Techstrong TV June 23, 2025

Hey everyone. Remember that? $32 billion Google acquisition.

Wiz, not so fast. You're watching Techron Gang. Hey everyone.

Happy Monday. Monday again. Yeah, can it just stay Sunday forever, but happy Monday everyone.

Welcome to Text John Gang. It's Alan Shimel here. Um, we've got some interesting stuff to go on.

As I teased in the opening, I, who would've thought that this DOJ antitrust unit would actually look into a deal, but maybe they're looking into the Google deal. Uh, reverse cloud coming outta Microsoft platform. This is gonna be a big platform engineering week.

We'll be a platform con this week, though. Some of us will be at the open source summit. Denver, we've got a lot to go over and we got a great gang here to go over it with you.

Let me introduce you to our gang real quickly. Some, some of them are regulars, some of always regulars, but fairly new. Speaking of regulars, let's go to our woman in New Mexico.

Not in Albuquerque, but in New Mexico. Uh, although she'll be in Denver this week for the open source summit. She's the play hub, CEO and open source ambassador extraordinaire.

Tracy Reagan. Hey Chase. How are you?

Hey, Alan. Yeah, I am, uh, hanging out at Open Source Summit and you know, we've got talks later today, so come on by. And tomorrow we're doing a, we're doing a, a, a focus group on CID cybersecurity in the main ballroom at the Bluebird Ballroom.

Grab a lunch and come in and tell us what you think. Wow, cool stuff. I'd love to hear maybe when you get back, chase and get back on the show.

We can get a report on that though. We'll be there live. Mike can talk to you about it after, and we can, we will have a full blown strong TV coverage on it.

Very cool. Alright. From the mountains of New Mexico to the mountains of Colorado, it's all mountains to me.

He's Futurum, uh, advisor on, on, I forget the exact wording now. Mitch. New wording is system engineering lifecycle.

Love it. System. Engineering lifecycle.

SELC, Mitch Ashley. Hey Mitch. Show.

How are you man? Good to be here. I'm very connected to Tracy 'cause those can mountains and just connected right up the right up the continent.

So, here's the question. Are you throwing off a mound yet or are you still not throwing? No, no.

I'm, I'm, I'm still, you know, sinking into the ice tank every day to, and warming it up again. See, seeing how the shoulder's feeling. We'll see, you know, the shoulder will tell me when it's ready.

Alright. All right. Those damn Yankees.

Um, next up, let me introduce you to Dr. Stacy Thayer, one of our newest gang members. Hey Stacy, how are you?

Hi, Alan. I'm good. How are you?

Good. Hey, Stacy. You know what?

I don't know if we've ever told people what you're up to these days Doing a couple of different things. Uh, so my work as a cyber psychologist, I'm acting director of the cyber psychology program at Norfolk State University, where I also teach forensic cyber psychology. And then I'm also working at Cobalt, uh, helping them out in their marketing team and working there in their senior event leads position.

Very cool. I love it. Cyber psychology, man.

Speaking of cyber, he's, he's all dressed and ready to rock today. Text and gang member future and, uh, tech, not Future Tech Field Day delegate. Our friend Jack Poller.

Hey, Jack. Hey, it's, uh, great to be on the show and, uh, great to meet Stacy. Uh, that's, uh, a, a, a very, uh, intriguing and interesting title.

I'd love to learn more. I always said we need some psychological Help. Don't you agree, Jack?

Oh, absolutely. Yeah. Um, all right, jumping from Jack.

He's got a big smile on his face 'cause the Yankees won a game. Finally, he's the chief content officer, Mike Ard. Hey Mike, how are you?

Yeah, and apparently I'm in Denver playing in a elaborate game of where's Tracy? Yeah. Okay.

Very cool. Very cool guys. Alright, so it seems the DOJ might be looking into this, uh, Google Wiz acquisition.

I thought we're in a laissez-faire form of government. Let's make it great. What's going on, Mike?

Well, apparently that only applies to certain companies. It may be, but it seems like there is some selective decision making going on here. Um, the DOJ is reportedly investigating the proposed acquisition of Wiz by Google.

But Jack, I gotta ask you, you know, what's your take on this whole thing? And is this a good use of taxpayer dollars? Uh, that's a loaded question.

I'll start with. Um, it's not surprising that they're looking into this for two reasons. One is, uh, the current administration has, uh, a penant for being very wary of what big Tech is doing.

They're, you know, very concerned about, you know, past censorship and other reasons. So that's one. And the other is, um, the new Assistant Attorney general, uh, Gail Slater, who covers antitrust, is a long-term antitrust person at the DOJ.

So this is, and and she's basically said that she's planning on continuing the path of the last four years of what the Biden administration was doing, so that they wanna investigate big m and a deals. And 32 billion is a big m and a deal, um, is not surprising. 2 billion breakup fee if this doesn't go through.

So they always thought that there's a possibility it doesn't go through. 2 billion is not chicken fees. I would imagine Google was hoping not to have to pay that money.

Uh, absolutely. And I think, um, you know, traditionally, uh, and I'm not sure how it's gonna work here, but traditionally, when the DOJ has looked into antitrust stuff, they've focused on sort of how much of the market does any one company control? You know, the, the classic case that people study in business school is the m and a activities among, um, office Depot, office Max and, uh, staples, where there were three companies that basically controlled the entire office supply market here.

When you look at, um, cloud security, it's not three companies. It's eight or nine majors and another 20 minor companies that are all involved in this. Uh, you have Palo Alto, Fortinet, uh, Orca, Microsoft, uh, you know, there's a lot of companies, uh, that play in this space.

And cloud security covers a very big broad definition, whether it's cena, cloud native Application protection or CSPM cloud server, uh, cloud, uh, security Posture management, or CWP cloud work, uh, work, uh, and cloud platform protection. There's, there's all sorts of variations of bundles of different services that these companies provide. So if Google takes it over, is that gonna corner the market?

The anti-competitive? I really don't think so. No, no.

Mitch, let me ask you, is this a distinct and separate market, this thing called cloud native application protection platform? Or can you make a legitimate argument that says that it's just an, an extension of cloud security and Google's a cloud service provider, so therefore they need this? And it's not a separate market, It's kind of the intersection of application security and Kubernetes container security is really what you're talking about, and it's the security world's, I dunno, entrance or, or getting into trying to get into that application layer without getting too deep into the app, but really still the infrastructure that apps run on.

So, you know, whe whether that's its own product category, you could argue whether that's that strong enough of an area, or is it just really kind of fall into AppSec or cloud security? A little bit of both. So I think it's a, you know, potato, potato thing.

Well, you know, speaking to people on Wall Street, they don't seem too concerned. When they were asked, they just said, taco, Well, you know, this has been a works in a while, right? We saw this, uh, maybe a year ago, 20, early 20, 24.

There was a effort to combine these two companies. Whiz declined. I think it was around 20 billion at the time.

So, well, you know, they made some money off of it right? Waiting and, and I can't, um, imagine that Google, uh, with all of their resources hasn't done some pretty strong research and preparation for, uh, this objection from the DOJ. So I suspect it's probably gonna go through, it just may take a little time and some money thrown at some lawyers and, uh, Or, or thrown or the money thrown someplace else.

Maybe some cryptocurrency, a certain cryptocurrency, or maybe some gold phones. Man, that's the idea. You know What the, maybe they'll buy some gold phones.

That'll be all. It'll be all okay. And that, you know, that's not, not, I don't think that that's too out of the question.

Um, but to your point, to your question, Alan, I really believe that these kinds of tools are essential for these cloud uh, providers. Absolutely. And, and you know, the other thing is Google is not the dominant cloud provider, right?

They're 9,800 pound gorilla. This isn't about search. And, and so, you know, they're, they're not the 800 pound gorilla in cloud and cloud security is almost a, a offshoot of, of the bigger cloud market or a subset of the bigger cloud market.

So I, I don't, honestly, I, you know, I I think, Jack, you might be onto something with the lady or person who's running the, uh, the, the, the antitrust over at DOJ, but as soon as someone in that administration says that she's carrying on the policies of the Biden administration, they'll probably take a 180 anyway. Yeah. But I, and the, the other, the other part of it is, you know, that Google's doesn't have a strong track record of after acquisitions continuing to support the other cloud Cs, the other clouds, right?

So Microsoft has done a very good job in trying to build tools that support Microsoft and Amazon and, uh, Google. Google not so much. So it's not clear if Google acquires Wizz will whiz still be able to maintain that level of independence and be able to provide the same level of security on a Nongo environment.

But, but there are other, there are other Synaps out there. There are, there are, but, but it also, it also means from an antitrust perspective, is if, does that mean that Google is actually going to be able to continue to compete against Microsoft or Palo Alto or Orca in providing, you know, A reverse antitrust, right? By doing this has, does the CNET market open up with more opportunity for others?

You know, especially when you have AWS you know, exponentially bigger than Google that CNET and, and take the wiz out of that AWS marketplace, you know, what does that open up? And that seems more competitive to me. I think this is just as much about competing against Cisco as it is the other cloud providers from a security market perspective, right?

Because Wiz brought that independent now to Jack's point, whether, whether Google can, can it can survive that through the, the Borg acquisition into Google. But, um, you know, that it's, it's more than just the cloud providers. Yes, obviously it's is is those folks.

But I think Cisco ought to, ought to be concerned. Maybe they aren't concerned 'cause they don't think it'll survive the, the multi-vendor, multi environment. But we'll see.

Stacy, what does a deal like this do to the mindset of the buyers out there? Do they just kind of freeze everything and wait to see how this soap opera plays out? Or do they ignore it until something dramatic happens?

I think they, a lot of them wait and see what does this mean? And I think, you know, there are companies that get acquired and to, to Jack's point, nothing happens with them. Nothing changes.

You don't really even know. And then there's acquisitions that happen where Wiz then becomes more Google than it was Wiz. And then anybody who signed on and said, well wait, I signed on with Wiz, this is not the wiz that I signed on with, may move on.

So I think it depends, does this just fall into Google's checklist? Did they check a box, okay, we have this technology, we did this, this acquisition, and they let them continue to make their own success and do things their way, or does it become the Google way of things? And are they getting what they signed up for within this change?

I think this is an essential purchase for a Google. I know we've talked, um, on this, on our gang shows in the past about where does Google go when everybody's using philanthropic and o open chat GPT, uh, in place of Google searches. I am surprised by how little I use Google searching anymore.

I mean, I, I, I never go to Google to look for anything. I am either talking to Anthropic or my chat PT window and I never ask Google for anything. Uh, so maybe this is a pretty essential part of Google's strategy to shift, uh, and build their, their, their cloud platform.

Uh, and in terms of revenue, I can't imagine them restricting, you know, companies buy revenue, right? So they're buying, uh, W's revenue. They're only gonna build on that revenue because they need that revenue to replace in the future.

What we used to rely on for typing in our single question in the Google window, because I think fewer and fewer people are doing it Well, it's interesting that you mentioned they're buying revenue because it's an all cash deal. So they're giving up a whole lot of cash to buy future revenue as, as opposed to keeping up a whole lot of stock. Well, it's one, one can make the argument that Google stocks more valuable than present day cash, right?

It also lets the, um, the current owners walk away very quickly instead of waiting to, yeah, it, it does. Well, they're not locked up like that though. They could still be locked up with incentives, but, but it also points to that, quite frankly, during the COVID years and immediately prior to that, these big tech companies built up, Fort Knox is full of dry powder, dry cash, right?

Apple, Google, Microsoft Meta. They're all sitting on huge reserves of cash, huge reserves of cash with really kind of nowhere to go with it at some level, right? Um, so I, you know, though Google is, you know, 32 billion is a lot of money in anyone's book.

They've got it. And then more Referencing a show from last week, maybe there'll be Google stable coins and you get those instead of money for Could be, could be that might, that might get the DOJ to go for it. I mean, I don't, I don't see the argument.

I don't, I, when I look at it, like you said, Alan, they're not the primary player in the, the space AWS is, these are tools that customers need. So it's only making the customer's experience better. And I don't believe that they're gonna cut off their, um, customers who are not in the Google environment and they're in the other cloud environments, whatever that might be.

Uh, because I don't think they wanna lose the revenue. They need the revenue. Yeah.

I, I think it'll go through. Alright, let's take a break. Let's come back and do a little reverse cloud.

You're watching text Junk. Okay. Hey folks, we're back and shifting a, a cloud gear slightly, but we're talking about Microsoft is now making available 365 local, it's basically the cloud version of their platform is now available on premise.

This sounds like the world has been turned upside down, and it is because it is. We just spent years moving everything to the cloud, but now our friends in Europe are concerned about control and we're building out sovereignty clouds. And of course now Microsoft is responding to that need.

Um, it's interesting, I guess, you know, at some point Microsoft probably could have done this at any point, but they're doing it now because Europeans are mandating it. But Stacy, is our mindset changing about what the definition of security is here from our friends in Europe, because, well, these sovereign clouds seem to be driving all kinds of decisions that I probably would've said not likely to happen a year ago. Yeah, well, I, I think Europeans and they just have a very different way of thinking about their data than we have historically in, in the us and that's creating a lot of, of tension.

So you bet things like the GDPR over there, I mean, the Europeans have really set the, the course for data protection, whereas in the US we're much more fragmented and we give companies access to the data. So they're saying, we don't want our data in us hands, we wanna bring it on-prem, we wanna bring it into, it makes sure that all our data stays in Europe. Then that does become a different way of thinking because it's essentially kind of drawing a little bit of a line in the sand.

I mean, is it saying we don't trust you, we don't, we don't, we wanna keep our data here. This is why. And Microsoft is now raising to, to meet that request and bringing out our standards.

So we say, okay, if we're not gonna hold the same standards as our European friends, then we have to essentially bring those standards to them and take them out of the us. And it's a different way of thinking than, than we've thought in the us. And without it, we can't su we can't support Cray, if you're in the u eu, you have to have, uh, this, this technology because they have to support the Cyber Resiliency Act, and we're not moving That direction.

I was at InfoSec Europe, you know, just a couple weeks ago and everyone was asking, okay, so you're, you know, you, you're, you're GDPR certified, right? You, you're, you're able to play in our space. I mean, we kept getting that question over and over and over again.

So it's clearly at the forefront of their minds. Mitch, we were just at AWS last week and I was talking to them about this particular issue, and they were pointing out that, you know, their preferred answer is a virtual private cloud. But even that, they said, you know, the issue is these SaaS vendors, and it won't just be Microsoft, they're all gonna wind up doing the same thing.

And essentially it's a managed hosting service now that they provide, and it doesn't scale out. So with changing the way that they allocate compute resources and networking and just about everything that went with it. So I think this is a more fundamental IT change than we think.

It's just not simply a matter of slapping a bunch of software and putting it in a different data center. Well, it's a common combination of things. To your point, Mike, um, there's a bit of nationalism in this too.

I remember being at when, and Alan was, was there also, and you, you were hearing the discussions about what software we gonna, what stack are we gonna build on in Europe that doesn't rely on North American US vendors. Can we be vendor independent from the US or less dependent upon them? That's why, I guess Microsoft's taking a page out of the, out of the, the finger in the d**e from the Dutch, because Denmark, Germany, um, I think it's Switzerland, if I remember right, have announced that they're tossing out windows and and office in, in favor of Linux and Libra office.

So they need to stem the tide of people saying, we can't be dependent upon North American companies. If it's running in your data center, it's your data, it's protected. And Microsoft added some additional data protection and make sure that data doesn't leak out.

Okay. I mean, as about as much as Microsoft can do to try to keep them as customers. So I, I think there's a bit of survival to this too.

It's not, they're, they aren't rushing for the doors quite yet, but they seem to be, there's a bit, a few folks are walking outta the movie, unhappy with how it's gone so far. I think there's an economic component to it too. You know, cloud data centers are business that's, um, really driven by economies of scale, right?

And the bigger you are, the, the, the better economics you get out of it. If it truly is driven on the EU side by nationalism, then the scale, the economies of scale don't accrue. If you have to have a data center in every country in the eu and that just can't scale.

And not only can it scale, you also face the much stricter environmental regulations and the lack of energy that you have there. And so it's a transfer of the economics back to the buyer, um, uh, rather than to the seller, right? So now the corporations, um, have to own the CapEx again, rather than Microsoft owning it and taking advantage of the huge economies of scale.

So the, the sovereign IT sovereign IP sovereign cloud issue is not strictly a European issue. As a matter of fact, I'd say the US is pushing for their own sovereign data and sovereign it, right? And we wanna, we wanna own the whole process from manufacturing all the way through.

But you're seeing it in Asia, you're seeing it, it's the balkanization of the internet. Now, what happens though for, with this sovereign it, sovereign cloud is, is the local market big enough to warrant an investment to, in essence recreate a whole cloud, a whole public cloud infrastructure for a given jurisdiction for a given sovereignty, right? Much like GovCloud was done for the federal space, right?

You recreated an entire kind of public cloud infrastructure. Now, if the EU can speak as one market with 30, what is there, 32 countries or something in the EU now, um, that, well, that's certainly a big enough market to invest into creating an EU wide true public cloud in every sense of the word, you know, a hyperscaler kind of infrastructure that would be sovereign to the eu. If the EU is gonna say each of the 32 individual nations need to have their own sovereign cloud or their own sovereign IT data, well then, then providers are gonna have to pick and choose certainly Germany, France, maybe Italy and, and Spain are big, but am I putting one in Albania?

Am I doing Lichtenstein, Switzerland? Well, Switzerland's pretty big Denmark. Yeah.

You know, but now you're starting to get into the, the nitty gritty of 32 different markets. I, if it stays as one you, it, it's certainly a big enough market to justify a a hyperscaler. I think the term sovereign too is a little bit misleading to be honest, because no matter what you do, you're still dependent upon Microsoft, right?

My, you know, it's, uh, they still have vendor lockin. Uh, it's still, you know, uh, it's ex it's exposed to US laws because it's, you know, Microsoft, so, well, it might be a local or private. It's hard to say.

Uh, the, the term sovereign, I think is a little bit marketing. Well, but, but the, the, the wording there, right, is local control. I, I think what you're seeing in a lot of these sovereign deals, if you will, is that the vendor, in this case, Microsoft, but it could be AWS, it could be Google, it could be others are saying that they are going to comply with local government regulations.

So if the government, you know, most often this comes, can you turn over this data to the government? We give the government access, or better yet, will you give the US government access to data? Well, That's, yeah, it doesn't, it doesn't solve the skepticism around, uh, and, and being so attached and dependent upon a US institution.

But I think, I think it's two different things, though. I think one is a concern about being dependent on US organizations for the technology. And the other concern is the data and data sovereignty and who can actually get access to that data.

And I think that there's a little bit of, um, rose color glasses there. The fear, particularly with the Patriot Act, was that the US would come in and suck up EU citizen data, right? And therefore, they want that data to be resident in the eu, not in the us.

Um, but that of course leaves that data subject to EU governments sucking up that data. And there's actually a lot less protection there than there is on the US side. Um, but regardless, I think that there, there are two separate concerns.

One is the data sovereignty, and one is, are we independent of US vendors? Well, there's also the, uh, the problem of Hotel California and the cloud. Your data can check in, but you can never leave.

That's a problem too. It's hard to get out. I would ask Alan the following question, how far can this go?

Will the state of New York wake up one morning and say, you know what? We don't want data to be subject to the laws of Florida or Texas or any other. Blame blame, but, but seriously though, so there, you know, we do, we do have interstate commerce, clause of the Constitution, and we do have, uh, a web of laws when it, you know, it comes to controlling, that's a federal, right?

If it's, when it comes to commerce as between these sovereign states, uh, it's a federal that the federal government is preempted that for themselves. So I would say New York or any state who made that sort of claim, even this lame duck Supreme Court that we have now would probably still have to uphold the constitution and the interstate commerce clause. Well, it's, it's, it's not as clear cut as that, unfortunately, right now you have a pat, we have a patchwork of privacy regulations.

You have California and Virginia that have con overlapping and sometimes conflicting regulations. And I don't think any corporation is yet brought suit to the Supreme Court to say that it, but it's, the potential of conflict is there with multiple states getting into their own version of the GDPR and the different requirements. And there are reporting requirements on data losses that are different between each.

So it becomes complicated very quickly, which is what the Commerce Clause was meant to perfect, but we're not there yet. Frankly, this is why, you know, the preferred method of regulation is a national, whether we're talking about cybersecurity and privacy, or we're talking about AI usage or what have you, obviously preferred would be a federal, nationwide type of, of regulation. But, you know, we don't have the political will at the federal level to get things done a lot.

And so it falls to states, We have a Supreme Court that also seems to wanna defer to the states whenever it can. So, you know, states' rights may prevail. I I still think there's an argument to be made for the Congress clause, my 2 cents for what it's worth.

All right, let's take a break. We'll come back and we've got our C block. This sounds like something out of like the movie BIG with Tom Hanks platform, fortune Teller.

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com talking about the cost of it and essentially makes an argument that says it's getting so expensive these days is that you cannot afford to not embrace platform engineering. 'cause otherwise the cost will just be through the roof. And so, Tracy, we've been talking about platform engineering on the show before and where it fits in DevOps, but is there something bigger happening here?

And is it gonna be driven not just by better developer experiences, but flat out hardcore costs? Okay, well, I, when I saw this article, I kind of laughed because when I've ever heard these two, the term fortune telling associated to platform engineering, it's sort of a joke to be quite honest. It's sort of something that is, you know, we talk about, you know, how can you build the perfect golden path and, uh, and watch developers create their own pipelines anywhere.

And you, you, you know, ahead of time what they need. Um, but, you know, maybe there is something more to it than just a, a, a frame of reference to what potentially could happen or what we're trying to do. Uh, I, again, i i, I kind of giggled when I, when I read it, because it, I always thought it as being a kind of a torical reference to what platform engineering is attempting.

But, you know, the farther we get down the world of ai, I believe that we can do better, um, you know, predictive work so that we don't have to be quite so reactive and in that space. I don't think it's a joke. I think it's a serious matter and, and a matter that we've been working on for quite some time.

I mean, these environments are really, really complex. Um, when you think about trying to manage a Kubernetes environment, even tracking the cost is difficult. Uh, we have terraform, we have DevOps tools, tooling that we need to be a adding, we need to have cybersecurity issues that we're addressing.

So yeah, it would be kind of nice to have some fortune, fortune telling around the platform engineering space. But, um, you know, what we build in the next two years and build an, uh, with ai, uh, we'll, we'll tell the story. Well, Tracy, I took that, I, i, I think it was somewhat tongue in cheek, but I took it really as the higher level message is really, um, a very old one, which is, uh, don't for focus on the short-term tactics, but focus on long-term strategy, right?

And, you know, we can, we can spend all our day, every day being reactive and fighting the fires that are right in front of us. And if we do that, we never plan for the future. And we never figure out what our platform really needs to look like to support something that's six months out or a year out, let alone 2, 3, 5 or 10 years out, right?

And I think it was, to me it was more of a parable of how do you get people to start thinking about, we've been doing platforms and you know, the cloud and platform engineering for 20 plus years now we need to start at the big level, start thinking about and planning about these things as long-term projects. Not let's just implement the next thing. Shiny object that comes in front of us.

Mitch, the Boy Scouts have a motto says, be prepared. This is essentially the IT equivalent. So is this achievable and how come we're always so reactive?

Well, the article certainly was aspirational. And I mean that in a positive way, a positive way. I like the analogy of comparing of fortune tellers versus fortune spenders and you know, we've all been in situations where we're thrown into a mess and we've gotta clean it up.

That's one scenario. Prob probably a very likely scenario for a lot of platform engineering. And I think the message here is be prepared as in raise Periscope.

Don't just, you know, pipe underwater and try to solve all the technical challenges, but figure out where you're going and why you want to go there. And more importantly, towards the end of the article, we talked about using cost management as a strategic advantage. In other words, kind of going back to the nineties, it's about the budget stupid or about the economy stupid.

You talk, talk the money story. What are the, what's the value that's the platform engineering is bringing to the business? Yes, I like that it's focused on developers and their cus who the customers are of platform engineering, but ultimately the customer's, the business, right?

What's the benefit you're bringing? Um, and I think there's a great story to tell. I I thing I like to say about platform engineering is platform engineering can be the force multiplier to DevOps.

It's the thing that can really leverage it, accelerate it, spread it across multiple projects without the chaos that can happen when it's just done organically. So I think that strategic look is, is well advised, Stacy, are we psychologically capable of achieving this goal? 'cause it's really about the humans at the end of the day.

It is. And we can strive to, I mean this don't be reactive. Try to be proactive is, you know, one of the swan songs of the security industry as well.

So I hear it so much and you know, I think as humans we can try, strive to be as proactive as possible and to try and forecast, but we're still gonna be reactionary. We're still gonna see what comes right in front of us. And sometimes that just eclipses everything we wanna do.

It's kinda like when you wake up in the morning, you think, here's what I'm gonna get done all day. And then you get done maybe half of it, right? Best laid plants, mice, and men and maybe platform engineers.

And so I think, you know, we can strive to, and this is the article is a good reminder to think in that mindset. It is a way of thinking. And I think we can all use that mindset of remember what we can strive to do, not just what's in front of us because then we can solve long term problems and the bigger picture as well.

But we have to carve time and make the time to in that thought process. So there's a, there's a culture that we've established, uh, in this area in DevOps and in platform engineering that I have been b******g about for a very long time. And one of those that part of that culture, uh, comes from open source, which I, you know, everybody knows I'm a huge fan of open source, but in this particular area, we have put so much time and effort in building everything we do through scripted processes.

Everything we do is scripted in this area. This is holding us back. It's, uh, keeping us from being fortune tellers, but we're not spending either.

Because what occurs is these platform engineers, they go directly to open source tools and start writing these things. And, you know, they build out their own terraform. They have all their get ups, all of this is scripted.

There are, there's not a lot of real serious tooling that's being implemented because why not? Because they would have to go ask for budget and they don't have budget authority. So we are in a, we're in a loop.

Uh, and in order to get out of that loop, we have to change the culture. And I believe that C-level execs have to understand that if they want a so more solid environment, uh, tooling, proper tooling, moving away from scripting is going to be important. And the other thing that we're gonna see are MCP servers that are gonna start managing these workloads.

It's not, that is not far away. Something you ra makes me think of, uh, Clayton Christensen's, the Innovator's dilemma, right? And one of the challenges it sounds like we're facing is we're using the wrong metrics.

And I think, you know, what Mitch highlighted from the article is changing the metrics from looking at cost as a cost center to looking at your costs as saying, understanding what's the business value, right? And, and I think your argument is right now is that the scripting is not providing business value. It's providing just pure cost benefit and a very small cost benefit and not true business value.

And if we change how we look at these things and how we measure them, then we can start operating differently And just don't know if it's achievable. And I'll tell the story many years ago, and I was asking a fellow, he came to me and he said, you know, what do you know about X, Y, and Z? And I said, you know, well, this is what we know.

And then I asked him, I said, you know, how come you're asking me? 'cause it's not like we don't publish reams and reams of content out there, and it's all available for you, and this is why we created all this stuff. And he looked at me and he smiled and he said, son, it's really hard to think about fire prevention when you're holding onto a hose from dear life.

Perfect. And this is true. That's Exactly, yes.

It's, And and I'll tell you something along those same lines, Mike, at the end of the day, it comes down to money, right? And a lesson I've learned in my life in business is people don't like to pay for nice to haves. They pay for must-haves.

And when you're talking about things in the abstract in the future, that, and, and this is by the way, Stacy, you know, this is a problem in security. Nothing happened. Why do I gotta pay more money?

You know, you want another trinket? We, you know, it's only when you get breached that you get religion, right? And it, it's the same thing here.

Don't talk to me about what this may be able to save if such and such and such happens. And we do that, that, and this, those are nice to haves, right? I'm, I'm holding onto the fire hose for dear frigging life, to your point, Mike.

And that's, that's where my priorities are. And in, and in tough budget cycles, those are the things that get funded and the nice to haves don't. It's just, I think just the way of the world.

And if you can have a developer write something that solves the problem for right now, script it out, then it gets done that way. And that's just the, we'll cont we, I, I've watched this now for 30 years and it baffles me every time we have a discussion, every time we think about evolving to the next level and being more, you know, proactive than reactive. I, I just think it's really difficult to do it on the, on the set of tools and scripts that we currently have that we're trying to manage.

It creates a reactive environment. Yeah. But that, that, that developer is on a fixed sunk cost budget, right?

That's already been allocated for, that's not new budget. And that's why people do it, right? And they don't have budget to buy tools themselves.

So they do what they have to do. And that's why the open source community has supported this and it's why it's flourished How much of this also though, Tracy is simply, you know, a lot of developers like to write scripts because they're like, Hey, you know, it's guaranteed lifetime employment. I'm the only one who knows how it works.

And therefore, I mean, I'm not gonna worry about the cost, Mike. It is built into our way we think and our culture. And I promise you, if somebody's written a lot of those scripts, everybody prays and prays that he doesn't go outside and get it by a boss.

Tracy, this might be waving the red flag in front of you, but isn't writing scripts sort of what the whole idea, what developers can do it all themselves and DevOps, we kinda set us ourselves up to go down this path even more so with DevOps. I mean, we've actually, I think somewhat abandoned the developers has to do every job. But we kind of created this mess even more so for ourselves.

True. Agree, or you, you tell me I'm Blank. I no, I'm totally true.

And, and one of the reasons is because we see this process in a very fragmented way. We see it based on each application team, let's just call it an application team. So each application team is, is given the task of addressing these problems.

We don't step it up and try to see it as an entire organizational structure and how do we solve it in at a higher level because they don't wanna spend the money on that. Each, or each team can can address it. So each team then goes and looks for the tooling that they wanna use for their particular language, for their particular environment.

And it's been working. But as we got more com complex, uh, infrastructure Kubernetes was, is very, very complex. We started building more and more of these scripts and now we're seeing, uh, the opportunity maybe to do something more automated, do something, um, with ai, an agentic ai, something that can make decisions.

Where's the data coming from? How do we see that history? How do we see what's happening?

We're gonna have to figure out how to really look at the scripts and try to repeat what they're doing. But they're all fragmented. So it's, it, it is a, it's a challenge.

And I'm sure someday we'll, we'll sort it out, but the way we'll sort it out, we'll just throw away the baby with the bath water and start all over again. Yeah, that's pretty much the way of it. All right.

Hey guys, I think we gotta pull the plug on this one. We're about outta time. We have as usual our full tech strong tv, uh, schedule immediately following today's gang show.

As I said at the top of the show, we're at, we're on dueling locations this week, Mike and Tracy and one of our tech strong TV film crews be in Denver for the open source summit. Um, Mitch and I will be in New York City for Platform Con. I think that's the 26th.

Uh, it's a virtual event by the way. com and, and catch all. I don't know how many hundreds of different sessions there are there.

Um, I'm doing one with our friends from check marks. Mitch, you are doing one, right? Mm-hmm.

Uh, we'll Also, I'm doing too actually panel and doing my own session, so, Very cool. And we'll also be, uh, we'll be broadcasting live on the 26th too, from Text Drunk TV there. So stay tuned for that busy week.

But for now, on behalf of Jack and Stacy and Chay and Mitch and Mike, have a great day everyone. We're out. Hey everyone, welcome back here to Tech Drunk tv.

I've got a new company and a first time guest to introduce you to. I I have a new company to us here on Tech Trunk. Um, let me introduce you to Dominic.

Dominic is the CEO and co-founder of a company called Story Block, and he's gonna tell us all about that in a second. Dominic, welcome to Tech Drunk tv. It's great to have you on.

Thank you so much for having me, Alan. It's, it's a pleasure. My pleasure.

Um, so Dominic, before we talk about Story Block, let's talk about Dominic. You're the CEO co-founder, you know, tell us your story. Yeah, happy to do so.

I mean, I'm a first time founder and the first time CEOI mean, I'm now 30. Uh, I literally just turned 30 couple months ago and been good for you. Thank you.

Yeah, I mean, I'm like, get 25, you, you don't know how 30 feels like, so like, it's, it's, it's a hard But point and at 30 you don't know what 50 and 60 feel like. So it's okay. It's, it's a constant learning curve.

Forget, But I have to say, I mean, in the last couple of years, so many things have changed. And, um, just to give you my background, uh, I'm a software engineer. Uh, I've been trained as a software engineer back in frontend as well as databases.

I've like really built, um, enterprise solutions, enterprise e-commerce solutions for larger prints such as Adidas and Reebok, um, when they were part, uh, for customer, uh, for agency back in the days in 2015, uh, I worked on things like a 3D yacht configurator where you have an Oculus Rift on, you can walk through, uh, and then select interior that you want. I mean, that was 10 years ago. And about eight years ago, we then realized there's more to a problem that we had in the agency, which later on became story block.

But I really made that move from soft engineer to, uh, leading a department in the agency, then found story block and bootstrapping it first, and then late on hiring people. And now we are 270 people across 47 countries. Wow.

Have customers of like 130 countries as well. We operate globally, fully remote, so no offices, all, all remote work. And no, it's, it's been been a crazy journey so far.

And we are driving to hit a hundred million in the r in the next couple of years. And, uh, really like hit hits, balls running. I mean, we raised 138 million, uh, just 80 million in the end of last year to really grow in the us So we have just built our US team by now.

And I'm, I'm super excited because I'm originally from the Aus from from Austria, and, uh, for me to fly over to New York or Boston or San Francisco, it's just amazing feeling to be on the ground as well. So, really loved it. Good for you.

What a great story, man. I love it. So story block itself, how old is just story block?

Yeah, so the product started in two 15, end of 2015. Because at 10 time, yeah, exactly the start of the product. The company itself is eight years now.

So we started it after we built the first prototype. I love it. So you were original, well you still headquartered, I guess, in Austria or, you know, founded in Austria and now, you know, customers at 130 companies, you've gotta love the internet, right, man?

Yeah, it's just Crazy. They're having, um, having like 200,000 customers now and all of them are scattered 130 different countries. It's, it's mind blowing, but really nice.

It really is. It really is. You mentioned that, you know, when you made the move from software engineer to running the agency, let's call it, or a department, the agency department, you saw that there was a problem that you guys had, and this is a very common theme I hear from founders, right?

I have this problem, I'm sure I'm not the only one who has this problem, this is a problem for all of us and I'm gonna fix it. What was that problem? Yeah, first, the, the immediate one, uh, was actually to say, we, we are not gonna fix it.

We actually plan to not build this MS Like there was a huge goal that we had to not build one. And the reason we actually then started and were pushed into that direction is that we were using an enterprise content management system from the Austrian press agency exclusively at that agency. And, you know, like we are working with them for multiple years.

And, uh, I think it was okay, it was not the best system on the market. It was really old, it was older than I am. Uh, and I mean, that says a lot, but at the same time it was okay.

It was really expensive, but, okay. And one of our customers, they had a small issue where a button was somewhat doing weird stuff from time to time, not always, but from time to time. So we just filed a bug report, uh, in like mid 2015.

And we sent them, Hey, could you fix that? Um, it's not a high pressure topic, it's not high priority, but it's annoying for a customer. Please, please fix it.

And we actually expected a reply of like, yeah, sure, we'll put it the backlog. Six months, months, yeah, yeah, exactly. The reply was, oh, actually we're gonna shut it down in six months.

Please find something else. So we just signed two deals, five year deals with them, like literally a month before that. And oh my God, Big surprise.

So Alexander and I, my co-founder and I, we, we basically looked at that email like, they must be joking, right? So we called them and tell 'em no, they, they were actually realizing, okay, it's end of life. They need to transition away.

And they do it in the worst way possible because literally transferred so many clients into this solution that we then forced to find something, right? So we, we decided to find something that works for both marketers and developers, because Alex and I, we are both developers, same with the agency. Many of like, we're like a team of 40 to 50 people working on digital projects day in, day out.

And then we had customers, multiple hundreds of customers working those systems every day. So we tried to find something that works for both ends. And turns out, when we then looked into open source solutions like WebPress type of three, which is also CMS, um, we realized, okay, they don't want to pay for maintenance, so we need, we should not host it ourself or have a third party hosted.

We, we also want to have more control of it. So we decided, okay, maybe open source is the right one. So when the customers told us, no, we don't want to pay for it, it's way too much effort to customize it and to, to have the security bottle next there we decided to, okay, hey, let we look into the next one.

So from Trooper, we then looked into Acquia, uh, Adobe Experience Manager, Sitecore, which are now our competitors, but they are the large sales, so digital experience platforms that have CMS, but also e-commerce surge and a hundred thousand of other, other components. And reality is you use 10% of and and pay for a hundred percent, which is certain Truth that that's normal and software, right? 80 20.

Yeah. And we then realized, okay, maybe they need something lighter, something easier. So for the marketers, we ask them and to do a survey basically to understand what they want.

They want management, they want the visual editor, they want components that they can mix and match. So it is always on corporate identity and corporate brand, but they can still have the flexibility of moving things around. And at the same time, Alexander and I, we wanted APIs, we wanted data, we wanted purely just data, uh, at that point.

And we then realized, okay, we can marry those two areas. We can marry the idea of components, reusable content blocks for storytelling with an API approach. It had less approach.

So content management systems, uh, that actually deliver only data, not a visual part of it. And turns out if you combine storytelling with three years, it were content modules, content blocks, storytelling blocks. That's how we arrived at Story Block, right?

Story Block. That's, That's essentially what we came up with. And we didn't want to build it first, but when we were having the needs to transition out of that solution, we figured we'll just combine everything into one large database first and then build a UI on top if needed, or we move it somewhere else.

So our plan was to not build something, but to transition to a product that is already there, but there was nothing. So we started building the prototype in 2016 and in thousand 17, we, we suddenly had all our customers on the system and everybody was super happy. So we decided to launch it, just the, the website and documentation.

And in September, 2017, and one month later, we had 1000 users on the platform profitable, and we start kept in growing. So from 1000 people to 3000 users, then to 10,000 a year after 25,000, a year after that. Fully bootstrapped, no, no marketing spent, no nothing.

What A great story. Yeah. Good For you.

And then hit the ground running. Thank you. Good for you.

Good for you. Um, you know, I, I, so I spent most of my career in venture backed startups when I started what is today Techron. It really started as my blog.

I, you know, I didn't raise money before I even had a chance to raise money. We very similar story, we had sponsors and yeah, that was 12 years ago and we're still here doing this. Um, it's a great feeling to be able to do that.

Now look, I'm familiar with WordPress and some of the other CMSs out there. I never thought of the headless one. Like I, I kind of, and I'm not, I don't hold myself out to be a developer, though.

I could, I could develop websites in A CMS. Obviously you don't have to be a great coder, but, um, I never thought of the headless. Is that, is that, do you think the, a big selling point here?

Oh, for sure. I mean the, the real topic for headless Yeah. Has emerged the mo the moment mobile apps were on, on the ground as well.

Yeah. Because suddenly you had two channels where you get similar or even the same content. Uh, and now we have things like Siri or in general LMS that you want to get your data to.

You want to have a screen displays or, um, any kind of of displays in your company that wants to display, uh, data on or visuals on this all is powered by the same system and not 20 different systems powering each one channel. So the moment we stepped into this omnichannel kind of, of, of selling, that is the moment headless made sense because suddenly you have one solution that can cater all the different that Goes across The book channel. Yeah, yeah.

So that, that was the Moment sense to me. So Dominic, let me ask you, is story block is not open source? No, No.

We thought hard about it, but, And look, I, I get it. You know, the, that has its own set of challenges. There's rewards to it.

I mean, there are plenty of people, you know, basically then you would be doing a, a hosted version would be your money maker, right? Yeah, correct. Um, is there a free version, a trial version, a test version?

What's the story? Like? What are the, the tiers?

Yeah, so we, we, we thought a love about open sourcing or not, because both Alex and I, we really believe like open source is, is something fundamental that we need to support. And here comes the twist. I believe it's incredible hard to monetize, even with a hosted version, it's always hard to keep up with support and maintenance on that.

And many of my friends actually run companies like Y Young from NN uh, that definitely have cracked the code on open source and a licensed host, uh, model. It, it's amazing. But at the same time, for CMS where there are so many open source solutions already, we realize that the customers that we are catering to, which is upper mid markets to enterprise, they don't necessarily need it.

99% and higher. And this is what we then decide, okay, fast Open source is something that we don't do with Story Block, but the money that we are making part of it, we distributes to the libraries and the components that we are using. So for example, we are one of the, the backers of Futures.

We supported next shares for a long time and many, many community conferences globally. And even right now there's like 20, 25 different, uh, meetups that we sponsor every month. So that's great that that is how we, we try to give back, even though we know the source that we are writing, it's not going back, coming to the pricing.

Uh, so the pricing by now is, is fairly simple. We have a free version for developers. One user, you can build as many things as you want, uh, and you can just get started on the free using tier.

There's no time limit to it, but in the first 14 days, you can also access all the other features that we have. That makes sense on collaboration so it's completely free to use even after those 14 days. Uh, but, uh, as the moment you want to add new users, you will pay for those users as a usual software as a service model.

It's a monthly subscription, and then you basically scale. We have some other parameters like, uh, projects that you're doing, so spaces as we call it, and consumption of traffic as an example. And depending on the size of, of your company and the size of like the, the usage of storybook, uh, the pricing basically gets down.

So the more users you purchase, the per user pricing actually goes down, it goes, Goes down. So it's a recessive pricing that just helps you scale over time. So if you have larger needs, you can scale and we automatically apply certain discounts to then come to a point where it's scalable for you as a customer as well.

But the main idea is monthly or yearly subscription. And for enterprise customers, we do a three year contracts, five year contracts as well, if needed for price stability. But yeah, that's the whole plan.

Got it. Now, is it, so do customers self-host this on their own infrastructure or in the cloud? Do you offer it as a SaaS?

Both, yeah, It's a pure SaaS play. Yeah, it's a pure SaaS play. We do have some enterprise clients where we allow and manage hosting, where we manage in their own AWS instance, a story block.

So that is something we have allowed now on like a really top tier enterprise, either government, uh, or large insurance or banks. This is the territory that we're talking here. Sure.

So it's offering price. Exactly. Yeah.

It's a, it's a higher price tech, but at the same time, uh, the rest is usually the going for a software as a service approach. So we hosted, they paying a subscription and then just use our A PS directly. The website itself is unhosted by them.

It's not hosted by us, so it's completely in their controlled. Got it. So to me, like, look, you know, the big draw here, and I guess it's the reason behind the headless as well, is right at once, use it everywhere kind of thing, right?

So whether I'm using this content in my mobile app or my OTT app or my website, or you know, wherever it's gonna go today, and you mentioned even importing it, that data into an LLM for a, I guess an AI type of, uh, I implementation, it's fine. It's written once and it's used all over there via APIs. It, it just goes out via API.

Exactly. And is that right? That is a hundred percent correct.

And the, the main thing, what makes it headless is not that there's an API because then you can just call everything in API. Um, it's more that everything you do in the application, every action you take, all of that is done through APIs first. So even we ourself, we build the API first on the management layer and also on the delivery layer, and then we build a UI on top, and suddenly everything you can do in the ui, you can also automate because it is all API, uh, because recently we saw the movement of the, the older DXP players who announce that they are headless, uh, and, uh, always bring the competition.

If you get a bike and you add two more, um, uh, tires to it, it's not becoming a car. It's still a bike with four, still a bike, four, four wheels, right? So, uh, and, and that's the analogy I'm using.

If, if you're not building a system from the ground up with the idea and to the manifesto of API first, it's never gonna be the same as a solution that is really driven from that ground up. And that's a big differentiator towards other like, monolithic older players that really like try to, to scoop into the, the headless realm. But, uh, yeah, I'd much rather get a car.

Yeah, I get it. You know what, Tommy, we never mentioned the website. Where do people go?

Oh, yeah. com and really interesting, uh, block is not written like you think it is. It's not B-L-O-C-K.

Uh, it's BLOK. So story block without c uh, reason is quite simple. Alex and I were both software engineers, and to be honest, the domain with the C was already taken.

So we decided to just, I've been there, done that. I've been there, done that. Yep.

Good for you. What a great story. Dominic.

Thank you for coming on today. This, this is, you know, this is the stuff that white people get into tech, right? Follow their passion, solve a problem, make a great company.

com with a, there's no C-B-L-O-K Dominick, thanks for coming on. Hey, come back and keep us posted on this. We'd love to hear more about it.

It's great story. Great, great, great experience. All right, we're gonna take a break here on Text Drunk tv.

We'll be back in just a moment. Hey guys, thanks for the drone. We are here with Janin r Bell, who's the developer advocate in the office of the CTO for jfr.

And we're talking about the impact AI is having on developer productivity because, well, not everything in life comes for free, as we all well know. Janan, welcome the show. Hi, Mike.

Thank you for having me. I think developers are being more productive with their very least more code is being generated. How much of that code actually makes it into a build and then into a production environment?

Might be anybody's guess still, but, um, there is more code, so therefore there's more stress in the system. What's your assessment of what's going on here? What's the impact of AI on developer productivity and the software engineering teams that support them?

First of all, it's a great question. And I mean, all of us, specifically developers start using AI on a daily basis, right? We, we, we, we actually, we became, uh, from the developers, we became kind of, uh, product managers with, with some knowledge of development.

So we, we give all the, all the task and all what we need, we tell the ai, uh, agent to do, and it actually do. And sometime we not necessarily go and check what it puts in. And I mean, we're not vigilant enough, uh, about this, uh, line of codes.

And let me, you know, what, I, I can start even with, with a personal story. Uh, go ahead. Yeah.

So, so actually I started as a developer, uh, at Jfr. And along the years, eventually I found myself at the CTO office, uh, developer advocate, speaking with other developers, telling them how they should use our product. But, but the story is that I still love to develop, and I got, I kind of fell in love in all this, you know, vibe coding, uh, that going around these days.

Mm-hmm. And, and, and I, I started travel a lot, and I needed kind of, uh, application that I will be able to save my receipt. So, so, you know, eventually jfo will reimburse this barrier that I, I ate at, uh, 10 10, uh, pm So, so I developed a vibe coding with, with one of the, um, famous platforms of vibe coding, uh, on the internet, an application, a web application that will simply let me, um, save my receipts.

Uh, subject it by subject is by, uh, you know, by, by the event. So I have everything organized. I know I can do that with, with, uh, Google Drive and all this, but I wanted to build something myself.

It's, it's so easy today, so why not? So I did, and it, I was super proud of it actually, because everything worked amazing, like login work, the UI was much better than I could get myself. Um, and everything, everything looked like, you know, production ready.

So, so I shared it with, I mean, it was a personal application just for myself, not something that, uh, our customers using or, or any, anybody else, but I just wanted to develop it myself. And then I was so proud of it. So I shared it with some of my friends, and I said, Hey, you know, you are still, uh, taking pictures of your receipts.

Go ahead. I, I developed something, uh, go ahead and use it. And I shared the link with, with him and what happened the day after that, I found some of his receipt mixed with my receipts.

And then eventually what I understood is that, okay, it created a login mechanism. But then when I, I said, okay, Ahan, you're a developer. You know how to read code, don't be lazy.

Go inside and read what it, what it did. And what I saw, um, got me, you know, o off, off, off guard, because what I saw is that it did the, the, the query without like select, uh, asterisk from, uh, receipts and not, you know, it, it didn't add that, uh, like just bring the, the, the current user receipts just, and he said it, it brought everything inside. So of course, nothing happened.

Um, I, my friend didn't got reimbursed for my burger. Uh, we, I just told him to stop using it. I fixed it, uh, manually eventually, although of course I could tell the AI agent, Hey, you did some mistake.

Go and fix it. And probably it would understand what going on and fix it. But the point that I'm trying to say is that we still, we have to, uh, remain vigilant and, and, you know, um, aware of what's going into our code.

And it's not only about, this is just a simple story as a, a private story of myself, but it's, it's not just about this, uh, code, but also about what AI brings in, in terms of dependencies, in terms of, uh, like here is zero day, uh, vulnerabilities. So we have to keep ourselves vigilance because, because of course we see that AI is evolving rapidly. And you know, according to Gartner, uh, 33, uh, of the organizational application will eventually include an AI agent by 2028.

So, so we see like, kind of a new moral law, I would say, things that, that used to take months. Now, we, we achieve it within days. Um, but, but again, as I said, nothing is free as you, as you start.

And, and with this, you know, great power, there's, you, you there, you need some great, uh, bigger responsibility because it can eventually expose you to some vulnerabilities that you need to be aware of. So as this evolves, how much is the developer job gonna move from being in one where we spend most of the time kind of writing code and, and, and, and shaping it to maybe reading code and editing in it once the AI creates it? And, and will that have a different, you know, um, impact on the psyche of the developers?

Right? So, so as, as I said at at the beginning, w we, the developers, we, we, from developing and writing line of codes, we become kind of, uh, pilots with co-pilot. Like, like, uh, we have co-pilot, it's the co-pilot.

You are the pilot, and you should stay the pilot. And yeah, developers today find themself, uh, just typing in the chat why they, what they need and waiting AI to do it. Um, sometimes they look what it does, sometimes not.

And, and this is the whole story. We, we, we, we, if, if we used to spend our time inside the id, now we spend most of it in that chat of the ID telling, uh, AI what we need. Uh, because, you know, they always say good developer is a lazy developer.

Uh, but, but still, uh, we have to remain, uh, cautious, vigilant and, and be aware of what's going in. And it's not only about the line of the code, it's also about the dependencies that it use. Because, because AI usually, it doesn't have any context of your organizational policies of best, of your best practices.

I mean, if I think about it with a time, it will probably have, but as for now, it doesn't have the context. And you need to, uh, instill the right tools, the right, um, practices and workflows, so you will be safe and you will not expose your organization and worsen that your customers to risks. And that's why it's very important this day.

And, and, you know, you started, I mean, precisely nothing is free. And again, you need to pay attention if we play with this word. So this is your pay.

You need to pay attention, a lot of attention for what's coming in. What impact does this have on the DevOps teams that are, you know, sitting on the back end of this code flow. And, uh, if the developers aren't looking at it, then what do they have to do?

Or do they have to set up some sort of more vigilant review process? Because, well, to your point, developers are lazy. I said, you need to, you need to implement the guardrails and the, the, the processes that will make sure that nothing walks in and expose you to some risks.

Uh, because again, uh, we, we, we, we gain lots of velocity, but velocity doesn't necessarily say trustworthy. So yeah, you need AI helps, but you need to confirm, you need to have, as for now, someone or some tool or process that will, uh, govern it because you have to govern it, otherwise, it will run into a chaos that you will not be able to control, and if, if you govern it, so you cannot secure it. So it's all about the governance of the process and, um, being aware of what's and how your AI tools are being used.

And not only that, but also, um, as I said, as I said before, uh, you know, organizations start to develop their own models in the organization. They need to understand what kind of, uh, models are they are bringing into the organization, because we know that there are already some malicious models out there that can, um, you know, eventually do some, uh, very bad stuff and steal information from organiza from organizations. So yeah, you need to have this, um, firewall, I will say, between your organization and the outside world to be in control what's coming in, to be aware of what's already in.

So, you know, in a day of, uh, log four j uh, vulnerability, you will know to act fast and you will know, uh, what to do. And I say Log four J because eventually the way I see it models are like packages. And AI agents are like any other tool that can expose you to risks.

Um, in this case, we see that the, the adoption is, is widely spread and everyone is using, um, you know, everyone is using AI agent, even my mom, like, is she speak with Chad G PT all day? Like, mom, what are you doing? No, she is chatting with Cha g pt.

So, so it's, it's so easy, uh, to adopt and, and I can fully understand why people adopting it so widely. So Also will the, the type of developers that we're seeing change, because there'll be a lot more people who are not schooled in how to write code, but they'll be able to create an application using these vibe coding tools, and they may not have the appreciation for the finer points, and they might not even be able to read the code. So how do we kinda incorporate them into our happy little DevOps workflows?

Yeah, Mike, you know, it's a great point because, because I think the way I see it, um, AI and these tools are blessed, but also a curse because okay, for me, uh, uh, and, and, you know, uh, developers with, with ears of experience, yeah, we, we know the basics. We've been there, we, we, we trench our hands in the mud to, to get everything working, and now it's easy to get it. And, um, I'm like thinking about the junior, um, stu, the junior, uh, developer, that j that just started, most of the work are being done from him, for him, and, and that can, uh, eventually get him to be, uh, less professional maybe, but still, uh, if it will remain vigilance, then he, he, he of course, will catch everything and will be able to be a professional, uh, developer.

But again, it's, it's about not being lazy and let AI do everything for you, and if it doing everything for you, make sure that you have the right tools that will prevent him to leak, uh, secrets or, uh, you know, um, create some SQL injection zero day vulnerability, because again, we developer, we made it ourself. We, we created bug. We may, might, uh, put a zero day vulnerability, but we have a SaaS tools and, and things like that, that, that helps us.

So also, AI needs these, uh, you know, these guard rails that will prevent, uh, AI from injecting this, uh, code into our organization. And yeah, uh, again, people were not coding. And I also, I heard about, uh, about someone who developed an application and, and deployed it to AWS and, and like he, he posted the, um, post on, on Twitter or x how, what it's called right now.

Uh, so, uh, and, and eventually people understood and found some zero day vulnerabilities there and start exploiting these vulnerabilities, which eventually caused him pay a lot of money to AWS because people start mining some bitcoins and stuff like that. So, yeah. Uh, because he was, he is not a developer and he is not aware of what's going on, and he didn't have any tool that could, uh, tell him, Hey, look, you did something bad here.

You might want to change it to this and that. So yeah, of course, um, especially people who are not, and, but not, not only, but of course, people who are not developers, they need these tools, but also people and organization that, you know, that they're being, uh, under regulation and stuff like that, they have to, uh, get the tools, the right tools and the right policies and processes that will keep them safe. Um, because, because it's so fast and everyone is bringing code, what I said, what, what took me one month, um, before now taking a few days, and these few days, I mean, I got it with lots of, uh, velocity thanks to ai, but, but still, uh, most of the lines I probably, I didn't look for and I didn't understand what it really got in.

So you need to, uh, put yourself kind of, uh, process, uh, built in process and, and make reviews and make sure that you have enough quality gates, uh, that, so those, uh, risk will not, uh, get into your application eventually. And, and to production, Will we need something that feels like an AI agent to review the code created by the AI and, uh, provide all that governance that you talked about, because it's not clear to me we have enough people to go review all that code in the first place, Right? So, uh, I'm not, I don't know if it's an another AI agent, but it's, uh, we will need to, uh, supply the AI agent with tools that will make it, uh, understand whether it should use something in a way it should.

For example, let's say before you use a package, let's say just for an example, Axios, Hey, check, uh, my organization policies about this access package. Do I use it in my organization? Is it blocked by, I don't know, by policies, by security policy?

So once this AI agent, and we see with MCP now, um, giving tools to those AI agent is so easy. So, um, so before two, uh, AI agents will decide to put a packaging, it'll first know that it, he goes and check with the organizational policies. And if it's, if he get a green light, he continues, it might slow him down a bit a bit, but still, uh, he will be much safer.

This is a small trade off, but it's, it's definitely worth it. Are we really gonna be more productive or are we just gonna generate a lot more code that winds up being, need to be reviewed and fixed, and eventually just kinda winds up slowing us down more than it speeds us up? So eventually, I, I, I have no doubt, we will definitely, uh, we will become more productive.

Um, yeah, as for now, we do get lots of, uh, lines of code. Uh, some of of these lines are probably redundant and can be better, but with the time, and we see the evolvement and we see new model, uh, goes every, uh, couple of days. Uh, so yeah, I have no doubt that we will, we, we already more productive.

I mean, we, we see things, um, getting, you get things much more faster. You, you summarize the whole conversation in, in just, you know, 10 seconds. Uh, so yeah, we, we are, uh, more productive already.

Um, but again, it comes with noise and it comes with a price, as you said. Uh, and, and we need to be, to be aware and stay, uh, cautious about, about what it's bringing in and, you know, so be able to, to let it work for, for us and not us work for it. So, yeah, this is the main point.

So as you think about vibe, coding and everything else that's going on, what's your best advice to folks about how to approach this and get started, but maybe not go too crazy? Yeah, I, I, I, I would say start small, start with don't, don't give it the old Bible, and then do it now. Start small with, with small tasks, break it down so you'll be able to, to review this, what it's bringing in.

Um, don't, don't immediately give it the all application and, and just, uh, sitting and wait everything to happen. Start small, uh, be vigilant about what it's bringing in, uh, and, and understand this is a great opportunity to learn. If we talked about this, uh, junior developers, um, this is great.

It's, it's a tool that people didn't have before, and now they have the opportunity to learn, so we definitely should get advantage on it. Um, so yeah, my, my advice would be, uh, start small, uh, stay aware of what's going in and, and don't let any zero day, uh, vulnerability sneak in because it might, Alright, folks heard it here. Hey, everybody likes to go fast, but the thing about going fast is that if and when you suddenly crash, it hurts a lot more.

Hey, Jonathan, thanks for being on the show. Thank you very much, Mike. All right, and back to you guys in the studio.

Hello home, in the latest edition of the Techstrong AI video series. I'm your host, Mike Bazar. Today we're with Raju Malhotra, who's the CTO for Satia, and we're talking about the impact AI is gonna have on the services economy.

Hey, Raju, welcome to the show. Thank you, Mike. When you think about it, we've been kind of relying on services to drive the economy, at least here in the US and maybe in Western Europe and other places for a long time now.

I mean, it's, it is a huge portion of the GDP. Um, now we have AI coming. How do you imagine that AI is gonna change the way we think about services, and what should we be maybe getting ready for?

Yeah, I think it's a, it's a good question. It's a multifaceted question, uh, because on, uh, the very surface of it, any new technology, you know, require, there's a lot of help, uh, that the professional services provides. You know, it happened with the internet, it happened with digital transformation.

So it has a positive impact on the humans to provide the professional services to accelerate the adoption of, uh, you know, ai, gen, ai agent ai, et cetera. So I think the first impact is, uh, the professional services itself as a delivery organization is going to help deploy AI more for their customers, particularly in mid-market enterprise customers, et cetera. There are a lot of benefits to those customers, and I think over time, um, we are moving towards a hybrid workforce where you have the humans delivering some professional services, and you also have some, uh, incarnations of digital workers that are the agentic ai, uh, you know, uh, incarnations that help, uh, in conjunction with humans to actually deliver.

So I think the, the impact is going to be profound. Uh, it's, uh, somewhat clear, I think in the short term it's going to be accelerating, uh, the adoption productivity, uh, improvements and professional services is growing in that sense. Uh, but over time, I think it remains to be seen, you know, how that equation works out.

To your point, I don't think most organizations have the skills necessary to deploy AI and AI agents, so they're gonna rely heavily on professional services. But elsewhere, it also seems like the AI will, uh, automate a lot of the manual tasks that require to implement something. And the, the length of the engagement may be shorter as more of those things get automated using some sort of AI agent.

Is that a, is that likely? I, I, I think that's likely. And I, I also think, uh, it's important to peel the onion on when they say ai, what do we actually mean?

Because I think, right, right now, uh, it is a very overloaded term. Um, from, uh, NIAS perspective, we think about AI in three categories, three types of ai, predictive ai, generative ai, and agent ai. And I think a lot of focus these days is about genetic ai, which really helps you automate some tasks and actually have some level of autonomy and decision making on behalf of you within the guardrails to accomplish, uh, those tasks.

But let's not forget, I think the predictive AI has been there for a long time, for many decades, and that continues to play in very clear automation, productivity benefits. Those are very well understood. Generative AI is becoming very prevalent, very useful, uh, for summarization, simplification, creation of content, creation of images, et cetera, et cetera.

I think that is increasingly getting adopted. And agen AI is exactly, I think to your point about what the, where the puck is moving, where there's, there's a lot of, uh, potential benefits and potential risks. So I think the AG agentic AI is probably more about, you know, how that productivity, uh, really affects, uh, the workforce.

But we should really think about, I think productive AI and generative AI are here to stay. They are actually having already a lot of profound impact. Mm-hmm.

As you think this through a little bit, I might argue that the number of professional services engagements has been limited because the cost has been higher. But if I have, uh, a shorter engagement periods, might I not have more projects as we go along? Because there's plenty of things that we never get around to doing, simply because the total cost was too high.

So maybe we'll have more engagements. Yeah, I think overall, really it comes down to, um, what exactly is the role of professional services, you know, short engagement, uh, specific engagement, time bound, or, uh, you know, exactly what the, what the kind of benefit does. I think there's a big change in that because it is moving from a time and material based model of hiring some consultants to get some jobs done for professional services to more of an outcome-based, you know, model also.

But to your point about, I think, uh, would it open up the aperture to do more with professional services? Absolutely. I think, uh, is it actually increasing the revenue for professional services already?

I think that is also true because in conjunction with the, the new tools that the professional services organizations have, they are actually getting more and more outcome focused also. So they're delivering better value, and they're able to charge a better rate, better, you know, revenue out of the engagements, even if those engagements are, uh, shorter in some cases. Mm-hmm.

Will the nature of the services being delivered change as well? Historically, um, professional services team would come in and engage, and they'd probably move in for anywhere from six months to two years, sometimes, depending on what their project is. I wonder, though, if we're gonna rely more on agents to deliver those services, is the, as the professional service is gonna be more continuous, and it will be something that we're kind of proactively managing on behalf of some customer somewhere.

Uh, but it's just always on. Yeah, and I think the, if you really think about what is happening in, in, in those few months, few quarters, few years of that professional services engagement, if you peel the onion and, and, and what's happening is there is some type of integrations that are happening amongst diff, you know, different systems that the enterprises have. There might be some, uh, custom code development that is happening that is actually either a glue code or a new kind of, you know, application.

There might be some cleaning of the data. So I think if you peel the onion a few layers deep, then you really, you know, can start thinking about the application of agent AI in those cases. We know Agen AI actually works very well for a lot of development type of use cases.

Cursor, Devon, GitHub, uh, copilot, um, Andro Cloud, et cetera, have already have had a lot of impact on reducing the time it takes to produce some code. And it could be in conjunction with a smaller human team for a shorter amount of time, but the output of, uh, uh, that, uh, project can be significantly increased. So I, I think, uh, you are right that a, I think it gives a lot more control in the hands of end customers who are actually buying these professional services, uh, engagements, but it also improves the level of predictability and the value that they can receive by using agen AI in conjunction with the human teams.

Mm-hmm. One of the things that we rely on for professional services a lot historically, has been these kind of application modernization projects where I had to go in and reverse engineer something and refactor. And I wonder if that's gonna become a lot simpler because, uh, the amount of time it might take to, uh, convert something from, uh, uh, one programming language to another, and these are all where those lock-ins have been.

So is the cost of switching platforms gonna drop? Well, I think, uh, in, in the case you're talking about, uh, the data is locked up in different applications and not just one platform, but multiple different platforms and quote unquote legacy, which might be, some of them might be on-prem, some of them might be in cloud one, cloud two, et cetera. So it, it can be a very onerous sort of, you know, exercise, uh, to do that through the old way of doing human, uh, the professional services approach.

I actually absolutely agree with you. I think it, it actually changes, uh, the realization of value from new technology because you really think about, instead of piecing together different silos, you really think about how do I get to the core of my organization's data? It could be employee data, it could be customer data, it could be business data, it could be different types of transactions.

And then instead of relying on the, uh, different software logics that, those app custom applications, or even the off the, uh, you know, uh, uh, standard sort of applications, how do I actually apply the agent AI to connect those data points and create that right fabric to achieve my outcome? So for example, if I have to take an action for, uh, closing a customer deal, I can actually use my agenta and the MCP connectivity or a, to a agent to agent type of connectivity to actually much more quickly get into my employee data, get into my skills, and, uh, consultant profile if it's a professional services organization, and move much more rapidly, uh, instead of being, uh, encumbered by, uh, the, uh, integrations that I might have to do otherwise. So I think, uh, yes, it actually opens up, uh, that possibility of agility, uh, and really comes down to, uh, leapfrogging, uh, in many ways, uh, the state of, uh, affairs that might be in some enterprises.

I don't think we've used this term in a while, but it sounds like maybe this is a massive exercise in business process re-engineering, and this time we may have to go in and actually think about a lot of the processes that we have. Sometimes I feel like there's more exceptions than there are rules. So are we gonna have to go in and make it a little more structured for these AI agents to automate it?

Uh, I think you're right. I think it, it, it would require re-engineering of the processes. One of the caveats, however, is that even when business process re-engineering was done well, and I say e when, when, because there were a lot of sort of exceptions to that rule.

Those processes were designed for humans. And humans have a lot of qualities as, as, as obviously, you know, we're defending our sort of human part of it, but there are a lot of inefficiencies that do not apply for agents. So I think the business process reengineering would be very different if you think for, for the agent to agent communication and, uh, the machine type of communication.

And that's more of a connectivity with the right guardrails and permissions. Um, but the workflow and the processes can be significantly accelerated and faster, uh, compared to, I think what the business process engineering of the olden times has been. So, so yes, I think at, at some point it is about reengineering that, but uh, really I think it comes down to the level of, uh, application to the agent scenarios, which is very different from human scenarios, Right?

So taking that to the next logical level, on the one hand, professional services firms will have their own AI agents and customers will have their own AI agents. And how will these AI agents kind of communicate with each other to create something that goes to that outcome that we're talking about? Because it's one thing to get my AI agents to talk to themselves, nevermind talking to somebody else's.

Yeah, I think it's, uh, sort of embarrassment of riches kind of problem, because you do want to have, um, interoperability, openness and, uh, different systems will have, um, MCP endpoints, just like we have the API endpoints for connectivity. But now you have much more agency, much more control, much more agility and action ability, uh, through the agent to agent communication. So I think he, first of all, I think it's important to know the embarrassment of riches comes because it would become very easy to create agents, and that doesn't mean you have high quality agents that are 30 certifiable and good sort of proxies of your digital workers.

So there's a big difference between creating an agent and actually creating a relevant, reliable, good, useful, productive, ramped up agent. And I think that's one point. And the second point you're bringing up is, uh, even when you have the right agents for different tasks and different areas, just like kind of, you know, digital workers in different departments and across different companies, then I think the, the collaboration and communication protocols that are emerging right now, to be fair, I think we have the model context protocol that, uh, anthropic announced and, you know, pretty much, uh, all the other major players are beginning to adopt it.

We also have the agent to agent, um, you know, um, uh, communication. I think that interoperability would evolve and, uh, would help orchestrate the agents, uh, in a better way. Uh, but I think the fundamental part is still going to be your core value is still the data that you have, the clean, actionable information about either your customers, about your business, about your employees, and how do you actually use that to deliver value.

I think that's how, uh, the, the communication is one thing and I think will evolve that communication. But still, uh, in that communication, the unique value that you bring as your agent or agents is still going to be very important. Right.

How will the role of the people who bring the professional services and the customers they engage, how will that evolve? Where, how do you envision people being involved in this? Or is it all just gonna be agent to agent?

No, no. I do think, I mean, I, I personally, and I think as a company, we do believe in, uh, uh, agent and human, uh, collaboration in many ways, peer to peer in many ways. You know, uh, agents working for humans, in fact, in some cases, humans working, you know, for an agent.

But I think it would be a collaboration, uh, uh, uh, type of situation. But, uh, I do think the evolution of this, uh, is in service of accelerating a lot of charter that we have defined as human beings for the organization. So for an enterprise use case, it still is important about vision.

What is the endpoint that you wanna have for your business? What does success look like, uh, for, for you as a customer, how you are creating value? What is the strategy?

What are the choices? What are the, you know, specific steps you are taking there? So the agents actually come in to accelerate, to automate, to, uh, collaborate with the human beings to, um, provide some of the kind of the tasks.

So it could be as part of an employee team, you have, you know, maybe an onboarding agent that actually helps the new employees just get up to speed much more quickly and discover the content that they need to do. Because it may not be as exciting for human HR manager to be spending a lot of time on something that is very tactical. Um, but I think in the same time, you have the, a lot of the, uh, delivery agents that work with your, uh, software engineering team to produce higher quality code that you actually want to deploy and use.

But that code could actually be really at a 10 x level to solve some way more complex problems. So I think it's a situation where, uh, agents, frankly, our sort of point of view is that it becomes a very much a tool in service of, uh, solving the problems that we wanna solve, uh, as a humanity versus, uh, little bit of a dystopian view of agents taking over. Alright.

Hey folks, you heard it here. We all have been a little obsessed with the mechanics of ai, large language models and how AI are gonna be built, but maybe the time has come to start thinking about, well, just how are we gonna use all this stuff? Hey ou, thanks for being on the show.

Thank you, Mike. All right. And thank you all for watching the latest episode of the Techstrong AI Leadership Series.

You can find this episode and others on our website. We invite you to check them all out. Until then, we'll see you next time.

Standards bodies don't just set technical specifications. They also drive greater understanding of the topics in enterprise technology like storage and ai. This episode of Utilizing Tech brought to you by Solid I features Dr.

J Metz, chair of SIA and the Ultra Ethernet Consortium and Technical Director of A MD, talking about how we can spread standards and ideas around the industry. Welcome to Utilizing Tech, the podcast about emerging technology from Tech Field Day, part of the Futureum Group. This season is presented by solidi and focuses on advanced topics like AI at the edge and related technologies.

I'm your host, Steven FoST, organizer of the Tech Field Day events series, and joining me today from Soy as my co-host is my old friend, Scott Shaley. Welcome, Scott. Hey, Stephen.

Good to see you again. Uh, I know we recently saw you in person, actually at a, a recent field day events. That was awesome.

Uh, great to be here again. Yeah, it's good to, it's good to see you as well. And um, as I said, you know, you, you and I go way back.

Um, one of the areas that we've both focused on for a long, long time is storage. And, you know, those of you outside the storage industry may not know it, but there's actually a really nice community in storage, um, a great group of people who love to get together at events. You know, for example, the storage developer conference is one of my favorite nerd fests, you know, FMS, there was the old storage conferences and so on.

And, and one of the coolest things about that is sort of the cross pollination that happens when you learn about what other companies and other people are working on, and you try to bring that into your world. Yeah, absolutely. I mean, that's a, a perfect example of that is, uh, I have chosen my, uh, attire appropriately as I now sit on the board of directors.

I've said one of those groups, Nia, and it's been an interesting way to utilize, to your point, what's going on in the market around, you know, all of us working to drive innovation forward, but we all know that we can't just do it as a one-off. We can't be unique or independent in certain ways and aspects of that. And so being able to tie all that together and, and bring it in as a conglomerate of people and companies to present to our customer base makes, uh, the existence of all these technologies more possible.

Yeah, it's been really, um, great having, uh, you know, I think people, when they think about standards bodies, they think about the technical aspect of standards bodies rather than the sort of evangelical and spreading the gospel aspect of standards bodies. Uh, SNY a is one of the companies or one of the organizations, I'm sorry, that is really, I think, spreading the gospel of storage far and wide. It's not about, you know, totally looking inward at, you know, how can we make storage better?

It's about how can we bring storage to the world? And that's why we have, uh, brought our old friend, uh, from who, who happens to know a thing or two about Snia a uh, Dr. Jay Metz to join us here on the, uh, uh, podcast.

Welcome to the show, Jay. Thank you very much. Very happy to be here.

Thank you. So tell us a little bit about yourself. Well, I am a technical director for advanced storage and networking strategy for the data center group inside of a MD.

And I am also, as you said, I'm the chair of SA, uh, have been for about five years now. And I'm also the chair of the alters and that consortium. So I've got kind of hands and and feet in both areas of the networking and the storage and the storage networking, and so on and so forth.

Uh, so that's what I do that and wear hats. It, it's, yeah. I was gonna say, and of course he's wearing the, uh, traditional js hat attire that is known for far and wide as, uh, Steven mentioned you'd go to an SDC event, and if you see Jay without his hat, you don't know who he is.

So it's been very, well, if I take off the hat, it's a, it's a being incognito, you know, people, I would never, ever make fun of Superman, you know, for taking off his glasses. 'cause I take off the hat. People just don't know I'm there.

It's, it's a fascinating event. And now speaking of not knowing that you're there, um, that's one of the things that people take for, take advantage of, if you will, as, as far as what this conversation's about, which is how we participate in these standards and these different consortiums and what it's really doing for the market and for our customers. And a lot of the time, those folks don't really see what this behind the scenes does.

So to, to Steven's point, the e evangelical part of it or the, the communication piece of it is something that you and I have spent a lot of time doing together, uh, within Snea now you as part of UEC as well. So, Yeah, and, and it's always, it was always kind of interesting because, you know, from the outside looking in, you think that this is just this one big monolithic entity that's kind of, um, solving a particular problem. But, uh, it winds up being much more involved in that with different, you know, perspectives and different attitudes and different thoughts and ideas and creative, uh, creative venues.

But it winds up being particularly interest for those of us who get involved in this, because there's always a new problem that has to be solved. You know, there's, there's nothing is ever really finished. So we get, we get some pretty nuanced approaches to solving problems that get both big and very small and, uh, in, in different areas.

That's a good, uh, kind of summary of, of storage. One of the things that makes storage interesting is the fact that it is very big and very small and very fast and very slow and very high powered and very low powered. I mean, storage is a lot of things.

Mm-hmm. And, and, you know, you and I, and well, all three of us are really have been, um, discussing all of these aspects of this technology for so long. And yet, um, I think again, there's not as much understanding of the nuances of storage, but that's changing now that we are starting to have greater and greater demands.

I mean, AI drives, um, greater use, uh, or greater collection of data. It requires data to make it work. Um, a AI-based applications are very data-driven applications.

And data collection means storage. It drives storage capacity, it drives storage performance, it drives bandwidth, it drives connectivity and networking and io and these are all things that groups like Snia a and the Ultra Ethernet Consortium are trying to evolve. Right?

I mean, have you noticed, and I'm gonna ask you a leading question here. Have you noticed that these things are ever more in demand in the modern world? Uh, you know, what we've been doing in storage is suddenly, uh, really important.

Well, I think the short answer is yes, of course. Um, longer answer is a little bit more involved. The three of us and those who are storage oriented people, we've got a certain intuition when it comes to what we mean when we use the term for those that are maybe software oriented or compute oriented or hardware oriented.

They may not see storage the way that we do intuitively, right? They may see it as capacity inside of a drive or a hard drive in and of itself that is storage after all. But the, but the, the real element that we think about when we talk about this is that it's not just about how it's stored.

It's about how, how you get it back. How do you move it, how do you preserve it? How do you, uh, make sure that it is there when you need it, when you need it at the right place where you need it, how do you make sure it is the, the exact thing that you thought you were going to get?

Um, and so what winds up happening is that what we consider to be storage, other people would call memory, other people would call networking, other people would call software, other people would call, you know, backups or archiving. Other people might actually look at it and say, um, you know, it's, it's management, right? So all of these things are, are depending upon how you take the diamond and you look at the different facets, and you could see storage reflected back at you at any given point in time.

But you know, what I think we try to do in Snea, and what we're trying to do in UEC and some of the other organizations that we work with, is that we're trying to say, look, if, if you, you say that you do this, or you need this kind of, or that kind of bandwidth, or you need this kind of latency, what do you need it for? Well, you need it for getting data from one place to another place, or what does that entail? And the further down that rabbit hole you go, the further there is to go, it's sort of like saying, what is the length of the English coastline?

As you start to drill down until the beaches and the actual individual grains of sand, you start to realize that it is an ever increasing fractal distance of information that you're gonna have to try to consume. Storage is the same way. If you wanna talk about moving a bit from here to there, what does that actually mean?

Does that mean you have to go through buses? Does it mean you have to go through, uh, buffers and caches and, and, and NAND or, uh, you know, high bandwidth memory? What does it actually mean?

You know, what are the channels that you use? What are the networks that you use? All these makes a difference and it makes a difference at a really small level, and it makes a difference at a really big level.

So, for instance, you know, um, I, I know recently you had a conversation with Gary Greer. He deals with really big systems, right at Atlanta, really enormous systems. I mean, he's got petabytes of, of ram, for example.

Um, and then at the same time you've got these, you know, these AI models that are starting to approach the trillions of parameters. And the, the average lay person doesn't understand what that means in terms of having the material to be able to do this. If I've got a 1 trillion parameter, large language model, for example, I need around 32 terabytes of RAM just to be able to hold it, right?

Well, no processor has 32 terabytes of ram, which means you've gotta be able to have a lot of processors together working together as one unit. Well, how do you do that? The data has to move from one place to the other, and you create little tricks, right?

You create parallelism and little tricks. That means that I can have things going at the same time. But what do you do when you do that?

Well, you change the nature of the data movement. It's no longer big pieces of data moved all at once. It's now big pieces of data moved all at once, and little pieces of data moved all at once to let everybody know where the big pieces of data are.

So you've got a, uh, you're, you're moving, you know, the needle in a number of different areas at the same time, just by small little tweaks in what you're trying to accomplish. And storage has to embrace all of it. And so that's why what we do at Snia is so interesting 'cause we have to do all of it.

Yeah. And, and if you look at it from that perspective, I find one of the unique pieces of that is like, look at the, the history of soy and where the markets come from. We had the introduction of E-D-S-F-F and the small form factor, which is now SFF within ssea.

It's whole purpose is to help with connectivity, what the box looks like and things like that. And we've got new systems and solutions that are being utilized by even the, the fastest AI clusters now that are using a unique form factor designed and developed out of something like snia and led by a bunch of these different companies paying attention to what you're talking about. Um, I have a, a very dear friend in the virtualization world, and I think I may have or not used this, uh, previously, but he still talks about storage as chips and I, and we're talking SSDs that sit at 64 terabytes, and to him it's still just a chip because he's not a, he's not a hardware guy.

And so that's where we, as these groups of people who really know what he's talking about, can help evolve that ecosystem without him really having to change his definition, but just solve his problem. I don't wanna cause any face palming, but I think a lot of people still think of storage as discs or maybe even as tape. And, um, of course those are still, they're still relevant technologies.

And I think that if you ask somebody in the know about storage, uh, they will absolutely stand up for disc and tape, but they will also say, check out what we're doing here. You know, And, and, and as well, they should, right? Because, because the thing is, like I said at the very beginning, we understand and intuit what it actually means, right?

And so, but when I talk to the people at UEC, for example, or I go in, I across the aisle to OCP, or if I talk to people at the Linux Foundation, I have to choose my words more carefully because there's the shortcut of saying storage doesn't exist with them. Right. You know, incredibly intelligent people, but from it coming from a different perspective.

So it's really important that we allow ourselves the luxury of learning how to communicate the proper terms in a way that's gonna be received correctly. Right? So, um, when I, when I wanna talk about the data for AI, or if I wanna talk about the data for, um, for HPC, that gives me the ability to have a level, common ground of when I'm talking topologies and networks, or if I'm talking about bid error rates on the physical level, or if I'm talking about, you know, in-network collectives at the software level.

Because by being able to redefine the question, you have a lingua franca that you can use to be able to associate what they want with what you can provide and vice versa. Yeah. And you actually bring up a very interesting, uh, comment about the fact that the, the cross pollination, right?

So I sit on SNE aboard alongside yourself, but I also participate in NVME and a few of the other things like OCP whatnot. And not only do you have to choose the, the, the moniker, the terms you use, but you also have to be careful about overshare and unders share and stuff. 'cause there's all these nuances, just like you have NDAs between companies, you have relationships between consortiums and until something's officially official, you actually have some unique aspects of how, uh, managing all of this stuff comes into play.

And being able to address that and drive across, uh, those barriers and screw driving solutions is kind of a, a unique aspect of what we get to do from that side of our, our day job. If you'll, Yeah, and I think it's absolutely critical. I mean, you know, last month we had a, a joint session between UEC and snea, right?

We had a, you know, face-to-face between the two different organizations. We, we did technical symposium individually, and then in the evenings we had birds of a feather where we could kind of combine and, and work. And then of course, we had the regional STC, um, where the, you know, the materials should be available online, um, soon if, if they're not already.

Uh, and the whole, the whole purpose here is to make sure that, that the work that's being done can be extended into other areas so that people don't have to reinvent that wheel. UEC is one of those places in particular that is, that is specifically, um, going to hurt, um, with the, in the data area if it's not careful, right? Um, and this is not necessarily just A-A-S-N-A solution either, but the SNA group, um, needs to be able to understand the proper, you know, framework under which the work that they're doing is.

And so mixing the two initiatives together is really important. If I want to, so for example, in ai, we have multiple network types. We've got a front end network, which is your general purpose network, and that's where most of the storage lives.

Then you have a purpose for ai, right? You have a purpose built network for ai, and that's what we call a backend network. It's like the 32, you know, uh, terabytes of RAM that you need in order to get the, you know, a system to work, uh, for model.

But since you need the data on one network, but the data exists on the other network. You wanna make sure that you have the best and most efficient ways of transferring the data, or in the future, you wanna have the data on the network that's doing the processing, which right now it isn't. So that's a, that's a, a fundamental aspect of AI that most don't even realize, right?

They don't realize that the data isn't even where the processors are. It just doesn't exist. So you have to go through all kinds of unnatural acts to get the data into the proper network so that the GPUs and the TPUs and the accelerators can actually process it.

And then if you're doing a lot of that movement, it makes sense that the organizations that are focusing on the AI network and the organizations that are doing the storage talk, and that's the whole reason why we're doing what we're doing. Yeah. You bring up a, that's a very interesting, and, and to your point, as I, as I mentioned, we recently saw Steven in person, and one of the, the aspects of the presentation that we brought forward was working with a partner to highlight how we can leverage storage to actively replace aspects of the memory required to drive some of those language models.

And there's trade-offs. Do I spend a fortune on the RAM to add and use my storage and accept a little bit of those trade-offs and things like that? But those are things that these organizations can't take the time to think about if they're busy thinking about that true backend that we're driving with the consortiums and, and the work that we're doing to get data from here to there, whether it's edge in, you know, AI at the edge, or AI in the data center, or rack to rack, all that kind of stuff plays a very big part of what we kind of drive with all these different, uh, efforts that we're doing.

Well. I've always been a big fan of one plus one equals three. Um, and I've used that phrase before, but if you, if you look at a particular technology like we've got inside of, of CN, there's two in particular that come to mind that are, are, and not only two, but there's just two in particular that come to mind.

One is the smart data accelerator interface, and that is the ability to use hardware to do movement, uh, data movement from, uh, from one memory location to another memory location. Um, and in and of itself, it is a very interesting approach to solving problems in a, um, uh, especially in a high, highly abstracted area, like, you know, something as a service. Um, the other thing that's really important is computational storage, right?

Where you've got the compute processing power next to the storage device itself in and of itself, it is an interesting technology. Now, let's switch over to, to UEC for example. I've got a processor that needs to run an awful lot of data and I need to move the data in, but the data has different types.

It's got object types, it's got parallel file systems. It's got block, and not all are being used at any given point in time. But if I, like in, in, um, you know, in LA L'S situation, they managed to figure out a way to avoid having to move exabytes of data or, um, at any given point in time for their iterative cycle inside of their, their workload by doing processing, right?

At the drive itself. In U'S terminology, we could do the same thing because the parallelism that involves really means that I've gotta send data to another processor to be processed. But if I wind up with that same principle of having the compute next to the data, I now shut down the need for the bandwidth, the need for the latency, the need for, uh, the network, uh, connectivity at that level.

I can actually reduce the need of it. Not ne you can't reduce it completely, you can't eliminate it, but you can reduce the need of it because these things are getting so big that you find yourself at the limits of physics, right? We need better efficient ways of doing things.

So what's that? That is the, the memory movement model, the com processing near the me, uh, near the, uh, near the, the data itself. And you've got the proper network directly connected into, uh, the processors, one plus one equals three.

So in and of itself, it's great combined to get, it's even more powerful getting those two groups to get, come together and have those conversations, has to start somewhere. And so that's what we did last month, and then we're gonna continue to do this, uh, in the future, not just with between UEC and, and sia, but you know, um, organizations like OCP, like IEEE, um, you know, UUA Link, uh, OFA, the, all of these different groups and organizations, that's just, some of them, you know, they all have a vested interest as we move forward in solving these massive problems to be able to be aligned. And fortunately, it's a really good thing, um, that right now, as of right now, there's a, a willingness and an inclination to do so.

You know, it's interesting that you talk about that. Um, if I had, um, taken out all of the proper nouns from what you just said, you just described the Edge AI use case as well, where we have limited bandwidth, we have to move processing closer to the data, et cetera. I mean, and this to me, Jay, this is the thing that has been so remarkable about going to industry standards, bodies and, and events and seeing what they're developing.

It's the, maybe unintended, but always in fun and surprising cross pollination of ideas. I think when, when, um, the next generation storage form factor designs were set, no one could have predicted how that would transform the design, the physical design of edge servers, and yet it did. And it is rapidly changing the entire E edge industry when, um, technologies, you know, DMA technologies and, um, you know, mo computational storage and so on, I think that those were defined before, uh, the AI use case arose, or at least the AI training use case arose.

And yet, look at that. That's pretty useful over there, you know, and that's something that makes this all happen. It's like, um, it's like magic happens when you have different people with different areas of expertise all communicating openly and all saying, Hey, wait a second, we did something really like this back in the day to solve this other problem, and now we have a similar problem here.

What if we, you know, for example, move compute closer to the collection and storage of data? What if we, you know, offload things? What if we develop protocols, uh, that allow you to, um, to have, for example, hierarchical memory, you know, that came from, uh, supercomputing, uh, developing PMA supercomputers, and then suddenly that's the core technology that enables CXL or the core concept at least that enables CXL.

It's so interesting to see how these things kind of spread, like fire from one spot to the other spot. And, um, and I think we're definitely seeing that with HPC and AI right now, right? Yeah, yeah.

There's, there's a lot of characteristics of both at crossover, but enough of a difference to make it interesting. Um, so yeah, it, it's, one is not exactly a complete overlap of those Venn diagrams and the other, but there's, like I said, there's enough of a, a cross combination to really start to challenge people into solving those problems. I think, um, you know, when we get into, when we get into what's going on in the future, the very cool parts of this is that much of what we want to do has been solved in the past.

It's at a different scale. It's at a different level, but it involves, you know, two basic fundamental, uh, concept. Concept One is the margin for error is much smaller, right?

So, and, uh, and as a result, very small increments of, um, of problems can create much larger amplification problems in, in, you know, for systems, right? Um, because of the tightly coupled nature of the way that these components work, if one goes down, the whole thing goes down. So it's very, very delicate, very sensitive.

So creating robustness and reliability in there is something of a challenge. But the other part of it is time. And we tend to forget that as fast as we are, we are still dependent upon other things to be able to feed us information or we have to feed them information.

And sometimes that information is at a higher level. It's at a control plane level, it's at a management level, and sometimes it's the data plane itself. But the act of time has made a huge, played a huge role in what we actually need to do, right?

And that's where the bandwidth comes into play. That's where the latency comes into play. The ability to get something or send something very quickly also means that you now have to run the risk of being idle while these other things are doing their own thing, right?

So the whole system has to rise. All, all the boats have to lift, right? That water has to be able to lift all boats.

It's not good enough to say that I've got the world's best GPU or the world's best CPU or the world's fastest ram if I can't get data in and out of it fast enough, or if I can't get the other piece of equipment on the other end of the wire to send or receive fast enough. And we're talking about wildly disparate components. We're talking about network interface cards.

We're talking about, you know, GPUs, we're talking about TPU and so on and so forth. And they're not all equal. They don't all have the same performance characteristics.

And so, and they're not designed to. So you've got a lot of variability and a lot of of ambiguity when you start off with a very specific and demanding kind of workload, whether it be HPC or ai, that all has to work together in concert. You know, you can't be playing, you know, box, you know, you know, uh, brandenburg's concerto in one group, and then you have, you know, Beethoven's fifth on the other, and at the same time it just doesn't work.

You know, two beautiful pieces of music, just not at the same time. So you wanna make sure that everything is working together in that concert. And that is where, you know, you have to think outside of your own myopic world.

And I don't mean that, I don't mean that pejoratively, I mean that, I mean that actually quite, quite admirably, right? We work so closely on the stuff that we do that it's often easy to forget that what we do influences other people. And if you don't actually work with, they're gonna go off and do their own thing, they're gonna create yet another standard.

They're gonna create another way of doing things, and then someone's gonna do something that's gonna take off, and then all of a sudden everybody's gonna flock over to that. So if you want your systems to work and you want your approaches to work over time, you've gotta rethink the significance and the influence of what you're working on in order to be able to make sure that not just you, but the people that rely on you are going to be able to accomplish this over time. That's a very valid point.

And I think it's interesting 'cause everything you're talking about can be to Steven's point, I can be right here in the core data center, and all those problems exist in one version of a world, and if I move out here to the edge, it all still exists. And then getting between the two becomes even more of a, a unique challenge. So it's, it's always kind of crazy to see that.

And your, your concept about the, the myopic ness and things like that reminds me of going way back into past to a tape-based storage, uh, war if, for those that are old enough to remember Betamax versus VHS, for example. That's a perfect example of kind of what we're trying to prevent here, both with Snia to Steven's point about the broadcast of evangelical side of things versus the, you know, nuts and bolts of being myopic and building the really cool thing. But the really cool thing, the lost because they weren't playing well in the marketplace and, and the rest of the ecosystem didn't, uh, parlay along with them.

So, um, it's interesting to kind of always keep that in mind about, you know, past, present, future, and there's always going to be a, a fun new thing to work on. It's just where, and how far away from today's shiny object of ai, or how far physically it is edge versus data center in this whole play of things that we're working on Agreed. With that said, uh, Jay, uh, what are you most looking forward to, uh, what developments in the industry are you looking forward to?

Now that we have this monster, uh, business driver of ai, where are we going? I am most looking forward to, and this is more of a selfish me thing, I am looking more towards extrapolating the stuff that we are doing inside of these different things from a technical perspective and marrying them to the ethical and moral implications of accomplishing these goals, right? I, I do think that we have a tendency as technical people to forget that what we do matters.

And what I do, what I, what I do, what I do is because of the fact that in order to preserve those, those guidelines, you should have the most efficient, effective, accurate data when you need it, where you need it, so that you can make informed decisions. And so I think the infrastructure is not divorced from those questions. It's not a software problem, it is an everything problem.

And so I am looking forward most to being able to have those kinds of conversations where the work that we do have a full understanding up and down the stack all the way to the end users so that people can feel more comfortable with using the technology without having to fear some sort of ai, you know, a GI moment of a, you know, of, of what, what's the word it's called? Um, the anoma. The singularity.

The singularity. There you go. That's the word I was looking for.

Um, and I, I honestly think, I, I honestly think that now is the time that we need to have those conversations, and I'm looking forward to having those. Yep. And, and I'm gonna just go out on a limb and say, if you're interested in those, in those conversations, they're happening in the standards bodies.

They're happening where people can get outside of their companies and out there talking to each other. Uh, again, I'll just put in a little plug, you know, my favorite tech, uh, event is, uh, is the sne a storage developer conference because it is so open and nerdy and fun and and engaging. Uh, there are of course, lots of other ones, you know, I mean, you mentioned OCP, which is always a lot of fun every single year.

Supercomputing is always a lot of fun. Every year. There's a lot of great conferences out there, and anytime you get people to together to share ideas openly and to really explore what this all means, what you're gonna find is that people are not just technologists.

3 version of the specification. They're interested in having the big picture conversations that Jay just described. In fact, he and I have had big picture conversations with Scott, you know, sitting in the lobby of the hotel at, at these conferences.

This is what it's all about. So I urge our listeners to get involved in these things. Um, before we go, Jay, uh, tell us a little bit, how can people get involved in some of the, uh, standards bodies and, and events that you, that you go to?

org as a starting point. Um, you can contact myself or Scott. I, you know, Scott is the chair of the Communication steering committee for SNA, and so he's responsible for communications.

Um, you can find me on LinkedIn, you know, with J Mets. Uh, I am wearing a hat, or actually, am I wearing a hat? I think I'm wearing a hat inside my picture there.

I may not be wearing, I know, but what the heck, what am I, what am I, what am I thinking? org. And, um, and there's a lot of material there under the news, uh, uh, situation as of as of right now.

0 specification. We're gonna have a lot of material educating people on what that means, how it works, how to implement it. And so there's a lot of material in both organizations that are, that are coming down the road in the next six months or so, that you can find out a great deal of, of, uh, information on these topics.

How about yourself, Scott? Uh, what's coming up for you? Yeah, so it was great to do the field day.

We had the Snia events, so we have some, uh, future events coming up as well as planning for SDC. Uh, and if you're looking to kind of connect with myself, as Jay mentioned, you can find me through Snea as well as I'm on, uh, former Twitter as SM Shaley and Blue Sky at SM Shaley as well, as well as LinkedIn. Feel free to, uh, drop a line and we'd be happy to talk.

Thank you very much. And as for me, you'll find me at s Foskett on most social media networks, uh, in yes, including the ex Twitter, as well as the Blue Sky and the Mastodon. And, uh, I would love to, to find y'all there.

Uh, you've of course can find me as well on, uh, the, the Utilizing Tech podcast, the Tech Field Day podcast, uh, Textron Gang, uh, every Tuesday, and the, uh, uh, tech Field Day rundown, uh, some Wednesdays when I don't relinquish the chair to my friends, Tom and Al. So thank you very much for listening to this episode of Utilizing Tech. You can find this podcast in your favorite podcast applications.

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