ai. It's both a solution and a problem If you, you know, read various articles.

Yeah. Let's turn, actually, let's start to talk about like, you know, what, what mm-hmm. Sources are there, um, that's causing fragile AppSec, particularly, let's try to pay some attention to ones that are getting worse, seem to be getting worse rather than better.

I mean, I hope I, I'm an app dev person at heart. Yeah. I live in the app layer, so naturally I play, I blame the platform manager.

So I'm gonna turn to you And I, I won't, I won't, uh, completely disagree with you. Right. Um, because having been hands on there, um, there can be moments where, you know, some problems just sh sit on the shelf for too long because no one is screaming, uh, about resolving them.

That does not mean that the pain of the end user is necessarily any less, right. But in some defense, let's say, of the platform teams, part of what is maddening right now, if you are on a true platform engineering team, is just the absolute, uh, complexity of what you have to deal with. It has, uh, reached a point with modern application architecture that platform teams sometimes are even trying to divide into, uh, specialized groups within their team, just so they can focus because, uh, let's see, we've adopted microservices, cloud native development, uh, 12 factor methodology, but you know, here we are in 2025, and applications still seem, uh, as fragile as they ever have.

There are so many applications that they have to manage. Uh, it, it is a challenge. I'm glad you mentioned 12 Factor, since I'm a big 12 factor fan.

Mm-hmm. Because it reminds me a little of cloud native maybe in some ways, which is 12 factor is for the app dev, it's for the app side, it's for the, the, our dev side. I mean, it's mm-hmm.

It's for the coder. Mm-hmm. It's a way to, um, code such that, uh, the fragility of the platform, so to speak, doesn't matter.

Mm-hmm. Cloud native. I kind of felt the same way about Cloud Native originated not as a platform engineering prior to platform engineering, but not as a platform engineering paradigm, but as a coding paradigm, how do you code to fragile infrastructure mm-hmm.

Um, mm-hmm. But is that turning on its head? Has that turned on its head that, that, you know, the many, many sources of this complexity need to be addressed in the platform, not just in App Dev, much as we app developers wish that we can solve everything and not have to rely on you poor people, And, you know, and just to drive, you know, our overall point home even more, right?

If you think about a simple user transaction, somebody wants to, uh, check out on, on a website, right? Modern Architecture one action, right? It can touch 20 services.

You've got inventory, pricing, authentication, processing, the payments, fraud detection, shipping, everything else. And any one of those, any one of those, uh, goes wrong. You know, failure point and the connections between them is also, uh, a potential failure point.

So again, platform engineering can help, but there, there are just so many things that can go sideways. One of the, um, interesting articles recently posted that I read, uh, had me thinking, um, and this is another, another article from Mike, but, um, and this talks about, uh, when I say AI being both a problem and a solution. Mm-hmm.

So coder AI emerges to enable anyone to build AppSec using AI agents. You don't have to be a coder. Now, you can use AI agents, which of course we're hearing a lot about AI agents.

Mm-hmm. Um, but it made me think, you know, as more people who don't have this background, they don't have this knowledge and experience, they don't understand code. Mm-hmm.

And they use these agents to, to put out these AppSec, are we gonna see more problems? Because they don't really have that experience and background. So it, it's great in one aspect, oh, we're lowering barriers, but without that knowledge, are we gonna see more problems in the future?

Well, yeah. It, that harness study that came out recently from the vendor harness mm-hmm. Um, according to this, you know, research study that they did, uh, AI coding has created deployment errors at least 30% of the time.

Mm-hmm. So, I mean, that is, isn't that the classic issue with a so-called fragile app, is the update creates the problem, which takes the app down. Mm-hmm.

Mm-hmm. But it's, um, It's not just about, so, so CrowdStrike had got got, sorry, sorry, hold, but CrowdStrike got all this attention, right? Yeah.

Um, but security incidents get all this, and CrowdStrike is seen also as a security company, right? So the, you know, one of the seminal incidents, even though it's happened only rather recently, was SolarWinds. Mm-hmm.

Okay. So, so, you know, um, these are where people are managing bad actors, making attacks and all this sort of thing, but the sources of difficulty with AppSec delivering like they're expected or they're supposed to mm-hmm. Are Legion, and you described help these sort of dependencies up and down the chain, mostly up, right?

Mm-hmm. Dependent services, there's so many pieces and parts to this, and they're not just in the platform layer, I fully admit, um, the, the, uh, uh, Venafi study from just last month, um, said that, uh, uh, 86% of organizations had some sort of security incident with a cloud native application, cloud native. Mm-hmm.

All right. Cloud native, so much attention, so much development around cloud native to, to ensure resiliency of applications. And yet about half of that 85% caused an outage or a disruption in app delivery.

And I don't see this getting better. I don't see this getting better yet. There there was, there was a, um, a sny did a, did a, a study or a report where they describe something that I feel like I've, I'm, I've been sensing lately in the market, which is people are getting exhausted of trying to keep up with the messaging and the storyline and the tools and everything around application, resiliency and protection.

I mean, Amanda, you, you, you're one of the editors feel like, are you seeing this Trend as well? Yes. But here's the thing, and, and I was gonna point out, you had mentioned CrowdStrike.

So, you know, the articles, um, from that fallout, uh, since then have basically shown, um, that they did take a hit, but they bounced right back. And, um, and, uh, there was a recent article, uh, what it service The brand bounced right back the brand and Yeah, yeah. Chaos.

And, um, uh, it says further down this article, I found this interesting. Uh, this was from our writer, Jon Swartz on Textron, ITSM. Um, as he interviewed people that dealt with the fallout of this CrowdStrike, basically they said, outages are not a problem we're gonna completely solve.

Um, they're just gonna expect that there's gonna be, um, problems with the app, there's gonna be outages. And, uh, you know, companies don't even, they anticipate there's gonna be problems. They don't expect to solve them all.

Um, so it's how to deal with, um, uh, the aftermath, um, how to handle communications and, um, and get back up quickly working again. Um, so, and I see a lot of articles about that, that really, they have no solutions on, um, reducing the fragility. Like they're just gonna expect that these AppSec have problems, and it's more about, um, how they handle them afterwards.

Uh, so I don't know what your thoughts are on that, but I, I've seen a lot of articles around that, But I, I also think that that is, that is a great way to go, um, prioritizing resilience over perfection. It's not that you are going to say nothing will happen, but we all know how expensive it is to get a, um, a system to even, you know, no one's gonna try and go to five nines. It's just too expensive.

It costs too much money, and often it doesn't make sense, but you figure out if something goes wrong, then what do we do? We fix that and hopefully we make it so that that problem, uh, doesn't reoccur. So create systems that will detect, respond to and recover, uh, from those incidents effectively, and hopefully, uh, in less than a week's time.

Yes. Right. Yeah.

Well, but that's, so, so that's what, um, chaos engineering is all, I mean, chaos engineering is, it's been around quite while. It's a wonderful thing. Um, and that would put you, I mean, to my sense that puts us in the 12 factor and, and app side, um, sort of approach.

Um, I, granted there's a real continuum down into platform engineering now, because, you know, that's a whole software stack, its own with development and life cycle and everything. Um, but, uh, um, are you really saying hope that, um, just get over it and Yes. Respect it.

I, I'm, I'm, and, and, you know, uh, a little more nuanced, but I, you know, I like going all in that way. So, Uh, Invest in your observability tools, right? Know what is happening, not just, you know, in the systems, but how does that roll up and impact your end users in the app, right?

And then, um, failure's going to happen. Not that you're gonna make any, you know, you're not gonna be diligent in doing your work, but understand that unexpected things will occur. How do you recover from it?

Um, so yeah, I, I think, um, no sleepless nights if, if you have the right systems in place to, uh, to recover quickly. Okay. So the platform engineer just said to me, oh, you worry too much.

Stop worrying so much. Or maybe the platform engineering engineer just said to me, well, your app isn't very resilient. Well, I, I think platform, I'm gonna sleep tonight.

You, you worry about your app, I'm gonna sleep tonight. No, no. But platform engineering, uh, if they are doing their job well, they are a partner, right?

So if it is an organization that is setting up new AppSec, or is revisiting their processes and their practices around how they are developing these AppSec, that is a perfect time to get the platform engineering team engaged and to understand how, uh, end to end this can be more stable, more secure, more resilient. Um, if anyone on the platform engineering team says, you know, that's, you know, that's not our problem. That person is probably gonna be looking for, for a new role pretty soon.

Um, it, it absolutely is their responsibility as a partner to help the development teams understand what can be done. Yeah. com site.

And, uh, it's a survey by, uh, written by Mike Vizard. And, um, it was a thousand platform engineers and IT decision makers across, um, across the world. Mm-hmm.

And, um, they're saying that the platform engineering success rates are higher. Um, they're, and they're seeing a lot more developer satisfaction, um, improved response times, increased customer satisfaction, increased deployment frequency. Mm-hmm.

Um, so, and this was, uh, conducted by Red Hat. So, uh, we are seeing that as a, a, a potential solution moving forward. If Done.

Red Hat's a pretty good source for this sort of thing. They, they, As a former red hater myself, I will agree. Okay, good.

Alright. Um, uh, well, um, so I guess what I was driving at though, um, was that there are these two approaches to take mm-hmm. Um, one just anticipates, um, the, the, you know, likelihood of issues mm-hmm.

And you engineer both in the code and in the platform. Um, like you say, resiliency first. That's a great way to think about it, but I, I do think that a lot of organizations can and should invest in reducing their frequency in, in mitigating the possibility of, uh, those same issues.

Maybe what you're reacting to is an overemphasis on, on mitigation, an overemphasis on, like, you know, a lot of these bold statements of secure, resilient platforms that you don't have to worry about that turns out not to be the case. Mm-hmm. But I, I, I think that, you know, uh, maybe I'm on the side of both, um, that Yeah, I think it actually, I think, I think it takes both.

Um, but you know, again, um, there's A, there's a lot of shoring up of DevOps practices that could take place right now. I mean, let's be honest. Right?

Right. DevOps seems to have gotten a little sloppy. It's, it, it, it, it reached the point.

I think partially DevOps meant too many things, and a lot of those things weren't supposed to be called DevOps. Yeah, exactly. So, so, John, Jon Swartz, who Amanda, uh, cited a little earlier, he is one of the great writers for Techstrong.

Um, he, he has written about something called Authority Bias, which is outside of Dev. But the basic idea that, uh, that culturally everybody trusts, you know, vendor X or tool X or whatever it is, could be open source. Mm-hmm.

Um, 'cause of it's track record or just 'cause it's a thing. Mm-hmm. And so the authority bias is to go with that and rely on it.

Nothing is sacred. Nothing should be sacred. No, nothing is Sure.

And certain, and that's the an example of the kind sloppiness that, that we're talking about. Mm-hmm. You know, CrowdStrike's, um, status, sort of, you know, protected status within the Windows stack caused that huge adage.

Yes. And CrowdStrike's a great brand, great vendor with great products, just you have to remember, nothing's perfect. Mm-hmm.

For sure. And I'm not sure anything ever is gonna be perfect. I mean, we can have all the solutions in the world.

We still must anticipate that, um, perfection is almost impossible. And, and do you really want, you know, your team's goal plating and over-engineering the systems for what might happen? Uh, No.

But that's, this is the right conversation to have, right? We want to invest in mitigation, we want to invest in resiliency before perfection. Yes.

Okay. So let's just, if I were to advise, and you, y'all disagree with me or, or, or violently agree, or whatever you like mm-hmm. But if I were to advise, what I would say is just put that framework up when you're thinking about 2025, put that framework up and decide what your culture and your approach is, where you are gonna invest.

Just don't do all of one, all of the other. Are you gonna work more to mitigate, or are you gonna do 20% mitigate, 80% anticipate, you know? Mm-hmm.

And true it up as reality hits you, you know, square in the face. You know what, that's a really good point. That's not it for the rest of the year.

Check in regularly whenever you, with, with whenever. Yeah. Let, let's talk, let's actually go back to a couple more, if it's okay with you guys.

Let's go back to a couple more, um, topics here. Mm-hmm. I wanna talk again, bring back AI like real quick.

Mm-hmm. Amanda, you talked about, um, uh, incorporation of AI code, AI generated code. We talked about that a little bit.

Um, there's also the incorporation of external AI services into an app. Um, these are all, uh, sources, new sources of fragility that are seeing intense investment. And I think another reason to think of 2025 as the year of the fragile app, at some point, there's gonna be a backlash to, to the use of ai.

And I think that would feed into this. Is there anything more, I've heard a fair amount about the, um, the, the strain put on the platform engineers or the platform managers by use of ai. Um, is that, is that going on?

I like resource constraints and, and management. I Think it depends on the organization, right? If you have an organization that has not done their homework and just, you know, gets a basket of money and says, Hey, we, we, we need, you know, we need ai, everyone's talking about ai, we need to be able to tell the board something or shareholders something that we're doing something with ai.

Every, everyone is, is going to feel stressed, uh, because there's no real direction. It's just do something. Right?

But, uh, especially in the context of where we're going, uh, in this conversation, if they say, look, platform engineering, we want you to implement systems, um, that use ai, predictive maintenance, identify failures before they happen, intelligent monitoring, you know, what's a normal variation versus an actual problem, uh, dependency analysis, self-healing, um, you know, trend spotting, those types of things. They, even if there is more work, they will not be as stressed. Because if you have been in this situation, you can, you can, if you are working on something you enjoy, that you think is going to be good for you, even if you put in many, many hours, the way you feel at the end is very different than if you feel you're doing something that has no purpose or, or, or real, uh, real outcome.

Right? So I think if it's done with intention toward good outcomes, um, yeah, I think the platform engineering teams will be happy. The ones who are complaining are probably the ones who are being put upon, uh, with people with baskets of money that just wanna do something with ai.

All right. I, I would like to, um, point out a article on, um, this is on Business Wire. Mm-hmm.

AI powered application development introduces new IT challenges. So again, um, we're going back to the IT teams too, and they're seeing high demand for these applications. Um, uh, nearly three quarters of respondents say their organizations plan to build 10 or more AppSec over the next 12 months.

Mm-hmm. Um, but you know, where this is a problem is it's a considerable workload. So they're filling that workload, they're filling a persistent talent shortage.

Mm-hmm. Um, high cost, uh, compared to traditional application development. Mm-hmm.

Um, and so, um, these are issues they're facing and complexities with integrating AI technologies, you know, uh, the trust, uh, there's some trust issues there, um, and, and various things like that. So that's a good article to check out too. But 10 AppSec, I would be the person in the room that, that leadership would, would be frowning at, because I would immediately protest.

Right. That's outrageous. I, I, you know, the justification would need to be really strong.

And if it is 10, 10 over quite a bit of time, not 10 working at once. Uh, yeah. So yeah, there's, there's, It's crazy.

It is crazy. Like, like what they think they can do now with just because of ai, like they're just gonna increase the workloads astronomically, I think behooves us as a mitigation strategy, I suppose to go ahead and say, maybe we should try less. I know that's really hard.

Culturally, that's super hard. Mm-hmm. But, uh, hope we need more of you in the room to say, maybe we should try five AppSec.

Yes. And if we're doing great, then we can add a few And learn, learn, right. Because then you will actually get faster versus being bogged down and trying to do 10 things at once when everyone is still learning.

Um, so yeah. Well, let's wrap up. This has been a great session.

I think I've learned a few things, and I hope, uh, it's been helpful, uh, to, uh, to, to those watching as well. Um, uh, I, I'll just say, I think that, um, it, it's a trend to look out for and this framework of mitigating sources as well as just accepting that this is gonna happen and anticipating it, that's the right framework to use whatever balance works for your organization. Um, hope you wanna give some final thoughts and then we'll finish with Amanda.

Uh, if you're not already looking at platform engineering, look at platform engineering and make sure that they are a partner with the development teams. Uh, that's my statement, Amanda. And the one thing I always fall back on, because it is at the root of everything, better communication, that's always key.

That'll tighten up DevOps. Yeah. All right.

Thanks so much. Hope, Amanda, this is Guy Courier signing off. We'll see you at the next Predict for 2026.

Thank you. Thanks. This is Techron tv.

Hello and welcome everyone to the 5G Factor. I'm Ron Westfall, research director here at the FU Group, and I'm joined here today by my distinguished colleague, Tom Hollingsworth, the networking nerd and event lead at Tech Field Day here also at the Future and Group. In fact, I believe we are coming off a successful series of Tech Field Day events and know, you know what, there's more coming ahead and we'll touch on that in a moment.

But today we'll be focusing more specifically on 5G mobile ecosystem developments and certainly the key ones that jumped out at us and, you know, merit our analysis. And with that, Tom, welcome back to the 5G Factor. How have you been bearing up since the last time you were on?

Well, I've been busy. We, uh, we had an opportunity to head over to Amsterdam to Cisco Live Europe, and, uh, got to hear about some of the cool advances that they're making. There's a lot of AI out there, but there's a lot of cool networking as well.

And, uh, it's, it's all kind of coming together, right? Like we're seeing the moves that are being made by the companies and how they're kind of combining to change the way that we do stuff. And so I'm kind of excited for the future.

And with Mobile World Congress coming up, who knows? Oh, well, yes. I mean that perfect segue into, you know, the overall conversation.

And before we really jump right in, speaking of, uh, tech Field Day, we have a networking field, day 37 coming up on March 19th and 20th, uh, featuring key players such as, uh, BT and Selector ai. Any, uh, additional comments on, you know, say the upcoming networking Field day event? com to learn a little bit more.

Exactly. And that I think, um, is definitely warranted. And well, hey, let's go into the mobile ecosystem.

And I think the first thing that we'll address is open ran. And as we know, open RAN has certainly been a constant theme for the last few years, and its development has, you know, it's been incremental, I think is a, a good way of putting it. And what is going on now though might actually spur a bit more open ran, uh, adoption here.

And to, uh, be specific, uh, we see that Ericsson is demonstrating its commitment to open ran by advancing the O2 interface with Dell and Red Hat. And as background, why is the O2 interface important? Because it's defined, first of all by the O RAN allowance, uh, alliance.

And it plays a critical role in enabling the goals of open ran by supporting the, the dynamic and flexible management of cloud infrastructure that in turn supports ran networks in a multiple vendor environment. And so that's really the underline right there, open ran, it's really about enabling interoperability amongst multiple vendor products without really too much trouble. And as we know, you know, it takes effort to get to that level where an operator can simply put these pieces together without having to, you know, think about it too much.

And so what's developing here is that Ericsson, Dell and Red Hat are carrying out proofs of concept to validate the implementation of the O2 interface. And that's showing, you know, really the ability to integrate cloud ran management, which is aligned naturally with the open ran specifications for the O2 interface. So that's really a follow up on the O one interface, really enabling now the inner working of the cloud components with the overall RAN implementation.

And what is going on here is that the collaborations using Dell Telecom infrastructure blocks alongside Dell Telecom Infrastructure Automation Suite and Red Hat OpenShift, which is providing the northbound integration towards the Ericsson intelligent automation platform or EIAP. And that is its open network management and automation plat through platform, through the O2 IMS interface. And also the O2 interface is providing that standard interface between the RAN management and automation layer and the O Cloud infrastructure.

So I touched on, on already, but this is providing, you know, more detail as to why this is so critical. And what that does, it separates the infrastructure and the management layers, and it has two key functions. First of all, the O2 infrastructure management service or O or IMS, and that's what we mean by IMS.

And this context enables the hardware and software resource management as well as monitoring at distributed site locations, delivering workflow automation. I keep saying automation, that's gonna be critical if not essential for any open ran implementation, because when you put together these different, uh, components you need to have automation built in. Otherwise, what's the point of adopting Open ran naturally.

And second, the O2 deployment management service or DMS is responsible for the lifecycle management of the open ran network functions. And so automation and lifecycle management are basically joined at the hip. You basically have to have that in order to have just that a robust automation implementation that's reliable and is not going to, you know, cause you know, the, uh, sweats at night should something go wrong as also as well as applications that are hosted by the O Cloud.

And so, uh, to your point, Tom, I'm definitely looking forward to the demonstration of this at Mobile World Congress 25. And from your perspective, you know, what else is going on? You know, not just with the O2 interface, but you know, with the overall open ran.

Cause I like the fact that Ericsson's really like pushing the O2 interface, but not just paying lip service to it, they're implementing it. And I feel like that maybe is one of the reasons why we never really got good implementation of OpenFlow as a software defined networking system is because companies were interfacing with it, but they were never really adopting it. And, uh, yeah, okay.

You could say Brocade probably did with their open daylight controller, but I, I don't feel like, you know, and we all know what happened to them. They're like four acquisitions down the road right now of their technology. But I feel like with Ericsson kind of driving this and saying, this is how you're gonna have to use it.

We're eating our own dog food, drink your own champagne, whatever, you know, uh, idiom you wanna use for that, they're forcing companies to write to that spec. They're forcing the companies to improve it, right? That's one of those things that you really cannot, you can't lab this up like this has to meet the, the real world impact of it.

And I, I love the fact that they're kind of following that same model, right? They're decoupling the management plane and the data plane. They're making sure that these resources can be moved around and can be utilized in ways that help kind of scale.

And, and that's one of the things that Open Ran really needs to kind of hit on is the ease of use, the ease of programming to the standard and the fact that companies can adopt it without having to pay heavy licensing fees or play ball in somebody else's court. Because what's one of the other things you run into with other competing standards is, oh, well, um, if you wanna play with us, you have to write to our standard instead of writing to develop the standard, which is something that companies really love. 1 Q trunking.

And basically that was an industry lining up against an incumbent saying, well, we're gonna develop our standard and everybody's gonna utilize it and basically drag the rest of the industry into that. I think with Ericsson kind of leading the charge here and putting some real money behind the development and resources developers that they can really kind of drive this as kind of the leading standard for people to write to. 'cause when you have Dell and Red Hat writing to it, I mean really all you gotta do is get HPE on board and you've locked up pretty much every vendor out there.

Yeah. And those are, I think, very important points, Tom. And I think it's also well tied in terms of the sales and marketing aspect.

Yes, we're heading into Mobile World Congress, uh, 2025, but I think it's, uh, no secret that Erickson's gotten some grief over how it's been implementing Open Ran. And I think specifically it's related to the at and t contract they won where they basically became the primary integrator for, you know, the implementation of, uh, at and t's, uh, 5G Network and open ran capabilities moving forward. Although, yes, Fujitsu was included in that implementation on the radio side, but now we're seeing Ericsson really upping the game here.

It's like, okay, we're definitely working with, you know, very critical partners in the mobile ecosystem, certainly in 5G, and that includes, uh, naturally Dell, but also, uh, red Hat and its OpenShift implementation. And to your point about real world implementations, it's worth noting that T-Mobile just recently picked Red Hat OpenShift for its cloud automation requirements. So this is sh now showing that open ran and, uh, key aspects such as cloud automation are definitely gathering momentum and steam.

And these can, I think, be difference makers in 25 as open ran, you know, it basically takes on a larger share of the overall ran pie. And speaking of market shares, I think it's also important to, uh, look at what's going on the device side. No, that there wasn't a dramatic shift in market share here, but it could be maybe the needle further down it comes specifically to the iPhone and that's, you know, a, a Apple announcing the iPhone 16 E and that's a new addition to the iPhone 16 lineup that is designed to really offer powerful capabilities at a better price.

And the iPhone 16 E is using the A 18 chip alongside the new Apple C one. And this is gonna garner, I think, a great deal of attention because it's the first cellular modem design by Apple and iPhone 60 E is also built for Apple intelligence. And, uh, it's really setting up to provide intuitive personal intelligence that delivers helpful and relevant intelligence while taking a, a, a step forward in privacy for ai.

And what's going off the announcement is that the new Apple C one is basically replacing, you know, the Qualcomm, uh, implementation here. And so, you know, Tom, from your perspective, what do you think is a key takeaway about, you know, apple coming out with the new iPhone team, iPhone 16 E and announcing, you know, the C one? I think I'd be worried if I was Qualcomm, because this is one of those things that Apple is known for just to call Intel and ask them how that worked out for them when suddenly Apple wasn't buying tons of Intel ships.

There's a reason why they want to do this. Well, first of all, we know that they bought this technology, the modem technology actually came from Intel and they've been developing it for quite a while, right? Like, I can remember reading the rumor sites and hearing, you know, folks like Mark Germond saying, oh, you know, the iPhone thirteen's gonna be the one that has the Apple modem in it.

No, wait, 14, how about no, the 15, well, they finally got it right. And I think that the value is that if Apple controls the modem technology and they have a development team working on it, then they can do what they've done with the M series chips, which is continue to drive innovation in the chip set that is Apple specific. I mean, look at, say the M four max, or I'm sorry, M1, M four max processor.

It is, it's an arm processor, right? But it has specific layouts for things such as, um, acceleration for video codex. So like when I'm doing video editing, I can toss those, uh, encoding jobs off there and they run a whole lot faster.

Well, you may not think that that's such a big deal unless you're a video editor, right? But what if I could build those kinds of optimizations into a mobile device? What if I could make the battery life, you know, 25% longer for the same size?

What if I can optimize certain other things for, uh, I don't know, uh, apple Intelligence? Do you see why it's so important that Apple controls the whole chip set? Because they can already do that with the N slash A series, but if they could do that with the modem, they could do even more.

They don't have to wait for Qualcomm to continually release updates. They don't have to, uh, you know, be at the mercy of a company who's supplying these parts. I think this is a huge leap forward.

Now, for those of you out there who are like, well, why did they do it with the iPhone 16 E? This doesn't make a whole lot of sense to me. Would you rather they have released it with say, the iPhone 17?

And if there are any problems to iron out that now you have a, uh, flagship device that has a massive amount of problems, this is how you do product development. This is how you release new features in a video game. This is how you release new hardware features.

You take a small test case with a very specific aim, you implement a new piece of hardware because the rest of the hardware is pretty much the same, right? It's a known quantity. It's, it's basically the guts of an iPhone 16.

But they've taken out some of the, the other little pieces like MagSafe, but now they're trialing this modem. So if it blows up, then they can go back to the drawing board and they can fix it before it actually goes into a mainstream release. That's critical because I think when you give the iPhone 17, you are gonna see Apple modems in the iPhone.

You're gonna see Apple controlling that as we go along. And just, you know, for those of you who don't understand how important that is, we are now two years past the release of the iPhone 15, where the USBC uh, charging port in it once the iPhone 16 E was released, apple has no longer sells a device that has a lightning port on it. We are, we're, it only took them two years to Rev from, we're trying this new idea to, we're all in on it and everything else is kind of off the market.

How long is it gonna take for them to trigger a refresh where they no longer have to support Qualcomm modems? 'cause that's the other thing. If I no longer have to write a software stack to support somebody else's hardware, I can create tighter integrations.

It's one of the reasons why Mac has been such a stable operating system for so long, is because they don't have to support every hardware manufacturer under the sun. So I think this is an amazing move for Apple. The question is, is it gonna spur a company like Samsung to do the same thing, or are they gonna continue to buy from Qualcomm?

And likewise, how's Qualcomm gonna react to it? And I think those are all outstanding points. Tom and points, I think one thing, uh, that is working to Qualcomm's benefit is that this move has been anticipated by them as well as the overall mobile ecosystem for several years now.

Now, theoretically, had this, uh, happen at, I'd say two years ago, I would say the impact of Qualcomm would've been a bit more direct and, you know, more concerning. However, I think that Qualcomm has really been doing an effective job of, you know, anticipating this and, you know, preparing, uh, the fact that, hey, we are going to continue on with our revenue diversification strategy. That's really been already, uh, paying off in terms of, you know, playing an area such as automotive, such as IOT and so forth.

And so this is something that I don't think is going to, you know, cause much of a drag for Qualcomm. Also, Qualcomm's planning assumption remains that there'll be 20% share for the 2026 launch with the current ship and QCT agreement that ends after that with really no renewal, uh, being assuming to kick in. And also it's a reminder that the chip set and licensing agreements are separate.

And so that means that Qualcomm's technology licensing or QTL has a license agreement with Apple that will continue to run through 2027. So they have, I think, a great deal of buffer and runway here to adjust to the fact that Apple has finally replaced, you know, the modem aspect of working with Qualcomm. And when it comes to the iPhone, now let's look at what's going on in terms of the core of the network.

We're going from the device to the core. So we're really doing an e ecosystem stretch here. I think it's interesting to note that Telstra, at least it's promoting itself as becoming the first operator in the Asia Pacific region to benefit from a programmable network with 5G advanced capabilities due to its collaboration with Ericsson.

And what's important here is that under this four year deal, Telstra upgraded, its ran with Ericsson's, next generation open ran hardware, and 5G advanced software will also implement AI and automation to optimize network management through self detection and self-healing capabilities. Also, and it invoke this already, Tom, is the fact that it can open that network to more developers across the wider mobile ecosystem through network APIs and who knows further out AG agentic ai. So, and looking at, you know, what's going on with network APIs, this is good news because, you know, with more developers, you know, looking at how can we leverage the Telstra network to, you know, enable more cool applications and capabilities.

It's also, I think, important to note that this is showing, you know, there's momentum here that's paralleling what's going on on the open ran side. So what we're gonna do is, you know, find out how 5G advanced network capabilities can work in a production network. And Telstra I think will be a good example of this.

And that includes, you know, leveraging a wider array of APIs. And with that, Tom, what do you think is, you know, important here in terms of not just the fact okay, that Telstra, Erics have gotten together to put the pedal to, you know, 5G advanced capabilities, but also enabling network programmability and 5G networks? I think it's super critical because one of the things that we hear a lot about is how programmability is gonna extend our networks, but it's difficult to see it upfront.

And one of the ways that I have seen it personally in the wifi world is through radio resource management. You know, being able to look at a, the, the airspace around you and make decisions about where clients need to go and how we need to allocate resources so that it works out a little bit better in general for everyone. Now, scale that up to a city or, you know, a, a a a county, basically that's what Telstra's talking about doing here.

And not only that, but if you are someone who is providing a service that runs across that network, being able to tap into it and pull data and statistics is super critical. So think about something like, uh, you know, security camera footage or something like that. If I have a remote device that is uploading pictures of security camera footage for a given, uh, you know, timeframe, window, what have you, if I know that congestion is low and during a certain time of the day, I can program my system to look for those statistics and upload during that time so that I can ensure, uh, proper transmission or cheaper transmission.

Because it's another thing that people need to understand is that there's still a cost associated with moving this data around. And that's just one of the applications that you can come up off the top of your head. But by programming to that standard, by making sure that people are utilizing Ericsson's, uh, you know, OAN specifications and capabilities, they're ensuring that whatever comes out the other side is compatible with other O ran, but that gives them leverage to ensure that more customers are writing their specifications to O ran so that more people are going to demand either use of that technology or would consider picking, uh, Ericsson as a provider in the future, knowing that I get 98% of the things that I need from a functionality perspective with an interface that my developers are already comfortable writing to.

Yeah, and I think it definitely brings out, you know, that it's a worldwide phenom, you know, 5G network, uh, capabilities and, you know, uh, the fact that Telstra Erickson are laying claim to be the first in Asia Pacific. Okay, you know, we'll include Oceania as part of Asia Pacific for, you know, the purposes of, uh, understanding what's going on here. But I think it's demonstrating like, yes, openness can make a difference in relation to say, relatively closed networks, such as in mainland China, where there's a lot of progress and innovation going on.

However, uh, I would say when it comes to these areas, open ran as well as, you know, network programmability, we're seeing, you know, how there can be differences at least when it comes to time to market and delivering capabilities that will ultimately, you know, prove that 5G can actually deliver the things we've been hearing about for a few years now. But now we're actually finally getting networks that are not only are 5G standalone, but are also supporting actual 5G advanced capabilities. And I think that this is good news already heading into Mobile Congress, and I'm sure certainly looking forward to talking about these, uh, you know, programmability capabilities at the event itself, not just with Ericsson, but certainly with all the operators that are there, Deutsche Telecom, et cetera.

So this is going to be, I think, uh, an ongoing ecosystem momentum aspect that we'll be talking about more and, you know, upcoming 5G Factors. And with that, thank you again everybody for joining us and be sure to bookmark the 5G Factor, we're on the future and group website as well as Tech Beal Day and what we touched on in terms of upcoming tech Beal Day events. And again, Tom, thank you for joining and hopefully, you know, there's, uh, you know, a successful Tech Field day event coming up here shortly.

Uh, there always is. com for the schedule, and, uh, if you pay attention, you might even see one of the other co-hosts there on a regular basis. Naturally, and I, I know I'll be there.

So with that, uh, thank you again, everyone. Have a great open ran and 5G Day Ladies and gentlemen in this corner, the Once and Future Champion of ai, IBM, you're watching Textron Gang. Hey, everyone, happy, uh, Thursday to you.

It's been a crazy week. It's Thursday already. I, I just, it's flying by so much news, so much going on.

The, the chaos just keeps spinning round and round. Um, but we've got a lot to go over today. I teased it a little bit upfront, uh, big news from IBM in, in the AI space, but I don't know how much of it is.

Well, there's a lot of it that's ai, but there's more to it than ai. But we're going to get into that. We've got that, we've got Google what's going on with them and, uh, some things.

And then we, we, interestingly, we, we, we found some people with a conscience in the, uh, department of Government efficiency. I thought they, they purged all those people. But anyway, let's first introduce our panel.

Who's gonna discuss these matters today? I'm gonna start off out west, uh, with our Silicon Valley eye in the sky. Jon Swartz.

John, how are you? I'm doing well. I'm, uh, it's a crazy news cycle as you just mentioned, Alan, so we're just trying to keep our head above water, All, all one guy.

I think a lot of people are in that boat, John. Yep. Just trying to, not just tech.

Yes. Yep. Trying to keep your head above water.

Moving from there, I guess we'll go down to Austin, Texas, where preparations are underway for South by Southwest. We hear it's our own and a whole award and good to have you. How's everything?

Always a pleasure. It's wonderful, beautiful sunny weather here. Couldn't be happier with that.

And preparations are well underway for South by Southwest. Be You've been exercising your Liver. It's be A good one.

It's gonna be a good one. Sorry, I said, have you been exercising your liver? I, I need to find another one.

I need to get a donor probably by the end of the week, but It'll be good time. Good for you. Moving up to, uh, Ohio, where she's back from her recent trip to New York.

She's our editor for Textron ai, gestalt it and more coming down the pike, Sulagna Saha Saha. Hi Sagner, how are you? Hi, Ellen.

I'm good, thank you. Good. It's great to have you.

Thank you. Uh, yeah. Okay.

And then finally the Dean of Harrison, our chief content Officer, Mike Vizard. How are you? Dean Harrison is in Westchester County, otherwise known as the central of all things IBM, because well just about everybody here who's in I Tech seems to work for IBM.

Yes. The old Armon. So ar Armon isn't Westchester, is it?

It, it's it's one county North Putnam, but, uh, well actually Armon is in Westchester. It's, um, I forgot the other town. They used to be where they had the big pyramid building that they abandoned a couple years ago.

Hmm. Okay. I always thought it was Putnam, but could, yeah, I mean, certainly, I mean, here look down here in Boco is a big IBM town too, right?

They Have a huge office in presence in Austin as well. Yeah. And San Jose, California, they had the Coddle Road, uh, labs where my dad worked for 20 years.

Yeah. I mean, they look their IBM They're everywhere. Yeah.

They were for More than a hundred years. Um, but some big news out of IBM Mike, why don't you kick us off with this? All right, let's jump in here At IBM bought data stacks, which originally cut its name on this, uh, open source Cassandra, no SQL database.

It was more of a higher performance database than your average document database. And it got a solid following. And then data stacks extended its reach into vectors and their ability to use that as a foundation for training, uh, models.

And then they also built a, um, a more elegant alternative to lang chain, which you can use for training the models. And it's one of the lang chain being widely used open source tool, but it's a little cumbersome. So DataStax has this alternative, John, you wrote this story, but what are they saying in the Valley about all this?

Because, you know, here at one point IBM was supposed to be, you know, the next overlord, right? And Watson in jeopardy, and then, uh, suddenly they were chasing everybody. I think the same, and I think the same applies to Silicon Valley.

They're almost an, I mean, I hate to say this, given the presence that I just mentioned that they had in San Jose for so long, they were the tech company here. They're an afterthought in the valley. They're rarely talked about.

Um, they have a presence, but it's tucked up in the hills in Northern San Jose. Um, in a sense, when we talk about the AI race, IBM is rarely mentioned here in the only references to Watson. Um, and that's from years ago.

So that this idea that IBM is, is acquiring data stacks is interesting. I mean, it's a move by IBM to kind of turbocharge its Watson X portfolio and kind of make this, make the use of gen generative AI within enterprises and kind of accelerate that. Um, it's, it's importance.

It's just, you know, Mike, it's here. It's so interesting the way things develop here. And this is not so much about IBM, but about just the perception of companies.

Here they are. The hot company for a few years, like IBM was then my Microsoft was the anti IBM, and then Google became the anti Microsoft. Apple is the anti-everything.

They, they have their runs. And I would even venture to say that a company like IBM is starting to get a little long in the two, excuse me. A company like Apple is starting to get long in the tooth and being considered kind of an older fuddyduddy type of company versus the upstarts.

So the, unfortunately that's the culture here, the new shiny object. So the announcement by IBM is interesting. It will have an impact, I would assume, among some of the customers that already use data stacks and financial services.

But for the most part, it's kind of under the radar. Um, I mean, it's a, it's a, it's a data grab, right? I mean, it's, it's the AI gold rush for data.

Um, I have nothing but good things to say about IBM because they were very good to me. I was in their futurist program for a very long time. They flew me around the world, uh, to just try products and tweet about it.

It was really fun. Um, but I think being cool in Silicon Valley is, is something that I used to care about and I don't anymore. It's very freeing.

But I mean, it's a, it's, it's essentially the future. You're living in the future when you live in Silicon Valley, and that means a lot of sacrifice to your day-to-day life. It also means that you're a startup or you're nothing.

And so I, I don't think that that's really necessarily a gauge of success. IBM has had the staying power, uh, uh, beyond any other tech company. And this just shows you how they plan to continue to evolve and survive.

We, You, you know, the one thing I was gonna mention too is the, um, the idea that Silicon Valley reminds me, you, you spark this man of Hollywood, you know, you're hot, you're in, and then you're discarded until you come back and do something again. So there are all sorts of companies and individuals who are the person of the moment who went away. So staying power is really important.

And I, you're right, IBM has been around for more than 110 years. I think I remember doing one of those a hundred year stories years ago. It's, it, it, it's, it's interesting.

But, and again, in the, in the big picture, the frame of things, this is kind of a small piece. I don't mean to undersell it, but I, that's basically a perception here at least. So, so go ahead.

I'm ahead, Mike ahead. No, Mike, you go. So the thing with IBM is they, they obsess about the monetization and rightfully so.

But what happens is, is every time they do something new or interesting, or they acquire it, they shove it in this kit bag that they give to IBM consulting, who then goes down and visits all these enterprises and, you know, integrates all that stuff into these global 2000 companies. And that's the business model. And so that's why every time they acquire something or they do something innovative, it just kind of falls by the wayside because when it comes to actually implementing it, there isn't really a push to build a platform and invite developers.

And I mean, they talk about doing that stuff, but they, on the execution side, they just blow it every time. 'cause they're kind of obsessed with being a consulting company at the end of the day. In fact, they, uh, just unveiled their AI integration consulting services, uh, around agent tech ai, which is supposed to help companies, uh, impact generative AI more safely and expedite the adoption just yesterday, I think.

Uh, but I feel like IBM maybe onto something, I know they got leapfrogged a bunch of times, even though they were first really one of the first people in the AI race. Um, so I think with their, lately with their efforts around what's next, uh, their AI product portfolio and, uh, and the data stack acquisition. And then, uh, with the data stack acquisition announcement, they also announced, uh, an agreement with the r there, the new, uh, Saudi airline company that they're integrating what's next into their operations.

And, uh, and with the upcoming MWC Barcelona in March, I hear that AI is going to be a big, uh, area of focus. Um, so IBM claims that their AI journey started back in, you know, uh, nine in the 1950s when the programmed the 7 0 4 mainframe computer with the, to play chess and wherever. Um, but, um, really, and, uh, with IBMI feel like that this company has touched literally every milestone technology in the tech space for over a hundred years.

Like punch cards, PCs, uh, mainframe. And, uh, I feel like they're more gearing up for the ai, uh, uh, revolution than before. Um, like, uh, and like all big companies and that, that have skin in the game, the vision is to embed AI across the board, which may not necessarily be, uh, like, uh, the most, uh, distinctive strategy.

But I feel like that, uh, they have done a few things lately, which shows that they are sort of, uh, going to be a part of the decidedly be a part of the ISI mean, we saw at Hot Chips last year, they announced, uh, that, uh, they were, uh, turbocharging the next generation of Z mainframe, uh, with the tele two processor and the spray accelerators. Um, and those chips are coming out this year, hopefully. Um, yeah.

So it appears that they are vying for, uh, the top, not the top spot maybe, but at least be in a shoulder to shoulder with, uh, the big companies that are in the AI race. So, let me weigh in here. It is interesting, John, you know, public perception and not just Silicon Valley public perception, but broader public perception.

Let's compare three companies. You've got IBM, which is you said has about 110 years old. You have Microsoft recently celebrated its 50th birthday.

Apple is is about the same, isn't it? 50, yeah, 50 in April. Yep.

Apple's also 50. And let me just throw another one in for the, for grins and giggles. Google, right?

Google's probably, what about 2002? 2003, 2001, something like that. Um, so let's say 25 years, half the age of the other two perception, Google is still perceived as an 800 pound gorilla controlling the markets.

It plays in. And as an innovator, apple, apple is having an innovation problem, an innovation dilemma right now where the, the market is saying, where's the innovation? We haven't really seen innovation since Steve Jobs passed away.

Microsoft say what you want, but Satya Nadella has reenergized that company, and they are perceived, they, they were out in front with OpenAI. They, you know, that investment was probably the best 10 billion they ever put in. Um, you know, and they, so they are, and they're, you know, second in cloud and all of these things.

So even though they're 50 years old, they're, they, they've reinvented themselves a little bit. IBM as says punch cards, the birth of the pc. The, the first time we started thinking of AI was real was Watson and the chess game and all of these things.

They have a hundred year history of leading innovation. Uh, the, the power PC chip, they don't get enough credit for that. When we look at what ARM is today and all of that, it, I mean, look what they did for, for, for those chips, the non-Intel chips, uh, mid-range, you know, mid frame, mid-range computers, mini computers, so many innovations that come out of there.

Exotic materials, quantum computing, there's still a leader there. But the mo the MO is, they're first with these things, they're out ahead because they do plow money into r and d and give them credit, and they do buy and acquire a lot of companies give them credit. But somewhere along the way, as Mike says, those accomplishments go outta the hype cycle, not necessarily into the trial of disillusionment, but they, they level out and you don't see them.

And part of it is because they're not necessarily, like Broadcom does this too. They're not necessarily looking for new customers. They just wanna go deeper into the customers they already have.

And so the customers they already have say, Hey, do you have the IBM AI built into your stuff? Yeah, I think so. My IBM guy put it in, or whatever, or, you know, they talked about it.

So kudos to IBM for being able to kind of surf that wave all of these years. But I think the key to their success is not necessarily surfing the fastest, the highest or the hardest. It's, it's staying right in the, you know, in the top, in the top right quadrant of the pack, but not necessarily in the lead.

Now I do want to talk a second about data stacks though. 'cause I'm a startup guy. And let's give a big shout out to the data stacks people you want to talk about pivoting and reinventing yourself, right?

These were a big data company with, with Cassandra, right? No SQL database jumped on the Vector database bandwagon early on when, you know, companies, frankly like Mongo, that had a Vector database solution, didn't realize they what to do with it. And, and they went that route with the Vector database and then took it the next step.

And now they're being sold here as a, an AI company. You know, there's OpenAI, there's, there's, uh, you know, anthropic and data stacks. Where did they become an AI company?

But I'm sure they got with enough data as an AI company at this point. Exactly. Everybody's an AI company.

Like we're all AI engineers. So I didn't see what they paid for Data stacks. I don't know if any of you have.

Yeah, but I didn't like here, you know, on the grapevine or anything, but I'm sure it was a pretty penny. This wasn't a, uh, a fire sale. And, um, congratulations to the Data Stacks team.

That's what startup culture is all about. Good for you guys. Now we'll see what happens to them as part of Big Deal.

So The one thing I, I would add to all that, and I remember having this conversation with IBM marketers and I was like, why don't you market these platforms and these technologies? And, and they explained it this way and they said, fundamentally, we're marketing IBM people and expertise and all the other things are enablers for that. And so, but they lead with all, you know, if you're here in New York, you can't go anywhere without running into an IBM ad.

But they're all the same. They're all about, you know, somebody at IBM has some expertise that you need, But I wonder how much NDL has changed that, You know, I was gonna mention, can I mention something that, that that happened with Jeanie reit, Gina Jeanie remit, um, just to give you an insight behind the curtains, when this company IBM was doing interesting things, as Mike said, they're almost treated like a consulting company out here. And again, maybe it's because they're an, an East Coast based company that seems to have some sort of humility, which is lacking out here.

But the one thing that was interesting was that Ginny Remit would always submit to USA today when I worked there as a tech editor, she would submit these columns to explain what they were doing because their marketing was kind of under, was kind of ho-hum. And, and they had, they would try to work out a sweetheart deal with our editor in chief to, to run some of her commentary. And I would sometimes say, this is, you know, b******t.

This is propaganda. We ran it more often than not. But that gives you an idea that even they acknowledged that they weren't getting The message through.

So ndl come back to that for a minute. 'cause it is significant, right? So when they spun out ndl, they really put all their like, tech support managed services stuff in there, but they kept IBM consulting with the main company, which allegedly is a quote unquote software company these days.

'cause it has higher valuations. But, you know, point of fact is the route to market is still through those consultants. Fair enough.

And Another another reason I feel like, uh, why it does not IBM does not come up as one of the most frequently named names, uh, at least in the AI conversation, is because, so they put like eight years behind Watson, but got eclipsed by Chad Chip. And also a bigger reason is that their share prices did not move much. At least, uh, their AI revenue was not, you know, through the roof or anything.

So that didn't get Well, they never figured out how to monetize Watson. I remember being at IBM think 10, 12, 10 years ago, and they were showing me like dating AppSec built on Watson that would find you better dates and stuff like that. But they just think they did it.

They, you know, they were out there and they, they kind missed that one. But, Hey, hey, one last thing on the, you know, who else we talk about a lot less these days? Who?

Red Hat. Red Hat who? Red Hat, who they've been, they've been, you know, bored.

We will be assimilated. They've been assimilated, they're now Red Hats who wear red ties with blue suits. Isn't that the uniform?

Um, anyway, hey, let's take a break. We're gonna come back. And you know what Google's done us wrong.

I'm speaking on behalf of all publishers now. You're watching Textron Gang, Discover Textron Group, the epicenter of tech innovation. We are your go-to for reaching IT leaders and practitioners worldwide.

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Let's revolutionize your tech journey. Contact us today and tell your story to the world in the most powerful way with Textron Group. Hey folks, we're back and we're talking about a lawsuit actually involving Chegg, which is a publisher of medical information and they're suing Google over their AI summarization capabilities.

And it's interesting, I'm not quite sure what the legal grounds are, but one of the claims that they're making is that this AI summarization capabilities hollowing out the internet and the knowledge thereof, because it's just summarizing everything. And if you watched a previous episode of Textron Gang, we talked about whether or not AI was making us all stupid. And this is part of that kind of conversation.

But the question then becomes, um, is this, and we'll start with you, is this kind of shift here with these ai, uh, summarizations gonna ultimately wind up killing all the companies that create the content, and then therefore we won't have anything on the internet that's worth looking at anyway. So, Well, great question. I would argue that content creators were already under siege, monetizing based purely on traffic has been a business model that's been failing for some time.

I mean, you remember when people used to make money from ads, from banners, banner traffic, skyscraper ads, that, that's been leveled out. Um, I think it's interesting because to me as an SEO keep in mind this is what I do all day every day. It's not really that different from Google answers, Google answers, you know, where it asks a question and it answers it.

The, this is sort of just a rehashing of that. Um, but I think that the, the, the crux of the lawsuit is that Google is eroding the demand for original content, which I don't actually agree with. I I don't think that AI generated summaries necessarily reduce the need for people to read and want more information.

Does it give them at a glance, does it give them a link? Yes. Um, undermining publishers, publishers' abilities to compete was another point, which I, I think is probably a fair point to make because they are essentially taking snippets of it and benefiting from it.

So I think that the perplexity model is a little more democratic, where they're brokering partnerships with New York Times and other big publishers and saying, Hey, let's, let's work out a financial arrangement. Google doesn't really do that. Um, any arrangements they make with Twitter, LinkedIn, um, you know, these social media sites that they've done for years have all been sort of quiet partnerships, right?

Uh, I like the fact that perplexity discloses, but you're talking about 120 million searches, uh, a month versus 130 billion. So, so the economies of scale aren't there. Um, but the other argument was that they're creating a hollowed out information ecosystem basically, that it's gonna lead to a decline in quality and trustworthy information.

Well, can we put that at Google's door? It wasn't that happening anyway with disinformation and other things happening. Are they making it worse?

Probably. Um, I think that a lot of publishers are bent outta shape because of the drop in traffic. Uh, but that could happen with an algorithm change that could happen with a lot of other things.

It just so happens that AI has become a boogeyman for these sites because their business models are failing. Are they justified? Probably.

Um, I do think that we need to value free and fair press. We need to value information and the ability to, to find good information. Do we want Google doing this for us?

No, but again, it's not that new. It feels new, but it's not, um, because of the Google answers that's been around for a long time, and this is just a sort of more prominent way of doing that. It's a little more at a glance.

You don't have to toggle it. Um, but I, I don't think Anybody knew where Google answers was. So that's, Yeah, Google answers are where you see it, it's question and then you click, yeah.

So 30 to 50% of searches at this point in time, and it, it varies based on the study you read, 30 to 50% have AI overviews, so this isn't even rolled out to all searches. So we have to think about what is the impact gonna be once that full rollout happens and it, and they're adding countries every month. Um, so what is that gonna do globally to information?

I don't know. But it's something that's being very closely watched and studied. And I don't think this is the last lawsuit we're gonna see.

I think we're gonna see even more of these because it, it's essentially taking co-opting information that is not theirs and presenting it as theirs is essentially, I think really, really not untrue. I think that they were faired in stating that. So let's cut the crop.

This isn't about AI per se. This is about the M word monopoly. Google has a strangle hold on, people searching for information on the internet.

And for the 25 plus years that they've been doing it, they did it in conjunction with most content publishers in the world, including Textron. Because in exchange for their being able to spider our sites and we want all of our information and we're gonna put it in as Google friendlier format as we can and publish site maps and all of these things so that Google can get all of that. The quid pro quo there was then when people search certain terms that are germane to us, our sites would rank or would show up hopefully in the top three, if not the first page.

And people would come to these sites to consume that content and get that information. They didn't get the information per se at Google. They found out where to get the information from Google.

And so companies, publishers, like a text strong and and similar we're getting 75, 80, 80 5% of their traffic from what we called organic search Google search. 'cause they rep represent 98% of the 99% of the market. Now starting with Google Answers, which was clunky and not as elegant maybe as the AI stuff is now Gemini, Google made a concerted effort to say, we don't wanna lose that traffic, we don't wanna send that traffic to other people's sites.

We wanna keep that traffic here so we can serve them ads so we could gather more information about them so we can do what we do to monetize these things. Right? And it, this didn't start with ai Ann, you're right.

We, we've seen a steady erosion of traffic from organic search for a couple years now. Um, but the quid pro quo is still there. Well, if you are not gonna send me traffic, don't use my information because you are now monetizing my information without my permission.

And the same way we're mad at OpenAI and we laugh at OpenAI talking about deep seek using open AI's information when OpenAI didn't pay for that information either. Well, I got news for you. Google didn't either.

I I would say Gen Z millennials, they're, they're less interested in using Google search. Um, You're right, TikTok. Yep.

Yeah. The under 30 crowd is more statistically likely to search TikTok for local search than Google. And that's because that experience is better.

So there, there, the empire is crumbling a little bit, and this may be a move to counteract that. Uh, but they're still the giant, I mean, they're still the one that this book I wrote about SEO for O'Reilly is still, I mean, I say in the beginning, I hope it's not always about Google and that was 2017. And yet here we are still talking about Google.

So, so every action has an opposite reaction and everybody who creates content is gonna start putting up registration walls and putting up stuff to prevent you from getting to that content without actually going through then to get to it. And I, that's just gonna be the natural order of things. 'cause to Alan's point, the quid pro quo is gone.

So no quid, the pro is gonna go somewhere else. If you're making money from your content, it is generally going to be from something other than just directly people viewing said content. It's gonna be you talking about it on Instagram.

It's gonna be you using affiliate links as an influencer. If you're a stand, you know, a a rogue person like me, I have a business, right? I have an agency that I sell my services, right?

So I'm not monetizing directly from content I put out there. So that model, I dunno if that makes you rogue, Ann, that that's a harsh word. Well, I've worked for myself for 15 years, so I, I guess that's pretty rogue.

But, uh, but the, the point is that making money from just putting out good content as an individual, as a small outfit, there's some concession you have to give, you have to do conferences, you have to do, you know, just making it on its own is not something that has been viable for a minute. And we can blame Google for that, I think to a large extent. But, um, I don't know, can we put the, all of this at their door?

I don't know. Yeah, I it just seemed all Inev inev, um, go ahead, slog. Now.

Um, yeah, I was saying that it's really not new. 'cause every time Google changes its algorithm sites get pushed to the back pages, some even get indexed, and then there's this obvious drop in engagement and traffic. But, uh, what I think is really harting some of these publishing companies is the fact that, uh, with the Google over AI overviews, so the, the key purpose of AI overview is to provide quick answers and save, uh, users browsing time.

And so that way com uh, users would just simply, uh, read, like, browse through whatever the AI summaries are and probably would not go to the page that actually has the original information. But to make matters worse, these answers are unverified and often inaccurate. We, we all remember the, the glue on pizza and Roday keeps a doctor away answers from last year.

And uh, yes, Google has done a series of changes. And, uh, to be fair, Google AI alone is not Jan. You know, Chad Chip wasn't that great either early on.

Uh, but the key issue here is that Google or o OpenAI or whatever company is doing AI such, they're harnessing publishers original content who, uh, which they put money and years into to create, uh, and to generate these summaries that are not even reliable. So that going forward is definitely going to be a problem. And, uh, that's probably what their point is.

Uh, the publishers who invite you to go Google in 2023. And, uh, there has been a slew of, uh, litigations lately based on, in and around this, uh, area. I, I absolutely you're correct.

And I think if I could make a prediction here, I think, you know, the reason I always bring a perplexity is that it is time-based. It is reputation based. It's LLM plus index.

The future of search is not going to be indexed as Google has so heavily relied upon. And so this is a sort of clunky way that they're trying to essentially enter LLM into index and to mix them and in the mix isn't necessarily good. But I think the future of search is absolutely going to be, uh, coming from AI agents.

I think we're gonna see more and more search. I'm seeing search GGPT, I'm seeing Bing show up in the top 10 and sites that I'm optimizing. That's never happened.

And that's exciting to me. So there, there's hope. No there isn't.

Plexity has just given me a citation. It doesn't drive any traffic to me. It's a very nice little salute as they drive by and steal my content.

So they're known better than anybody else just because they waved at me and said, thank you. They do chain of thought though. They do show you how they get to the conclusion, which is helpful.

You, you know, we talked about legacy, going back to IBM, we talked about legacy and the legacy of, of Google was always to not be like IBM and to do know evil. And as Alan mentioned earlier, the M word monopoly. I mean, this is no, not surprising what happened with the algorithm changes at the expense of content creators.

I mean, there's a duopoly between Google and Meta in terms of advertising, which is all but killed the fourth estate. So, you know, this is part of their leg, this is part of their legacy and it needs to be put out there. I I'll tell you what I am looking forward to, that I will no longer have to care about.

It's called SEOA lot of time and effort spent on optimizing sites for Google traffic that I'm not, probably not gonna spend nearly as much time being worried about. If you're only thinking about Google, you've already lost searches everywhere. Searches, searches in everything we do on every platform we use.

Spoken like a true SCO Rogue Warrior. Rogue, Warrior Warrior. SEO, battlefield, TSEO, battlefield.

Thank you, Anne. All right, let's take a break. We're gonna come back and, and handle our our third block today.

Uh, some surprising resignations over a Doge. Is it Doge or Dog? Do who the hell knows you are watching?

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Hey folks, we're back in. As Alan alluded to, there are some conscientious objectors have emerged that dos, which I'm kind of surprised about. I thought that they'd all been weeded out.

But, uh, a couple of federal employees with technical expertise basically put out a joint letter saying that they would no longer quote unquote, participate in the dismantling of democracy and its services. Alan, I know we've talked about this subject in the past, but is this gonna be a larger trend? Will other government agent employees kind of stand up and say, you know what, we're not doing this either, and maybe we're on the verge of something that feels like a general strike.

I don't know. Viva La France. Um, so first of all, I thought they checked that you could only have a black heart if you worked at dots.

You, you couldn't have a conscience. I guess not. They must have inherited some legacy folks.

They did. They did. These, these people were, were already there as USDS employees and they had come from Amazon and Google.

So I just wanted, can I just put that out there? Because these people are actually trying to do their job and they just got, they basically felt like they were forced out. Yeah, I mean, look, we see what's going on here, guys, right?

You, you don't use a blunt instrument where you need a scalpel. And so what you do, things like that, the, the results are what the results are gonna be here. And I do think it's only a matter of time.

You know, I was reading an article today, you know, the governorship in Virginia is up for election this year in November, right? Lot of federal folks down in Virginia losing their jobs and feeling this pain. Not that the governor of Virginia has done such a great job.

What's his name? Len Kin or whatever. Uh, I think we are gonna start seeing the manifestations of this chaos, of this dismantling of America, right?

We're gonna start seeing when people start voting. Yeah, I would say that, uh, to give credit on the other side of that governor conversation, the governor of New York said she's excited that there's a bigger pool of talent to hire from. And she's inviting all those doge people and laid off government workers to apply for jobs in the state of New York.

Yeah, these were, uh, engineers, data scientists, product managers, designers, they're talented people. Um, and they got thrown under the, the ages of, of Musk, who, you know, is the worst boss ever. So, uh, more power to them, you know, they also were at reacting to, uh, layoffs of, of their peers.

There were 40 layoffs just before that. And plus these individuals were being questioned about their political loyalties as part of their job, which is just absolutely absurd. But then again, we we're used to this.

Now It's almost esque, isn't it? So in a, in a lot of ways though, this kinda resembles how layoffs often get handled in private companies, right? What typically happens in a lot of organizations, especially the larger ones, is somebody comes up with a number and says, we're gonna cut 5%.

And then, you know, who gets cut is just generally Time out, not time out, time out. Don't, don't even go there. Don't go, this is not a 5% cut.

These are people doing searches looking for things like diversity or inclusion. And if it has that word in it, they cut you out. Whether it's 2%, 5% or 50% has nothing to do with that.

They are, they are. This is a political hit list kind of, uh, campaign here, right? Is, this is not your company-wide, we gotta cut 10%.

They're, they're targeting specific enemy list and specific kinds of programs that they deemed not in, in line with their worldview. Let, let's not, let's not give them the dignity of, of comparing it to something like that. This is a, this is a hack with a machete, right?

This is this. Yep. So This is a political cut that Has no doubt about it.

Claiming is their number. Right? Right.

What take the, the USAID thing, you think there was a percentage they wanted to cut outta that? No, they think that we're done giving food to people and, and, and, you know, and they cover it by telling us it was all based on condoms for Palestine or whatever. Come on.

It is nonsense. It's nonsense. This is a political hatchet job.

And when the people wake up must, I mean he, go ahead. I'm sorry, John. He's using The Yeah, he musk's using the same playbook that he did at Twitter, right?

He gets, gets rid of the people that he thinks are politically infused. Uh, he, but in this case, I, I sometimes think you give him too much credit. I think they're just blindly cutting like wild.

I mean, it's, it is precise in terms of certain people, but I also think they're not, this is just like a wild free for all and slashing, right? And I don't think they're putting a lot of thought, I forgot what agency it is, but they cut 'em one week and had to hire 'em back the next week. 'cause they Figured, oh no, there was nothing important.

It was just the nuclear engineers, no big deal. I Mean, they, they got, they got, they got so drunk with power that they, they've cut so many people that they realize, oh, wait a second, we can't run that operation now. And then you're seeing this in these town hall meetings with just incredible pushback because services are being denied.

But I mean, this is part and parcel of, of their crazy plan. And then they're not complying, you know, the, the courts are saying, no, you have to do these things and they're not doing it. Look, I mean, there's 14 states pushing legislation to stop Elon and what he's doing.

I don't know how successful they will be, but I expect after an attack, there will be a counter attack. This is America. We're not gonna take this lying down.

We're gonna fight for what we believe in. And, and yes, it's gross, and yes, it, it's undignified, but it's also part of the democratic process. And I think democracy is going to see the greatest test it's seen, you know, since its inception.

I, I really do. And, and I'm ready to fight for what I believe in. You know, I'm not gonna just sit and read news and get mad.

I'm gonna do something about it. I'm gonna lobby, I'm gonna, I'm gonna maybe even go to a demonstration. I don't know, I'm kind of scared of public anything.

So I was in New York. I was in New York, I'm gonna do what I Can do. Yeah, no, I was in New York this week and down Broadway and it was freezing out, but down Broadway came a demonstration of hundreds of people chanting, Hey, hey, ho ho, Eric Adams must go, right?

And, and stopped the immigration. And because what happened there was a travesty. I, you know, I've had friends reach out to me and say, Hey, on Textron gangster, we talk about politics or politically charged subjects, and I think we have a duty.

And to your point, we have a duty to, because history shows us, if you sit back quietly and as you say, read the news, you're a collaborator at Nuremberg. The, I was following orders, defense didn't hold water. And I'm not saying these are Nazis, so we're not going there right now yet.

But you can't sit by quietly. If you are a patriot, you have a duty to speak up for what you believe in. John.

Oh, I don't think we have a choice, actually, because the people that we cover are part of this movement. They are part and parcel of aiding and abetting what's going on. And they are, uh, enriching themselves.

And in the process, we don't have a choice. We have to write about This has its Accurately. Yeah.

Tech has its mitts all over this big tech does. Oh my God. Yes.

It's, uh, the, the oligarchs are, are, you know, they're leading the, this, this anti revolution. They're, they're, they're, they're is engorging themselves, Right? So part of the issue though, and there was a good report on this on CBS news two days ago, and they went and they interviewed a bunch of folks in various small towns, and they were all convinced that, you know, the government was inefficient, it was wasteful, and they didn't have a lot of sympathy for these people being cut.

So it wasn't something that they were riled up about. And I have to wonder if part of that is maybe the government agencies just need to do a better job of explaining what they do to people so they understand and they value it. Because right Now, no, you know what, Mike, this is the opposite of NIMBYs.

Until it's in their backyard, they don't give a crap. But when their daughter got fi gets laid off, or their, or their son all of a sudden can't go to school or, or their milk goes bad or their farms go bad in the field, then all of a sudden stuff hits the fan. Now what the heck's going on?

Right? That's, that's the nature of the beast until it hits home, it's always good to point to the next guy. Oh yeah, those people are inefficient.

Is government inefficient? Yeah. Is it almost by design?

Yes. Is it the best of the worst form of government that we've ever had on this planet? Yes.

Right. And so you, you know, if you're okay throwing babies out with bath water, go ahead. Right?

But that's, that's what's going on here. So, and, and, and, you know, we'll, we shall see where the chips fall to Ann's point, right? This is still America, I think.

And I think we still Have democracy. We still have checks and balances. It does not.

And those people in we're, I don't care what map they show you, all of those people in those little towns don't equal all those people in cities and suburbs and so forth, where, where most of 80% of our population lives. And, and as a wise man once said, you know, you just throw stones, make sure that, that you're not living in that glass house because they'll come back the other way. I always, I have to think about what my late father used to always say in these situations, pigs get fat, hogs get slaughtered.

Yeah. Yes. All right.

But hey, more power to those conscientious folks who, who showed they do have a conscience and a heart and, and stood up for what's right. So we need more of that in America. Um, guys, if that's it, I think we're going to call a wrap on this version of The Text Drunk Gang.

I can't wait to see what we talk about tomorrow. It's Friday. Um, and Sagner, John, Mike, thanks for joining me.

I'm Alan Shimel. You've just watched Text Drunk Gang. Stay tuned.

We have a full text drunk TV schedule for you coming right up till then We're out. This is Textron tv. Hey everyone, you know, one of the nice things about doing what I do at Techstrong and Techstrong TV is, you know, I've had the chance to be in this industry, whether it's through Techstrong or some of the companies I've worked with are co-founded for a really long time, and along the way I've had the opportunity and the pleasure of meeting some real gentlemen, some really fine people, whether they're men, women, what have you.

Uh, this next guest is, is one of those people. He's my friend, Roger Barranco. Roger, Roger.

And I know each other probably 10 years or more, um, maybe more thinking back. And, uh, then all that time as I, as I say, he's been one of the fine people you meet in the, in this, in the industry, in the cyber world, currently Vice president, global security operations with Akamai. And he's, he's probably been at Akamai now, was 10, 12 years.

I'll ask him. Let me introduce you to Roger. Hey, Roger, Barranco, how are you man?

It's great to have you on Again, Alan, it's so good to see you again, buddy. You know, I, I, It's been too long. It has been.

I I remember walking through data centers with you and saying, this is the cloud, right? Essentially, uh, when it was, you know, what, 15 plus years ago, even, uh, when that was, uh, in its comparative infancy, right in around It. Yes, it was, it was private cloud and it was just, you know, you were running things in VMware, multitenant, VMware.

That was, that was basically it. That Roger, how long are you at Akamai now? It's gotta be 12 years now.

Yeah. You know, if you include the acquisition of Prolexic from my, my, uh, it's a little over 12 years. That's 'cause I, of course, we knew Prolexic, I remember Akamai buying it.

For those who don't know, Prolexic at the time of their acquisition by Mite was probably the preeminent DDoS protection pool and company in the world. And, and Akamai bought them. And they've been thwarting some of the biggest DDoS attacks ever since.

Um, now of course, Roger, you moved above and beyond that, as I said, global, uh, security operations, vp, you know, Roger. But give people a sense of, I mean, you've had a distinguished career. Give them a, an idea of, of where you've been and now you got here.

Yeah, sure. You know, um, for anybody on here that's looking at security, wow, it's still cutting edge. Uh, how do you differentiate yourself if you're looking for a job and a career.

It's clearly security. It's always changing. It's always exciting.

Uh, it's invigorating to think, Hey, you know, we're, we're protecting the world's most critical infrastructure from nation state actors from, you know, really well, e equipped, uh, cyber criminals, uh, across the board. So, you know, uh, if you're into an environment that's always changing and interesting, uh, this is it. So, Roger, I'm gonna ask you to do a little Akamai kind of setting the, the field a bit.

A lot of people out here think of Akamai and I, I think they fall into camps. Some people say, oh, Akamai, they're a security company. Right?

Probably the minority of people, though I think most people still think of Akamai, and it's part of their original mission, if you will, which was, you know, current commonly CD n Content Delivery Network. They, and of course, and, and, and I don't wanna ppo CDNs, right? Right.

In a world where latency counts, and if we can get you to the edge next to where you're gonna access, if we can get information and, you know, content to the edge where you're gonna access it quicker, that's a huge plus. And that's a very, very important mission. But Akamai is so much more than a CDN security is, but one of of many things that Akamai delivers today.

How would you describe Akamai? So, you're right. The, the CDN is the foundation from which many of our solutions sit on top of it, which makes it very powerful because of the size and capacity of the platform and how close we are to the actual end user that needs those services.

So, mixed in with security, you get great performance. It's really rare to have those two things together in the same package. Right?

So, but you're absolutely right. Um, the fact that the foundation is CDN, the reality is that well over 50% of Akamai's revenue is security. And it's security across a plethora of products.

From API to bot management to DDoS, like you mentioned before, clearly waf, uh, it, it's extremely deep and broad, uh, which is sometimes one of the challenges, right? It's to think of, well, what are all the different situations and challenges that we can help with? But layering it in with the right tool for the job Is, is key to it.

And that, you know, not to be flippant, but as you get older, you learn it's all about having the right tool for the job, right? It really is. It makes life a lot easier all around.

Um, so we, we've laid out sort of the Akamai story. Roger, you guys recently came out with the Defenders Guide, right? Right.

Give a, and, and over the years we've featured Akamai security research and, you know, our friend Martin McKay for many years was writing the, uh, Akamai reports. Martin, of course, has moved on stuff now, but, uh, what's this defender's guide? Is it the latest incarnation of this?

Tell us about it. I, I really like the evolution of the Defender's Guide. So we used to call it the Sodi, the state of the Internet.

It was a wonderful document that contained a lot of metrics in what we're seeing, and we do see the bulk of the world's internet traffic that's clean. Uh, so we're well positioned to talk to these data points from our findings quite literally along the way. But the, um, so DS evolved to the Defender's Guide because we said, Hey, we wanna make this more actionable.

We, it just doesn't, you know, we don't wanna just contribute to the standard, you know, a lot of people or do the fear, uncertainty, doubt type discussions. That's not who we are. We really wanna say, this is what we're seeing, and this is how you can help yourself.

And if you go to the Akamai website, it's, it's very prominent on there. Uh, you can download that guide and it will talk to what we're seeing prominently from a cyber concern perspective, and look quite literally what you can do to protect yourself along the way. Okay.

Um, so give us, I mean, Roger highlights high, you know, we only have 15 minutes. We've probably used seven of them already. Uh, sure.

But, you know, arm people here. What, what, what are the kinds of things they should be really digging into? One thing that I see all the time is that it, and it's exampled by the fact that the number one attack source is very consistently the us.

So the attacker, the bad actors might be in Eastern Europe or somewhere in Asia, or wherever that happens to be. Why is that? Because the Americas are typically behind on patching.

It's just that simple. So just doing the basics, like patching is incredibly important. And I know it's really tempting to have deep discussions about Redtail, which is, you know, a malware that goes in and it takes over an infrastructure to, in a very intelligent way, um, participate in crypto mining, right?

But the reality is, if you have a really good zero trust microsegmentation environment in place, you're gonna be protected. Uh, if in a very significant way. If you have strong API protections in place, aside from WAF protections, very different security protocol, you're gonna be a much better place to pull those items together.

So what have we seen out there? You know, it's pretty stunning to me that d believe it or not, Alan, I don't know if this is gonna surprise you or not. DNS attacks still make up 60% of DDoS Not, not surprised at all.

Yeah. 9999% of the time. Right.

I always leave a little sliver there, because there's always that super smart nation state Actor something right Out there. But, you know, I I, it's funny, the interview I did before you, Roger, was with a company that specializes, they're all former special spec ops people, Uhhuh digital, and they specialize in protecting high net worth individuals, celebrities, et cetera. And we were ta having this discussion.

Some things never change in security. And one of those things is, is that unfortunately people don't get religion until after the calamity happens. Right?

Then all of a sudden they're looking for miracles, or they're looking for solutions and d os protection. Today's a perfect example. You know, until, until you've been a victim, you just think it's fine being the zebra in the herd.

They're never gonna pick on me. And then one day that lion grab grabs you and it's like, oh, I should have done this. Right?

Right. And I don't know, I mean, maybe guides like this telling people sharing real world incidents, I don't know what it'll take for people to say, Hey, we've gotta be proactive about, because you're right. A DNS based DDoS attack today is, you know, that's like getting hit with a, with not even a bow and arrow, maybe a cross bow, right?

It's, it could be lethal to your business, but there's really no reason in today's world that you should be susceptible to that, You know, the solutions are very inexpensive. First of all. It's not like you need some massive infrastructure on that.

There are some great people out there that, you know, can help with that solution. Um, it, it, it, like I said, it's just, there's no excuse for it. And to, Alan, to your point, goes back to patching a little bit, is that the, to be a good internet citizen is critical because those are DNS servers that are being com not compromised, but taken advantage of.

And that can be modified, you can change your settings, but very specifically, uh, you know, on the DDoS front where you're going, we just had a lot of customers from the, uh, Australia New Zealand region, get absolutely hammered because of a political support statement they made, uh, related to the Israeli Palestinian, um, conflict. And there were a lot of, uh, entities that were knocked over and absolutely crushed. And to your point, they, unfortunately, several of them, uh, for lack of a better description, had to learn the hard way.

And they, they'd come to us and say, help us out, because this very fine product that they had in place with very strong AI and ML and, you know, language models and everything, did a good job on 99%, that 1% that it didn't do such a great job on it had no solution for. So if I give advice to anybody, it's gonna be, Hey, you know, challenge your vendors and make sure that they have that human overlay that's absolutely critical for that consultative engagement to handle that 1%. Because in today's world where it's much less brick and mortar, wow, it's 1% is crushing.

It's all Bottom line. It's all it, that's all it takes. You know, you mentioned the magic word there with ai.

I mean, you know, when I look at AI from a security point of view, it truly is a double-edged sword. Absolutely. There's so many things we can do with AI that can make us better security pros that can raise our level of security posture, make us better protected.

But at the same time, you know, it's the old story. The bad guys are not dummies, and they use it too. And they're using it to be more effective to, to have better attacks, you know, the find more attack surface.

Any advice on that, Roger? Yeah. You know, so two things.

You're absolutely right because we see it all the time. The, the rate at which attacks shift when you put a mitigation in place is stunning. Which is why the, so the security operations team has had to evolve and add people like data scientists and threat researchers directly into the security operations team.

'cause you don't have the time to escalate to engineering to see about background investigations anymore. No. When you're protecting a customer, but the AI is making it, uh, very interesting.

But I will tell you, Alan, at the end of the day, it's rare to find a truly novel, traditional attack. It's always some variance of a line injection or a SQL injection or an API attack. If you put the basics in place to protect you, you will be in really good shape.

And very quickly, every customer we have that spends a lot of time with us during peace time, when it does move to war time and they're under attack, it ends up being a really good situation for them. 5 terabit attack and here's all the detail on it, and they didn't even know they were attacked. That's perfect.

That only happens because we're testing with them and working with them during peace time to prepare for that bad day. Agreed. Agreed.

Roger, we're about out of time, but for people who maybe want to grab the guys and, and, you know, get into it, what, what would, what's your best advice? I know it's a long URL, we're not going to give it to you 'cause no one's writing it down, but how, what's the best way to navigate to it? com, it'll be prominent on the homepage, just click on it and it'll gl guide them through.

It's really easy to access it. And a wealth of actionable information. It always is.

It's been one of the best reports on the internet for years and years. Man. Roger, next time you come up here, we'll do this in person in the studio, please.

I'd like that very much. Right. We're, we're 15 minutes from feno?

Yeah. Awesome. All right.

Event. Roger Barranco, VP Global Security Operations, Akamai Technologies here on techron tv. We'll be back with more In just a minute.

Stay tuned. ai video series. I'm your host, Mike Vizard.

Today we're with Arthur O’Connor, who's academic director for data Science at the City University of New York, from the Professionals Studies Organization, as I understand it. And we are gonna be talking about, well, what's going on with all these AI models in particular, deep seek, which seems to have set everybody back, but no one's quite sure what's real and not real here. But Arthur, welcome to the show.

Thank you. Thank you for having me. As I understand it, deep seek, at least the folks who, uh, are behind the model claim that they found a less expensive way to train that model.

And, um, but also folks are saying that some of the guardrails were bypassed and some of the outputs are a little more, um, shaky than others. So what's your assessment of what's really going on here? Well, the, I think the development is a kind of a useful reminder of, uh, to all of us that, that, you know, artificial intelligence, particularly generative artificial intelligence, is not just about the number of parameters the size of the training data set, and the, you know, how many GPUs, uh, are using in a enormous server farm that's consuming all kinds of energy.

It's really about how smart you are and how creative you are in designing, uh, the data. And certainly a lot of the, what is called these distilled models that, uh, R one represents is really about not just the size of the training data set, but the quality and the relevance of the dataset instead of scraping the whole internet. Yes, it's useful in learning the constructs of diction and language and how to form human-like sentences, but it's not particularly, the web is not particularly, uh, good at explaining, uh, complex logic or solving math equations.

Um, uh, and that's where if you start to focus on certain data sets are very high quality to use those design your parameters and your test timing through what's something called interference training, um, in addition to the initial supervised fine training and, uh, reinforcement learning, that that really can improve the quality of the output. So do you think for most organizations, they're gonna wind up focused more on these distilled models that are narrowly aimed at a particular use case, rather than everybody trying to make use of the largest language models in the world because, well, that's just a more expensive approach every time you invoke one of those directly, It's more expensive for the people developing the models. Uh, the, you know, the, the, there are literally hundreds and thousands of open source variants out there, which you can find on me, meite, such as HuggingFace, the real challenge for most organizations just to find out what's available, how they work, and most importantly, how they can be safely and effectively applied in their business process.

And that remains a major challenge because, um, you know, unlike, for example, data science, which is almost universally, uh, can be applied to just about any kind of field. So far, the current generation of, uh, generative AI tools have really been, you know, they performed some neat tricks and have been really good at certain things like visual creation or editing or writing code snippets, but it's been fairly limited to a, you know, mean a dozen or so use cases or business models, what have you. So it's really gonna take, uh, organizations some, uh, getting up to speed on kind what's out there, what did they do, how much they cost, and how do you mitigate the risks of using these tools.

Things too that everybody's obsessing about is the GPUs that we use to train this model are maybe not the most costly GPUs in the world. And we're also starting to see people talk about things other than GPUs for both training and inference. So do we need to be smarter about what classes of processors we're using to train various types of models?

The success and the performance of R one, uh, that's the deep seek, uh, uh, model certainly confirms that, that it's, you know, not just about size, it's also about, you know, quality and creativity, how you use those things and how you architect that solution. How much expertise do we have about those types of, um, more advanced uses? I, I would say, but it seems to me a lot of the data science teams that I talk to, you know, they kind of just run right to the most expensive GPUs and processors they can find.

And they have maybe a particular model and they're not really thinking through the implications of running this thing in a production environment. So who's gonna be smart enough in these organizations to kind of sort all this out? Well, Michael, you've hit upon one of the more interesting structural and cultural implications of the whole evolution.

And that is that in most organizations, uh, are basically structured around the previous digital revolution. And so you have data science expertise sequestered in these, uh, centralized in these IT organizations that kind of have their own mysterious language and processes that are removed from the main line, uh, and the main business units. Um, and this generative AI revolution's really gonna require data science expertise to be mo far more diffused to not only maximize the benefit of using these tools, but also minimize the rather significant risks, uh, of, of the, of such tools.

And you are correct in the Silicon Valley high tech mindset that, you know, bigger and better and faster and more powerful is, you know, necessarily what you're going for. And in many cases, uh, it's not, there's lots of, uh, business people that, um, are, uh, IT people who are overwhelmed by the business unit saying, I want a large language model to do this, to do that. And it turns out that the business case would be far easier, better, and more cheaply solved by, you know, for example, a collaborative fil filtering model for personalization.

But everyone's wrapped up in this gen AI large language model, uh, that those important distinctions in that important knowledge is not sufficiently diffused in the organization. We need to rethink how those IT teams are organized then. 'cause historically we have yes, um, infrastructure and software developers, and now I'm throwing in a bunch of data scientists and there's security people and it takes a village to do anything.

So, um, how should the village be organized? Well, if it, it has to be, uh, sort of centralized and decentralized. So, uh, the expertise and the knowledge of understanding what data science techniques or what generative AI techniques works best for what use cases and at what cost and what, you know, ROI, that needs to be more, that has to be ha decentralized.

Uh, but what needs to be centralized is this policies, procedures, and the architectural standards. Uh, because as, as mentioned before, you know, a lot can go wrong. Uh, you can some well-meaning individual trying to, you know, fine tune a model can wind up, uh, training the model, uh, on proprietary information that now is part of the model and part of the, you know, public, uh, knowledge base.

So there's some important guardrails to be put in. Uh, but as you probably know, most organizations still don't have policies and procedures. It's, it's, as I noted in my book, it's, it's kind of wally world.

And in that regard also, I don't think people really understand the degree to which maybe these models might drift over time and that which seems to be working perfectly fine, suddenly six months later is not. And do we have a process for kind of observing that, monitoring that, and updating and replacing models when necessary? Sure.

Answer is no. Uh, on one hand, I think most users don't realize how powerful these models are. They still use them for, you know, summarization or text generation.

They don't realize that you can assign a role and you can ask it to figure out fairly complicated things with a fairly high degree of accuracy. But because they're not, you know, super users, they don't quite appreciate that. And at the same time, you have this sort of naive a or ignorance on just what you should put in a model and what you really shouldn't.

Or if you're gonna put in proprietary information, how do you use it in, for example, there's a concept called in context learning where you, uh, sequester that private information from the public domain. Well, maybe you have some insights, 'cause we've been talking about this in other interviews, but it seems like people are struggling a little bit with, um, a lot of the business processes that they want to use AI in are essentially deterministic. They need to be done the same way every time.

And gen AI does things differently almost every time. So that's a probabilistic outcome. How do I insert something that is probabilistic into a business process that is deterministic?

We're still trying to figure that out. Uh, all we know right now is that we have organizational structures and performance indicators for employees that are based on things like expertise and credentials in seniority. Whereas this revolution is all about the democratization of expertise so that, you know, the junior, uh, uh, user, uh, employee can potentially have the same amount of expertise subject matter expertise as the senior, uh, person.

And so this is really gonna upend the whole performance hierarchy in organizations at least has the potential to. And so we don't quite have the tools or structure in place to, to handle that. And, uh, I would point out a recent, um, art study issued this month, actually in February, 2025 by, um, Microsoft and Carnegie Mellon.

And it did this study of these three hundreds or so knowledge workers and the results find that it, you know, the ability to, they call it AI whisper, the ability to know how to quite prompt or interrogate these models is actually becoming just as important as actual subject matter expertise. And it also finding that the, the use of these models actually decrease the employee, uh, critical thinking skills. Uh, so because of this phenomenon called cognitive offloading, meaning it's the risk of using GGI as is the calculator has done to our arithmetic skills as the smartphone has done to our memory of the phone numbers of our loved ones or what GPS tracking is doing to our sense of direction.

I'm not entirely sure whether that's a good thing or a bad thing. 'cause I could pop the interview. It's both.

Yeah. Um, so how do I kind of navigate this all with some reasonable expectations? 'cause you see, there seems to be a disconnect that every COOI talk to is like, AI is going to be awesome, change the world, and we're gonna be more profitable than ever.

And then when I get into the middle managers, they're kinda like, well, maybe, yeah, but it's sure not easy to operationalize this thing. Yeah, I I would not wanna be a CEO or, or a CTO, uh, of a large organization right now because, uh, they're, they're overwhelmed. They're, they're being, uh, you know, they're getting calls from the board of directors saying, well, why aren't we doing ai?

And, um, from people whose, you know, enthusiasm, um, and interest in, in the business model is, is certainly commendable, but whose knowledge of data science may not be quite up to snuff. And so they're put in the un envious position of explaining all this stuff. Uh, and we don't have an infrastructure, we don't have an organizational structure, and we don't have a performance employee performance metric, uh, to measure creativity and adaptability.

Uh, and so we're just sort of foundering right now. So what's your best advice to folks then about how to do this? Should I take everybody and put 'em on some sort of corporate retreat and say, this is what's real and not real?

Or are we just gonna stumble our way through this? Both, uh, uh, we, we, we need to certainly most employees seriously need to upskill, uh, and, and get smarter and more knowledgeable about what these models can do. And I think for the average users, they'd be shocked at, at the level of sophistication, um, these models can achieve.

I mean, it's, remember Michael, that this was, you know, this wasn't really expected when the first transform former models, uh, uh, arrived. You know, they called it an emergent capability, meaning that they had no idea it could do this stuff. And so we're still on that path of discovery.

And particularly when you start talking about, uh, these reasoning models, uh, and intelligent autonomous agents, um, it gets really interesting and it's going to take, um, a keen eye and a cool head to figure all this out. Uh, and it is going to have major impacts on the future of work. Um, and, uh, there, as you said, there are a few guidelines right now, but, uh, I would say stay flexible, get smart, and, um, slowly, uh, you know, don't forget the, while it's important to figure out and understand new technologies, don't forget what is permanent and what is universal.

I'm thinking of a quote from Jeff Bezos, uh, you know, who was talked about, people talked about, you know, Amazon and what the new technology was that enabled this business model. They said the important thing is to focus on what doesn't change. And what doesn't change is people want choice.

People want convenience. People want low cost. And it, it's very important to remember those things when you embark on these grand ideas of artificial intelligence.

You use the phrase knowledge worker earlier, and I'm scratching my head sometimes about that term because I wonder if we're evolving into not knowledge workers, but maybe knowledge supervisors, and we're gonna have all these AI agents that are kind of gonna be repositories of knowledge that we're gonna have to figure out how to orchestrate. Is that where we're headed? Well, that's certainly the finding of this, the Carnegie Mellon Microsoft study in, in, uh, this month was that, um, the nature of work is changing.

So you're overseeing, uh, and curating a knowledge process rather than doing the knowledge yourself. And, um, you know, Michael, when you think of it, you know, a lot of what you and I and millions of other people do is we sit at desks and we respond to emails and we synthesize information. Uh, and that's exactly what these models do.

So, um, uh, anyone tell you that, oh, they're just word calculators that they, they can't possibly threaten what I do. Uh, they may be mistaken. Arthur, you mentioned your book.

What's the title and where do I find it again? It's on Amazon. It's called Organi, seeing for the New Productivity Revolution.

Um, uh, it was out, uh, in December of last year. Uh, and it just goes through a lot of these steps and a lot of these tips on how you organize around this new technology and how you make the best of it, and how you get your data in line to optimize, uh, the outputs and minimize the risks. All right, folks here heard it here.

Hey, even in the a i age, you should look before you leap and there's a whole book about it. Absolutely. Arthur, thanks for being on the show.

You're very welcome. Glad to have it. And thank you all for watching the latest episode of the Textron AI series.

You can find this episode and others on our website. Until then, we'll see you next day. Hello, this is Dion Hinchcliffe.

com. And here are my analyst predictions for 2025. I've got three of them.

We're now moving into a new domain called agent-based ai. And this is the next big wave in generative ai. And instead of generating content for you, this AI that takes direct action on your behalf.

So actually getting work done and, uh, using a browser or using applications and actually accomplishing tasks autonomously across multiple applications. And it can be multi-step tasks, it can be for a long period of time. And so this has implications for the digital labor market very significantly, uh, a large, uh, percentage, and by our estimates about 4 trillion globally and labor can be automated in this fashion.

So a, a lot of rote tasks that before you might have had AI advising you or, or telling you how to best complete that task using content. Now the AI can just go actually do it for you. That has major significance in terms of how CIOs are gonna automate in the future.

We've been following all the latest Agentic AI product announcements from the top enterprise vendors. Uh, we have a report coming out in a few weeks that we'll cover them. But, uh, what organizations have to be doing is getting experience now in making, uh, agent AI perform and do it safely with guardrails.

My next prediction is also about ai, something called super intelligence. Then the next step beyond that, uh, we may reach, which is artificial general intelligence. And this is a conversation I, I don't see enough people focusing on 'cause it has major strategic impact to our organizations.

And this is the top vendors like OpenAI or Anthropic who are, have the stated goal of eventually getting to the most advanced type of ai that's the A GII just mentioned. But on the way and that we're seeing signs that we're actually starting to reach it is this concept that's super intelligence, which is AI that is smarter than our best PhDs, uh, smarter than our best geniuses who can do things. They can solve problems that humans cannot have not been able to solve so far.

And this is we're seeing as, uh, the AI models climb to IQ benchmarks, tr you know, run every day on all the new models that are being released. Uh, new versions of models that are being released all the time. We're seeing that, uh, they're closing in on that super intelligence and should be in the lab by the end of the year.

And that's something organizations have to be contending with, uh, preparing for because, uh, these super intelligence can allow your organization to do things your competitors can't. It's very significant. Uh, and this, this, um, milestone will be reached here shortly.

Um, and it'll be in production and available to, to all enterprises sometime next year. So definitely not to prepare for that. And my last prediction has to do with the cloud modernizing existing workloads and moving new workloads out to the public cloud.

And that now is because of the cost of, of these new types of workloads, AI workloads are always on. Uh, we also have a lot more, uh, compliance and regulatory issues, data residency that we have to deal with. And so private cloud is returned to the conversation using the same technologies, but running inside co-location or inside a enterprise data center to really manage costs or optimize performance or do deliver on constraints like data residency, um, that can't be delivered easily any other way.

And so private cloud is not not gonna be the next new destination. Public cloud is still the primary destination, but we see private cloud emerging as a major Alternative for certain types of workloads. Those always on those highly perform at those, uh, things like AI training, it'd have to be run for months, uh, often makes sense just to, to, to cut out the middleman and, and, and there's, there was significant cost savings in, in that regard.

And so Receipt private cloud is really being added to the mix, to the whole spectrum of the cloud computing conversation. Uh, it's part of a continuum, uh, where before we only saw public cloud, so that's a, it is a major shift. 71% of CIOs say they're reconsidering where we're gonna run their workloads this year.

So that shows you how, how big a trend. Uh, so I predict our organizations will be adding a lot more to the mix going forward. And so those are my, my analyst predictions really focused on the CIO for 2025.

com. Hello everyone. Alex Smith here with the Futurum Group, and today we're gonna be sharing with you some of our predictions in going into 2025.

And I'm specifically gonna be talking about cloud marketplaces and the role that we expect them to have in the technology industry. In fact, we think cloud marketplaces will become as important as a route to market for the software industry as traditional distribution has been for the hardware industry. And there's really three main reasons why that's the case.

The first has to do with marketplace fees, which have been coming down over the past decade. You go back a number of years when marketplaces first came on the scene and fees were around 20% north of 20%. 5%, uh, depending on marketplace, depending on scenario.

And in this price point, they're operating in a similar margin stack to what, uh, traditional distributors would offer for their customers. So overall, it is becoming a more cost effective route to market. And vendors can bake this fee into their pricing.

They can offer their sales force comp neutrality, many do, and that again, makes it overall a more cost effective, uh, route to market, uh, compared to what it was in the past. So that's driving some momentum. The second factor has to do with cloud commits.

And by this we mean, uh, long-term commitments that customers make to spend in the hyperscaler environments. And increasingly, this part of this c commit can be used on third party software products that exist in the cloud marketplace. So that is an additional way for customers to burn down these long-term commits.

And this commit amount continues to grow right across the three leading hyperscalers. That number now stands north of $400 billion. So what you see here effectively is a, a ready made economy for software companies to be able to tap into because they are dollars that have already been committed to spend, and in many cases, if they cannot spend it on their compute needs with the hyperscalers, then they're looking to spend that on their software needs through that same same vehicle.

And the way to tap into that is through these marketplaces. And I think what you'll see now is the next evolution of that where when the hyperscalers are going to discuss their commit contracts, they will not only be talking about the the compute and storage needs that they're providing, but they'll also be talking about the software needs that that customer has to, and saying, why don't you break, bake that into your, uh, commit plans going forward. So I think that will be more tailwind for the cloud marketplaces as well going forward.

And then the final factor has to do with the role of channel partners. And increasingly what you're seeing is that the hyperscaler marketplaces are creating programs and policies and other forms of enablement to allow counterparts to be a part of this overall marketplace engine. Right?

We mentioned earlier that as the overall marketplace fees come down, that leaves more room again in the margin stack for the channel partners to, to be involved as well. In fact, you're seeing now north of a third of all marketplace deals involving some kind of channel partner. Some marketplaces leaning much more heavily into that motion than others.

And this also means that the software vendors themselves can include their traditional partners as part of their overall marketplace strategy so that the partners are not competing with what they wanna do on the marketplace front. So we expect channel partners to play an increasingly important role in marketplaces going forward as well. So again, the three drivers fees coming down, the growth of committed spend and the increasing role of channel partners will all drive cloud marketplaces good going forward.

And so a call to action to the vendors out there, uh, that might be watching this is as you were thinking about your, uh, go to market strategy overall, really consider the, the role and the importance that you place, um, on the hyperscaler marketplaces as well as the role that your traditional partners will play as part of that marketplace, uh, strategy. Because really they will go hand in hand, um, to be one of the fastest growing route to markets, um, collectively for the software industry overall. Hi everyone.

I'm Mitch Ashley, VP and practice lead for DevOps and application development with the Futur and Group. These are my predictions for 2025. First 2025 is go time for AI in production.

A lot of AI projects have been stuck in the pilot and prototype phases. Matter of fact, some estimates say that only a third of those have made into production so far. This is the year where AI has to get real and start demonstrating value that impacts how we develop traditional software as well.

We will see vendors introduce capabilities that help us start to blend and coordinate workflows and pipelines across DevOps for both traditional software as well as AI projects, which tend to have some differences in how the workflows are performed. So look for those features maybe later in 2025. Prediction number two, built in AI rather than bolt on AI across the software development lifecycle.

Much of the AI we use, particularly generative AI today, are things that are bolt on. They're chatbots, they're natural language interface to it. They may be an IDE plugin that helps us, uh, generate code or get access to a code base.

Increasingly we'll see more AI that is just a part of the products and the tools and the workflows, the tool chains that we use for creating software rather than an adjunct or separate thing. I think we'll see a lot more productivity as more AI is really integrated into how we work rather than a feature of a product or a separate product. Kubernetes dominance.

That's the next prediction. And we tend to think of Kubernetes as the cloud native container orchestration software. Of course, that's what it is.

We use it with microservices, containerized AppSec, all kinds of workloads. But that's the point is that Kubernetes has really expanded its use across virtually any kind of product and service that we may use. We may be provided by a third party a service in the cloud.

Uh, it could be even on hardware, you know, integrated hardware and software to use for storage solutions or an edge solutions. Kubernetes truly is ED everywhere and has become the workload system for any kind of application or service. With that comes though, we need to up our skills in Kubernetes operational capabilities.

It is complex, it's getting simpler. We're offloading more of that to third parties, but we'll also see AI help us here with operationalizing Kubernetes, reducing some of the complexity and improving our overall ability to run it effectively. Well, thank you for joining me for these predictions around DevOps and application development.

I hope you'll check out the full ebook of all the predictions by the Futurum group analysts. We cover a number of areas, whether it be enterprise applications, ai, of course, infrastructure, security, you name it. com.

Thank you.