Techstrong TV – January 24, 2025

Hey everyone. I'm excited. We've got the trouble with Triples, or maybe it's software integration you're watching Textron Gang.

Hey guys, happy Friday. It's another week in 2025. It's, before you know it, it'll be June.

Uh, we're almost through January, but you know what? We've had an amazing text on gang month of January, not only because of our great gang members, but it's just been a crazy month with stuff going on here, right? How often do we invest $500 billion in Ether?

Um, but that was yesterday's show. If you missed it, catch it today. We've got the trouble with triples, as I mentioned.

Well, that's Star Trek. But there, there might be a trouble in Software Integration Town. We're going to hear about that.

We're going to hear about a couple of other things. But first, let me introduce you to our full House of Text Drunk Gang members today. Some of them sporting their gang color clothes and everything, and, and cups.

Um, first of all, we'll go, I think we'll go west to east. We'll start out in the west. And if you're gonna start in the west, you gotta start at the top, the king of of the valley there, Jon Swartz.

John, I see you're back home. It's good to see you. How are you?

Yes, It's good to be home. Hey, yesterday, very interesting thing. I was just gonna drop this in because I, I wanna write about this.

Eventually, I, I stopped by a, um, stealth AI safety risk assessment startup. They, they're, they're doing something that a lot of AI companies do. They're holed up in a house, so they're all living in the house together, putting together the company.

Sounds like a TV show. It does, does, I imagine like three or four members. Yeah.

Sounds like every Cool out a hype house Sounds like every startup I ever knew. So I don't know. But anyway, Well, uh, Benioff started Salesforce in an apartment, which is weird, but in any event, uh, this company, the reason why this company's interesting is that Eric Schmidt is in a sense, one of their advisors and one of the, the people who will be one of the executives there is, uh, help write the Biden's executive order that on AI guard guardrails that was just revoked by Trump.

So, uh, it was pretty interesting. They sent pretty interesting things to tell me about where they think this is going. And Fodders, can we, can we move along to the topics at Ham?

It's good to be with everybody. Alright, Well, moving right along then. Let's go, uh, to our next Silicon Valley resident there.

If John's the sa, she's the, I don't know, the Duchess of Silicon Valley. Lisa Martin. Hey, Lisa, how are you?

Good morning, Alan. Great to see you guys. We have a lot of integration things to talk about today.

I'm gonna weave that theme through all blocks. Absolutely. One of my favorite topics.

Moving next, I, I guess Colorado is further west than Texas, so, we'll, we'll, we'll, we'll stop high on the Rockies and, and say hello to Mitch Ashley Mitchell, it's good to see you. How's everything? Very good.

I'm looking forward to a very integrated conversation. Okay. There you go.

Okay. And then moving from Mitchell to Texas. It's our own Ann Anne Ahola Ward.

I think I almost got that right. Nailed it. Yeah, nailed it.

Okay. Thank you, Anne. It's good to have you here.

I you did you, you changed your New Year's. Is that Valentine's Day up there? It, well, it's Valentine's and birthday.

Yeah, it was my birthday, so It was your birthday. Oh, happy birthday. Why have so many flowers?

Thank Happy Birthday. Happy birthday. Happy birthday.

Thank you. Good for you. It's why I have flowers.

All right. And I figured why not get all the hearts out And, uh, you wanted to. Speaking of birthdays, it's our rum curmudgeon up in Harrison, chief Content Officer, Mike Baard.

Hey, Mike. How are you? I'm good, how are you?

I'm good. Not gonna say anything more. I want to jump right into things.

Um, all right. Our first, our first, uh, topic today. I mentioned it was the trouble with software integration.

Is there, we gotta shoot out at the Okay. Corral here. What, what's happening?

What, what's the problem, John, you wrote about this. I think. Let's, Yes.

Um, rum Intelligence did a report, um, by, uh, Keith Kirkpatrick. And, uh, they, In a sense, um, he kind of, in a sense, when we talked to each other, he, it was almost in a sense, like a 3D jigsaw puzzle being fit together between existing software and then integrating AI Intuit all the while under pressure from the C-Suite to do it as fast as possible. So we, we discussed this, um, it was, the survey was conducted in the fall of 2024, and it kind of offers us a snapshot in the choices customers face over the price and functionality of Gen AI and other AppSec while assuring management their prudent investments.

And I, and I think the reason why this is really interesting and very newsworthy is because there are so many choices these companies are gonna have to make based on all these ag agentic AI offerings from every consumable software company around. And it's going to be a lot of incredible pressure from Wall Street to show customers are making the right choices and integrating things in the right way, according to Keith. And, uh, some companies are considering consumption models as part of their strategy.

And I kind of would turn this to Mitch because he's the expert in this area. Um, it's probably not surprising, but I think there is a sense of urgency now that there hasn't been in, in quite a while. Well, and, and by the way, shout out to Keith Kirkpatrick, who, uh, is the practice lead for enterprise applications, colleagues of mine, colleague of mine at, uh, Futurum.

You know, it's interesting because the survey was back in, you know, end of last year, mid last year. And the pace, we all know the pace of how things are changing with AI agents and AI bots and AI interfaces, and everybody's using kind of their own people are sometimes buying it, or it comes with your Google or your, your Microsoft or your upgrade your subscription to it. And kind of as a former CIO the challenge in that situation is everybody has their favorites.

So they always want you to integrate their thing. And so you, you also have to be able to demonstrate, so if we spend all this money on Slack or on AI for whatever platform that we use, what's the benefit? What's the ROI and it, 'cause they aren't cheap, you know, you're talking about 10, $20 or more, $30 per user for these kind of capabilities.

We are seeing that now. I mean, if you take, there's a lot of kind of people talking about Google Agent Space as kinda having the lead. 'cause they really naturally have integrated into all the Google Workspace Suite and everybody needs to catch up with them.

I imagine in two months it'll be catch up with Microsoft or whoever. Um, so it is like a, it's like a, uh, a moving a 3D puzzle, moving at a hundred miles an hour. That's the problem we're trying to solve here.

Mitch. It seems to me at least that, I think 75% of the people said that they have an issue with this. And I assume the other 25% were lying or just clueless.

Um, integration's been a mess as long as I can remember. So how does this get any better ever? It it is, it is, it's one of the biggest jobs of IT organizations is integrating all these tools.

And that's why you see such a move to platforms, whether it's data platforms, development, DevOps, whatever kinds of platforms. And that, that's, I think that's the, the, the real race that's going on here is Google, Microsoft, and, uh, OpenAI trying to lock you into their ecosystem, right? Get you so invested in their capabilities.

Uh, you know, OpenAI is supposed to come out with the operator to be able to access information on your computer. Is that the right way to go? Or should we just, uh, we're a Microsoft shop.

We'll keep on the, uh, co-pilot plus path. So as a, as a CIO you're looking at this and say, how much am I gonna spend not just on the tools, but people to integrate and support all this stuff, especially when it's changing quickly. I think they're gonna pick their primary platform and probably ride that in most cases until things settle out a little bit more, which may make it harder for them to switch to anybody else down the road, frankly.

Alright. I, I think there's a, there's a subtle nuance here, and I didn't speak to Keith. You did John, between software integration and, and communication.

Yeah. I think we've made tremendous strides using APIs and Zaps and stuff like that over the last 10 years. Whatever, of one software being able to transfer data, send kickoff, some sort of action, you know, communicating and working together, right?

I think we've, we, we've cracked that nut to a large, large degree. Look, I mean the, the success of APIs talks to that, where that's the majority of traffic on the internet are APIs. Talking APIs.

Now if you are saying that's not integration, that's just communication, okay. That's a nuanced kind of discussion. And um, and then, so the question then begs what is true integration?

Is it you live on my platform and you no longer exist as a standalone piece of software? Is that integration? Because what about API and communication and and so forth, interoperability, is that not enough to be true integration?

Because if it is integration, I say bs, we got plenty of integration out there. You have a good point. 'cause APIs give you access.

They don't necessarily mean things are integrated. Think about, oh, copilot might be integrated into all the tools that you use in the, in the ui. It's just part of it, it isn't sitting up there as a, you know, clippy thing that's gonna bother you or another window or screen.

So, and it and APIs, Alan, are, are central to AI agents being able to talk to other traditional systems as well as between agents. So it's part of the fabric of it. But to your point, integration isn't just connecting the dots between different applications and systems.

It gives access. But that may be all. There's also a difference between an API and what people call a connector, right?

Which is a more polished version of something that I can invoke that is not a, you know, just raw bits. 'cause I think just exposing an API doesn't do a whole lot for most people who are trying to integrate something, Then you have to build it, right? Mm-hmm.

And Maintain, I think if we look at it from, oh, sorry. Go ahead. Go ahead, Lisa.

I, the, I was gonna say, I think if we look at it from a customer perspective, I look at IT marketing. I do a lot of work with boomie integration platform as a service. I see a lot of their events and we look at it from a customer centric point of view.

And customers just expect all of the data that companies have around them is going to not be siloed. It's going to be integrated, it's going to be accessible. You think about all of the different SaaS applications that vendors have and the number of AppSec that people have open at any one time.

We expect these seamless business processes. We expect data to be available so that companies can truly be data companies to deliver value to the customer. And the customer doesn't care.

They just wanna make sure that what, what data a company has on them is, is just, that is integrated so that the business processes that concern that customer are delivered and the value is proved. John did, did, uh, in speaking to the analyst, what was there this distinction between APIs and true integration? There?

There was, um, ke one of the things that Keith pointed out in the, that year, the survey that was, that was interesting, something I should have been mentioned earlier. It's just, we, we talk about the, the applications that have been deployed, I think, was it one fifth of the respondents? So they deploy more than 11.

And I think there was one other thing that more than half of those that their application technology stack blended application developed in-house. Um, it's just, I, you know, Alan, I just like this, this kind of sense of frustration and we always, we see this undercurrent in a lot of the stories and segments we talk about just the, the pressure down permeates in the middle, and then these decisions that have to be made. Um, it's, it's not gonna get easier, basically.

No, I, I don't think it is. Alright. If we have nothing else on this, let's jump, uh, take a quick break and we'll jump into our B block here, which is, uh, the future of product development in the age of AI or Aquarius, or is that the fifth dimension?

I don't remember. com is the leading resource for news analysis and education on challenges facing the cybersecurity industry. com covers all aspects of cybersecurity, including data security, DevSecOps, cloud security, application security, network security, security threats, and more.

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Home of security bloggers network. All right, folks, we're back in Talend's point. Yeah.

We're gonna talk a little bit about AI and product development and marketing and where all that data's going. And I know this is in Lisa's sweet spot, but there's a story on digital CXL talking about this issue, and it feels like maybe we're getting a little more data driven in our product development, but I gotta wonder like, well, where does that spark of ingenuity start to show up if we're keep using the same old data? So, Lisa, how, what's going on here?

How do we strike a balance? Great question, Mike. This is such an interesting topic to me because as long as I've been in marketing, which is almost 20 years now, which I can't believe product managers have, and I, I, and I was a product marketing manager for many years, working very closely with PMs.

They've been tasked at really guiding the strategic direction of our product. They have to balance what the customers want, what the business wants, what's technologically feasible. And historically they've done that by customer advisory boards, customer feedback, which is still incredibly important, but also market research, competitive analysis.

And now with the data science as a foundation, they're able to use machine learning, predictive analytics to make truly data-driven decisions and things like, um, predicting feature user behavior. How are users interacting with our products? How do we prioritize one feature over the other?

And so the role of PMs is changing, I think, for the better. And there's a lot of alignment or integration, I'll say with marketing, because what we expect is to have all of this telemetry on how customers are interacting with their products to be able to make informed decisions in a timely fashion, almost in real time, so that the, the vendor is competitive. There's a number of alignments, I'll say integration as well, just to be cheeky with data science PM and marketing that I really thought was great in this article.

And the first one is user segmentation. It's incredibly important to understand where users are based on their behavior, how are they interacting with product features. This helps PMs develop personas.

And then marketing can take the development of personas and the buyer's journey per persona to the next level and facilitate that buyer's journey and understand what content do you use, what do they want to see at certain stages of that journey to get them qualified into a salesperson. Also, AB testing is a great alignment where data science is great for PMs as well as marketing. That's been around for a long time.

As I said, I've been in the industry for 20 years and ad testing is nothing new. And it's not, but it's a staple of product management. It's a staple of product marketing, and it really can kind of take the user segmentation that we just talked about to the next level.

Machine learning and algorithms can help not just determine which feature is performing better, as I mentioned, but also how were those different user segments that they determined and that they've identified how are they interacting with the technology. And the third one is churn prediction. It's definitely more cost effective to market to and retain customers than it is to attract new customers.

Every organization has percentages of both, especially from a marketing standpoint, but it's really important to understand from a PM standpoint and a marketing standpoint, who's churning, who's likely to churn, why, what is it that we can do feature-wise? So we'll start reducing and dialing down that churn. Maybe it's introducing new engagement models or customer support.

So data science as a foundation for product management in alignment with marketing goes a long way to, to really helping companies become and delivering what customers want, which is that lifetime value. Excellent. Excellent.

You know, what about digital twinning, right? For product? I, I, I just, it came to me while I was listening.

Ke you, Lisa, I've been doing a lot of interviews lately with some companies that, some big companies, I think Siemens, for instance, right, has created this whole digital twin sort of platform where you can take your physical product, a boat eventually, and you create a digital twin of it and see how it'll react in different sort of weather conditions or sea conditions. For instance, I, I wonder if we haven't thought about digital twinning products into some sort of, you know, virtual environment and, and that's A great idea To see what they, I think for Security. Yeah, that would be amazing To see, oh, that would be great for, for security, right?

Because you could set up your whole environment, drop this in there, and mm-hmm. And, and play it out. I think we've seen people doing that, especially like on high-end products, whether it's, for example, an aircraft engine or something like that, where there's millions of dollars.

But I'm not quite clear that digital twinning has gotten cheap enough for everybody to go use for product Develop. See, I, I, I think it has, I think it, it, it may not be cheap enough for, you know, a lower level software product, but I, I think the technology for digital twinning and creating that virtual environment to play in sandbox, if you will, I think someone already took that name. Um, but I think I, I think it's, it's cheaper than ever.

It's cheaper than ever and every day it's getting cheaper with, with AI and, and machine learning and stuff like this. Well, not to make AI agents the solution to everything, but if you dig down into kind of what, what are AI agents and what are the different types and kinds and, um, actually have a, a brief coming out soon. I'll plug it when it, when it comes out.

But if you look at it, you know, there are, there are AI agents that are reactive to triggers and things happening in the environment, like an image or a light source changing. There's also goal oriented, there's utility oriented. Um, they're learning agents, which would be something that might enhance or maybe even replace what a digital twin knows.

And then there's hybrids of these, and of course multi-agent from, from the same or different providers. So I think, Alan, you know what intrigued me about your comment too is that AI agents could potentially be part of that digital twin, whether it's technically representing it that way or it's just rep representing it through the data that it gathers and the inferences that it makes. So, you know, when I, instead of just presenting us with information for here's the flights and hotel availability and book, all that, but take into account my calendar and my workload, what's kind of pending for to potential invites, the travel time, my preferences, personalize all of that for me, um, and then deal with all the changes that happen in my environment instead of me dealing with all that information and, and taking action on it.

I love it. I mean, I'll, I'll tell you something. I, uh, I was planning a trip and I went into, I, I, one of the ais, I, I use a, I use a lot of the different ais that I'd like to see the differences.

And I said, gimme a three day itinerary to go, or four day itinerary to go here and there. And it laid out a beautiful itinerary better than anything I would get from Froms or something like that. And, you know, I, I just, for, just because I'm crazy like this, I said, okay, go make my reservations at these restaurants and pull up the flights and, you know, let's book them.

And, you know, the AI very politely told me, you know, Jack off, he said, we, we, we don't, we don't do that. We don't do that. I Don't have that feature on my Ai, that's not my job.

That's not my job. Um, but I thought to myself, wouldn't it be great if it was, you know, and I mean, tell me, Mitch, tell me you're the AI agent, man. Um, are we, am I gonna be able to do that soon because that would, that, that would put the cherry on my Sunday, right?

I, I think that's, to me, one of the potentials, the real value of AI agents is not presenting us with more information, which, which what, what AI did for you, right? It gave you really good itinerary, which is super, that's very valuable. And to your point, the need is, well, I don't wanna, now how do I execute on that There 12 things in there, go do 'em.

Yeah, exactly. I want you to do those things for me. And that's gonna take AI agents talking to others, both AI agents, but also traditional systems back in, Back to the software integration problems, Services making the payment.

Exactly. Back to the integration. So, um, you know, when Satya Nadal said that, uh, SaaS is gone, it's all gonna be agents.

I think it's a hybrid world where we see agents talking to traditional services and systems, APIs, et cetera, to accomplish it. That that's the world I wanna live in, where you can say, make it so it would be Captain Picard If you do that. You gotta go like that.

Which one you say it Make it. So, And let me ask you something about all this. Do you think that the pace at which products are rolled out and updated is gonna accelerate as a result of all of this?

And we might have a new product launch every three months, or will it go the other way where we're just adding new features to everything constantly and there isn't such a thing as a product launch because, well, there was the first launch and now everything's just an update. I definitely think the features, I think features are a lower lift. I think features have a quicker opportunity for revenue.

They're, you know, taking advantage of money already have coming in. You add a little bit more to that income stream versus trying to go get a new one. Um, and I think it's less jarring.

I think whatever, whatever is the easiest way to take the money is the way it's gonna happen. And yeah, and the way, the way that this works is if you slowly stack it up, right? Like, we watch these services slowly add little features, and then they hike up the price and it's $2, $3 at a time.

And, and so I think that's probably what we're gonna see. Um, especially, I think You're already seeing it. Oh yeah, absolutely.

I think it's gonna get more subtle and the prices are, the increments will get smaller, but the the, it's gonna happen. The prices will go up. I Mean, look, look, not to segue into our next block and talk about phones, but for most of the world, even for most of us in the tech industry, our biggest, the, the applications we interact with the most live on our phones.

I, I don't know about you, but I, I think I have over a hundred AppSec on my phone. I'm, I'm crazy Easily, But I've got over a hundred AppSec on my phone. Every single one of those AppSec is being updated, if not daily, at least weekly.

I think I, we don't pay attention. We've become numb. And I don't know if that's a good thing, but we've become numb to the constant continuous update.

And I couldn't tell you what version of this app that I'm running, surprisingly, I can't tell you what version of iOS, for instance I'm running or what version of Mac Os or, but even Windows, right? I mean, it used to be a big deal when, when Windows would upgrade from, you know, windows 95 to 98 to Emmy or whatever, you know, and we have Windows 10 and Windows 11, but think about all the incremental upgrades that take place in Windows or, or your Mac or your phone, whether it's Android or whatever. We don't even pay attention to them.

We're desensitized to it. That, To Anne's point, that's what happened with Apple and Intelligence, right? Yeah.

It wasn't a big OS Drop, not at all, Right? Incrementally. And that got added, and we're still seeing new features roll out in small, Small release, right?

Not since the launch of OS 10 has, apple had something that dramatic and that different, that caught everybody's hearts and minds, But you had to sign up for a beta to use it, right? How many, I'm still on the beta cycles and I still don't necessarily know how great this Apple intelligence is to tell you the truth, other than the little thing that makes cartoon pictures, um, you know, and you get those pretty neon light around it. I'm, I'm not a hundred percent sure I'm, I'm, I'm buying it, but that we'll save that for the next block.

We'll save it for the next block. Anything else on, on, uh, product development though? In, in the AI world?

I'm, I think that, um, sorry, go ahead. Go ahead, Mitch. Okay.

No, no, no. I was gonna say from a, from a kind of customer perspective, there's some, this article had some great examples of Airbnb and Amazon, and I always kind of default to Amazon. I don't do a lot of Airbnb myself, but there's so much data that's collected, and we have this expectation in our consumer lives that bleeds in, and I talk about this all the time to where business lags, where things like Amazon are gonna use AI to make predictions based on past behaviors we've done in a non-creepy way.

There's a line there, maybe it's dotted, but we have that expectation that the experience will be seamless. They're going to, they're going to serve me up relevant information so I can make a buying decision because the better the customer experience and PM and marketing have a lot to do with that, the more sales go up, the more revenue comes into economy. So I think the integration p the data science piece, foundationally, is really critical for that customer experience delivering the value that customers ultimately expect.

So let me give you, let me give you an Amazon gone wrong real life story on that, Lisa. So I, I have, I have the big 15 inch Alexa screen in our kitchen that I use as like a, a digital center from my home. And if you guys have all used Alexa, you know, and you get a notification from Amazon, it blinks yellow or you get a yellow light around it.

I don't know how much you guys use it, but I get a notification. I said, hello Alexa, what's my notification? Hello, Alan.

Good afternoon, Alan. A product you're following has been reduced $3. I said, what product Alexa?

Well, it's the, I don't know, the Dough Waer, cat bed, rabbit hutch, cat tree. They started giving me all these products. I don't have rabbits, I don't have cats.

I don't know where the hell it got it from. Oh, so I, I, I said, Alexa, I'm not interested in this. Please take it off my, my list.

Oh, would you like to me to add this to your list? I said, no, take it off my list. So AI gone wrong.

I bought a dog bed one time a year ago, and now it's trying to gimme every animal hutch in bed that they've got over there. Guess the lesson is don't doom cra don't doom cra rabbits. No.

Well, I I'm trying to take it off. It won't let me take it off. Yeah.

And It won't. Interesting. That is a good example of AI gone wrong.

I don't have an Alexa because like, I have Siri and that's enough. It's listening. I have a dog named Claire, but I call her cl Siri pops up probably we'll do it right now.

Um, but so I don't have the Alexa experience and so I'm, I'm old fashioned Alan, where I'm on the Amazon website or I'm on the app and I have good experiences where surfing up relevant information. But you make up a good point is where is it getting that information that's surfing you up wrong, irrelevant content. That's a question mark.

You, but don't assume that it was you that did it. Anyone that shared a computer or you know, a phone that was near your phone and your GPSs were turned on, your phones are talking. So someone close to you geographically on their phone could have bought it.

Someone could have used a shared computer. If you and your spouse share a login, don't assume that it was you that did it because your data's getting creeped from all. Well, I'm going home and asking Bonnie if she's been searching for Rabbit hutches, That's all.

You might be getting a new rabbit. Maybe We're getting, just wanna think Happy birthday Rabbit. Don't die Alexa 20 times.

'cause I don't know what I'm gonna show up on my Alexa now. It's, it, It's getting crazy. I'll tell you, I was, we have this attic and there's a ladder that goes up in the attic and I had it down the other day and sure enough, an email pops up asking me, you know, am I interested in these awesome new attic ladders?

And I'm like, I didn't even talk about it. I didn't mention it in some sort of video. Captured something somewhere.

And it was just kind of weird. Wow. Yep, yep.

That's crazy. It is. Again, it didn't have to be you, it didn't have to be your phone, your, your spouse's phone, a friend's phone, someone in the vicinity, your neighbor that was your phone was near their phone.

They're, they're having a conversation whether you realize it or not. Scary world. It's a scary world.

Well, alright, let's take a break here on Textron Gang. 'cause we're overtime on this block. We're gonna stay on that phone theme.

Coming back at you though. You're watching Textron Gang. All right.

As we were talking about earlier, yeah, this whole Samsung versus Apple thing continues to play out. The latest is the fight over ai and Samsung has a new phone out there talking about how it can access external LLMs and, and have Bixby on your phone. And whether these two things are actually talking to each other is a mystery to me.

But Anne, what is your take on what's going on here with Samsung Apple ai? It seems like, you know, it, it, it's a boxing match. Oh, absolutely it is.

I mean, these are two players competing on a level that most can't and don't, um, I should say that I am X apple. This is the only big company I ever worked for, and Samsung has been my client for almost a decade and, and has been very good to me. So I have love for both companies.

So I say this from a place of love. I do think Samsung's phones are absolutely more innovative. I will say that because I am an Android user through and through, I've used Android phones, um, as a majority phone for a long time because of the amount of control power it gets.

These s 25 series, galaxy phones have a boost of, of AI features that I think have been unseen as of yet because they have cross app experiences and integration with GI or I'm sorry, Gemini, Google's ai, uh, to perform tasks across multiple AppSec. So I think we're gonna see sort of more active assistance coming from these phones, especially for things like calendar events, sort of more like an actual assistant, which we haven't really seen from these phones yet. Um, they also have improvements to existing features like the gallery AppSec circle to search, sort of the, the things we've seen on Google Pixel phones and other things.

It's, it's catching it up, but it has the new Qualcomm Snapdragon eight, uh, chip set. And so from a hardware perspective is gonna be tough to beat. Um, I would say if you're looking at sort of the core features, when you're looking at an Apple phone, you're using Chachi BT as your third party AI integrator, right?

And now with Galaxy, you are looking at Google, so it's not really truly Samsung versus Apple as much as it is Chachi, BT or Samsung, sorry, versus Chachi, BT, and Google. I mean, it's, it's, it's the alliances within, uh, these two that I think makes it really interesting. So I think making a choice as a consumer, if you value privacy integration and a subtle sort of AI experience where it's not so much in your face, apple is your best choice, I think Galaxy makes sense.

If you want more features cross crossing between AppSec, uh, multiple devices, live translation, um, and you don't mind the AI feeling and presence and watching it and having it feel a part of your experience, I think, uh, galaxy AI is definitely your your choice. Yeah. This, this, this is interesting.

I remember when the, when Samsung or Apple used to make an announcement, it always was hardware heavy. Now we're seeing beginning last year with Samsung, now the sign is the smartphone makers are, are leaning on AI to make their phones stand out. I think Galaxy AI last year was the big focus, and, and I think now, but instead of focusing on individual AI powered features like generative edits, uh, Samsung's incorporating AI into its phones on a more fundamental level.

And in a sense, you know, as part of the settings and, um, it, it, it's interesting because in a sense, uh, this stands out and, and when you compare it with Apple, um, apple is kind of slowly rolling this out and there is a genuine concern, not just on Wall Street, but in, I think within Apple, the stocks get been hammered lately among concerns about iPhone sales tapering off. And there's a lot of attention being set on what impact, if any, apple intelligence will have. I I don't think it will immediately.

I think it's gonna happen probably later in the year as more of these features become available, but it is part of the story and for years and, and knows as, as well as anybody, Samsung was in a weird way chasing Apple or dueling for the top spot in smartphone sales rarely got the buzz that Apple did, even though it's feature sets were better probably. And, um, now it's in a sense kind of leapfrog apple and it will be interesting to see what Apple does when it rolls out the new AI features and what impact they might have at all. What I, yes, you're absolutely right.

I think Samsung has gotten less, uh, fanfare. I think they've gotten less media attention or they are quietly making these beautiful screens beautiful products. I think they both make beautiful products, but I do think Samsung has been short shifted in the press.

I do also think that, you know, when it comes down to it, someone's getting the bill, someone always gets the bill, right? So who's getting the bill for this new intelligence that we know they're spending billions building? I think Apple is gonna do probably a freemium model.

They're gonna have paid tiers because that's what they do. Ai, I think we're gonna see free access. I, I think for now at least.

And so that's gonna be something consumers will notice. But again, how are they gonna monetize all of this? I think right now we're in the wild, wild west, let's get 'em hooked sort of phase.

But eventually I think you're gonna expect to see subscription costs for this, and it will be, you know, something you're expected to pay for, not just the hardware of the phone or the service with your provider. You can, that will change. Oh, Go ahead.

Sorry Mike, go ahead. Do you have a sense whether people actually switch phones when these announcements come? Or are we all like Apple people and Samsung people and we're just along for the ride?

Most People are zes. I, I would say there's such a thing as digital tribalism, and I have been berated for being a primary Android user. I will tell you, I secretly also use my secret phone as an iPhone, and that's just so I can stay up on all features.

And when startups come to me a lot of the time, they don't have an Android app yet. So I have to have both and I have to be fluent in both. But I prefer Android and I get so much grief for that from Apple people.

'cause they're like, your text, you're green, you can't do this thing. And it's like, why do you care what color my text is? But it's a very real thing where, where the more you get locked into Apple, and the reason I use a Mac, I have an iPad, the reason that I don't use a primary Apple phone is that I can't give them everything and I won't give them everything.

I won't give one company everything because once you're in, you can't get out. Once all your stuff's in iCloud, you can't get out and I just can't let 'em have it. Lisa, You wanna add to that?

I was just gonna ask Anna a question and, and, and you, but you really answered it. Like from a, from a a cost perspective, as you know, if, if the Apple model, like you talked about is becomes subscription to use more AI features and it's baked into Samsung, how likely are from a customer behavior perspective, is that likely to influence? I don't, I think you bring up a great point.

We're so locked in. I'm Apple everything, even Apple tv. Um, I wouldn't switch.

I know how to use this. I know how to operate it. Um, and I think even though it's, it's an arms race right?

Feature for not, not really feature for feature, but the Apple folks are gonna remain. The Apple folks, the Samsung folks are gonna remain, remain the Samsung folks. And I think we're gonna continue to see that jockeying for market share globally because I I just think consumers are, once behavior is set, it's really hard to change it.

Absolutely. I think the only thing I see changing it is the cost of hardware because iPhones have gotten exorbitant. Um, yes.

And and I think that that is something that, uh, younger people are maybe less concerned about. Um, so, but people Don't feel the cost, people don't feel the cost of the phones because it's wrapped into your, your carrier subscription often, right? If you upgrade you line sign on two years, they, they don't know the difference.

But, but here's, here's my take. I can't wait to see this year's WrestleMania and these two heavyweights go at it in a, in a, a cage, a cage death match. Here, here's the facts.

At the end of the day, in this corner, you've got Apple OpenAI and Microsoft, and in this corner you've got Samsung and Google, right? And, and it's funny, it's the same fight over that we saw in the PC wars and the browser wars and you know, is the Qualcomm series eight Snapdragon as good as, what's the new iPhone 16? Is it the A 20, the a 18 whatever it optimized for ai, right?

This at every step of the way here, the these two get it go at it. What's interesting is because it's Google though, you do have an integrated suite of, of pro of, you know, work products, right? Google, whatever they call it workspace that is now integrating that AI that integrates right into the phone system, where on the other side you have OpenAI, which is not really part of Microsoft, but sort of part of Microsoft, not really part of Apple, but sort of part of Apple.

Hey, if we had a real, you know, FTC that was looking at monopolistic practices, I think Google's in trouble, frankly. But that, that being said, I don't know if they're ever gonna be able to charge this for these things because I'm telling you, it's going to be table stakes. It's gonna be table stakes.

Well, They're gonna charge, I guarantee you they may hide it, but they will have to, somebody's gonna always get the bill for all of this r and d all of the expense of maintaining this infrastructure that is needed. Whoever's coming up with the 500 billion will pay this too. We missed you on that stigma, Alan.

Oh, I, well, let me, all right. I'm glad you said that because let me bring it up. If you didn't catch it yesterday, I started a new LinkedIn live little video series called Shimmy Says, and I talked about this on Shimmy says, I thought so though.

It's not live. You can go get it on LinkedIn, it'll probably be on YouTube shorts and you and, uh, TikTok, if we're still allowed to do TikTok, uh, TikTok is, well, it's Shimmy says, and I, I spoke about the, this, this 500 billion, that's Stargate. I I've got Stargate in my, in my brain.

Yeah, it was, that was, I loved all of the Stargate iterations, but, um, anyway, yes, someone's paying for it. So look, those tech bros didn't invest all that money for nothing, that's for sure. Yep.

Good Point. Um, do we have anything else, Mr. Ard?

No. Uh, well I Just wanted to show of hands, like, so who is Apple on this particular group Here and I, I used to be an Apple hater. I'm, I'm my half hand, but I'm raising a half hand because I do technically have an nice, well, it's Only your secret phone.

I wonder what people do with a secret phone. You said that. I'm Thinking Oh, all kinds of stuff.

I Don't know. Look, this is a family show. There's a family show.

We may not want to share it. Oh no, I, I will say I have very, I, I handle sensitive information for my clients, so I'm not gonna put anything Facebook on the same phone. That handle really handles my work.

Yeah, absolutely. Good for you. I didn't realize the level of paranoia had reached that.

Hi, but that's pretty cool. Maybe Apple would, I think Anno, I say caution. Yeah, So that, so that makes me the only, that makes me the only Samsung person on this, this.

Well, No, and I just recently got a Google, I, I've been Samsung up until this last phone. I I tried the Google Pixel 'cause I figured, ah, my whole life's Google anyway. Why don't I just see what we, whatever.

I will never get another one. I'm glad, like Lisa, I have Apple tv, I've got my watch, my phone, my Mac, my iPads. The, The only thing I, the only thing I'm ever really jealous of on the Apple side is that yeah, Siri is a much better experience than Bixby ever will be.

And Bixby is just Not Bixby Is Bixby is the Google Siri going Away Version Of way though going away? Yeah. Yeah.

In the, in the new phone. Uh, it's Ai, which is gonna be based on Gemini. Well, wait, No, they still chance.

They still have both. They hire and you're supposed to figure out which one to use. And Bixby iss an idiot.

So I don't know. Yeah, But they say Bick, uh, over time Google is gonna replace what Bixby does. So eventually it, it's probably gonna be gone.

John, you wanted to say something? Oh, no, no. I, I, I like tried Google Pixel.

Actually, you know, the weird thing is I can't use a Macintosh or an I an iPad or, or desktop is completely pc. I will, I just refuse to go back 'cause it's so counterintuitive to me. I used to write for Apple Trade Magazine and so the phone is just, oh, hello.

The phone is just, you know, that I, I'll always stick with it. Hmm. Go figure.

Anyway, biased, we will see how this plays out. I think. Thanks for Joining our consumer focus group here on Textron Gang.

You Know what, maybe we could do this for the, for product development. We could be a focus group. We're Available, right?

Four, we're available. We're the digital twins. Okay.

Um, hey, this is a great Textron gang. We've got a full day of Friday Textron tv following it, do check out. My shimmy says Show.

I'm interested to hear what you say. And next Thursday at two 30, you can join me live on LinkedIn if you want to participate in that. Um, but until then, have a great weekend, everyone enjoy it.

I hope it's warmer or it's safer wherever you are and, um, or colder I guess depending where you are. But, um, we'll be back Monday with more texture on Gang. More fun.

Until then, is Alan Shimel for Techstrong Wear Out. This is Textron tv. Hey everyone, it's Alan Shimel.

We're back here at techron tv. Our next guest is Scott Deon. Scott is the CEO of a company called Augment Code.

We're gonna find out all about Augment code, but let's find out first all about Scott. Hey Scott, welcome to Tech Drunk tv. It's great to have you on here, Alan.

Thank you for having me. So, uh, The pleasure. Uh, prior to running, uh, augment code, I've actually had an interesting journey.

I did a PhD in machine learning a very long time ago, uh, when the technology was about symbolic reasoning rather than neural nets. Uh, but I, you know, I got mm-hmm. Inspired by, uh, Jeff Hinton, who was one of my early AI professors.

Been following his Yep. Been following his career and his large language models emerged. Um, I, I saw this opportunity, uh, to maybe reduce some of the pain that I'd seen, you know, so, uh, multi-decade career of doing really hard system software at places like Pure Storage, uh, web Logic BEA systems, uh, and, you know, was always daunted by how hard it was to crack open a broad, a really complex, large repo and make changes to it, uh, and felt AI could help us do a lot better at maintaining these really large, hard software projects.

That's amazing. That's really cool. Matt.

I, I, you know, I know you're not supposed to ask age and all of that stuff, but gimme an idea. When did you get your PhD in ml? Uh, early nineties.

Wow. Wow. So, gen ai, a GI, all these things were not even on the radar at that point, right?

Uh, it was very much about logic and symbolic reasoning. Uh, in fact, um, people like Jeff Hinton took grief from the symbolic reasoning powers that be, 'cause the, you know, they said, oh, if, you know, if you ever get those little toy neural networks working, we'll go in and find the symbols, uh, for you. Uh, and, and so, I mean, he had the, uh, wherewithal to stick to that research agenda for 30 years until the technology, um, and the performance caught up, caught up, caught up with what, um, you could accomplish.

And so, uh, I appreciate that persistence. I do. I think we all do.

We all do, right? In, in retrospect, um, you know, it's, it, it could wind up being, uh, kind of the, the, the, the project of the century, or at least the early part, the first quarter of this century, right? Uh, um, excellent stuff, Scott.

So, you know, I I've interviewed so many founders and CEOs over the years and, and the successful ones always have a passion for the mission. What they're doing now, obviously times like, uh, AI and this kinda stuff has been a passion of yours for 35 plus years. So, but I mean, it's ama I'm married 35 years, so I I can appreciate the, the, the distance there, you know, um, that's a long time to be passionate.

What about Augment Code's? Mission kind of gets your juices flowing. I'd love to, or where we should define what is the mission, you know, maybe go there.

Well, let, let me, let me start with a passion and then I'll hit the mission. Um, you know, okay. I loved programming when I, you know, when I got to do it.

And when, um, I first started in the industry and experienced software engineering at scale, I was struck. I was working with people that were better coders than I was. Um, but the job wasn't fun.

It was really harp. Uh, and it was, you know, um, as you, you get, um, many engineers trying to work on a multi-decade, uh, or at least, uh, you know, a significant scale, tens of millions of lines of code, um, uh, and it becomes really unwieldy. It can be fragile, um, extremely complex to understand what's going on, uh, require a tremendous amount of coordination, uh, to get those changes, right?

Um, and so as large language models emerged, it was like, wow, is there a way to attack this complexity? And the products that were in the market, uh, in those days, like the early, uh, GitHub copilot, for example, um, struck me as much more targeting simple programming than software engineering, where you're really trying to, uh, deal with a large, complicated piece of, of software. So that's what we wanted to go after.

We wanted to, um, bring, uh, the full power of understanding of your code base, uh, to bear with ai. Uh, when you get started with most of these coding ais, they're like a new college grad, which I once was a long time ago, uh, where, you know a little bit about programming languages and algorithms, but you don't understand the software that you're trying to work on in the environment in which it runs. That's augments differentiation is that we come in with comprehensive knowledge of your software, uh, without ever training on your coat.

Love it Again. You know, this is a, a mission a, uh, a company that couldn't exist until, until it was, the technology was there to support it, right? The, the, the horsepower and, and everything else.

Um, tell us a little more about augment code. I mean, you're the CEO, but how big, and don't, again, I'm not asking you to say anything, not kind of public, but you know, who's the customer base. Tell us a little bit more about the company.

Yeah, so, um, we only launched the product, uh, you know, within the last, uh, six, six months or so. Um, it's now available for anyone, uh, to use free of charge. Um, and, uh, it, it really impresses people pretty quickly, uh, in terms of, you know, giving them knowledge of what's happening inside their software.

So, for example, one of our customers Lemonade, uh, they've got, you know, uh, north of 10 million lines in a mono repo. Uh, and, you know, they're constantly moving engineers around that project, uh, bringing new engineers on board, uh, and augment helps them orient into the, into this new code base for them, or new area of the code base really quickly, uh, so they can come up to speed without having to put a load on the, on the senior, uh, employees. Uh, another, uh, company, uh, COUM that uses us, uh, they do migrations, uh, on upgrading of e-commerce AppSec.

So they're constantly jumping into new code bases and needing, uh, to find their way around in order to make changes, uh, that, you know, they're getting an order, uh, 50% acceleration, uh, for their workflows because of all this knowledge augment brink. So, you know, even though we're new, we've got hundreds of, uh, companies now using the product mostly in the tech industry, software and intensive companies, and, and once you try an AI that understands your software and its environment, you never want to go back. So they say, um, that sounds great.

Um, what's the plan to commercialize here? Well, uh, you know, the, I I think the game is changing around AI for software. You know, the, the, as I said, the earlier ais are novice, uh, now everyone wants that contextual knowledge.

Um, and, uh, we're in a unique position to be able to deliver it. I, I think the hope is that we can pay down a huge amount of, uh, software debt. You know, if you look at, uh, just the United States market alone, we lost, uh, two and a half trillion dollars, uh, last year due to software failures.

I mean, there's not a piece of software I've ever encountered that doesn't have a long list of features, nice to have, as well as refactoring and tech debt that people would like to fix and change. Now, I see this opportunity with, um, ais that understand your software, like augment, uh, that we can deliver the software of everyone's dreams. We can make it more reliable, easier to use, uh, secure, more fault tolerant.

I think all of these things can come out of, um, these much more proficient ais, like the one that augment is delivering. Hmm. You know, I'm trying to remind them, I was trying to think.

There was a testing company, I, Gil Sw was the founder, CEO, and I'm blanking on the name, but they used to test, but they'd look at a website and tell you how a person would see it, you know, based a person not seeing a real person, didn't see it mind you, but they would tell you what a person would see, right? It was like optical something testing kind of reminds me of that, right? Where without a real cumin being in there, the AI is, is telling you what the human experience would be, so to speak.

And, you know, and that's an amazing thing if we could do that at scale, you know, when we're talking large scale. Um, and that's one way, you know, that it's one way where we're seeing AI kind of change the game. Yeah.

But a, a great way to think about this is, you know, humans are really good at thinking over the long term about what they'd like to see in a piece of software, right? Do I wanna change to a microservices architecture? Do I wanna move this application to the public cloud?

Um, what, you know, is there a mobile interface that I wanna develop, uh, for it? Um, what we're less good at is all of the incremental, uh, uh, steps that need to happen in order to accommodate those changes. You know, especially in a large repository, you know, even a simple, there's no simple change in a large repository, right?

You wanna add a field to a data structure, tructure. I mean, you, you, you, if that data structure is persisted, you've gotta update, uh, the database schema. You've gotta, um, change any of the command line or other APIs that use it.

Um, so AI can really help. Like, if you open up augment code and you make that change, it will offer to pull that change through an entire large repository, potentially touching dozens of different files, um, and guiding you through that process. And if you get interrupted in the middle of it, you don't have to go back and struggle to try to remember where you were, because the AI will help you pick up right where you left off.

Yeah, absolutely. It, it, it's, it's a wonderful thing. You know, we were talking, uh, on our Techron gang show last week that, you know, they, they say there's about 27 million developers in the world today, software engineers.

You want to say, no, there's 30 million, all right, I'll give you 30 million. You want, tell me this, 25 million. I'm not gonna argue with you, but somewhere in that range As a result of using ai, they say, look, by 2030, we may have a half a billion people who are, I don't know if you really wanna call 'em software engineers, but, but they're asking AI to develop code for them.

So the amount of code that's out there that's going to be out there, you know, you're talking about exponentially more code and AppSec and stuff floating out there that really to the point where I don't think humans wrap their heads around it. It's like trying to say, oh, that's 30 million light years away and this is 40 million light years away. What's 10 million light years to a human?

Right. Uh, same thing with the, just the sheer amount of code that's gonna be generated by these AI and everything that really only another AI is gonna be able to sort of wrap their head around, you know, speaking that way. Kinda wrap their head around it and, and make, you know, heads and tails of it all.

Yeah. I would say, uh, two things here. One of the challenges with the, with this, these novice ais that I was mentioning earlier, is because they don't understand your code base, they're really happy to add new coat.

Like if we were building something together and you had added something last week, um, if I start trying to add the same thing, most AI will be like, oh yeah, well, sure, let's add, you know, yet another class into the system. What augment will try to do is say, Hey, why don't you reuse, uh, the code that Alan wrote last week, rather than try to add new code? Let's adapt and reuse rather than proliferate code, uh, inside a repository.

And one of the most exciting things I've seen is when, uh, augment wanted to delete code rather than add code into a repository, because that's how we can get to higher software quality. Um, and, and so most repositories, I hope, can shrink as we make them better and more secure and remove dead code. But I think you are right that, um, you know, the barriers to delivering software are, are getting reduced and the economic returns that can come from having all of the software that people want, software that can do any different task, uh, that we imagine, uh, I think that can unleash a lot of human productivity and, and wealth and make many more of us, uh, able to, uh, create, uh, the software of our dreams.

Agreed. Agreed. You wrote a blog article a little bit ago, Scott, about, you know, this kind of the, the impact this is gonna have.

com or what's, what's the URL? com. And so they could get the blog from there, I assume?

Uh, yes, absolutely. It's, uh, on the top nav on the side. Excellent.

Tell us a little bit about maybe this blog post and some of the concepts there. You know, so we've hit some of them already, right? That I, we really wanted to tackle the discipline of software engineering rather than just, uh, toy programming.

Uh, and that, you know, real software, you know, complicated software lives a long time, uh, you know, and it comes with documentation and, and testing and, um, you know, a lot of the development happens outside of, uh, integrated development environments. You know, um, engineers use, uh, tools like Slack often to communicate, you know, it's augment, uh, slack can or augment, can join a Slack conversation. So if you're having a debate about how a piece of code is supposed to work, um, you can invite, augment, uh, into the Slack conversation.

It will render a verdict, and you can even assign a pull request right out of, uh, slack, uh, to, to augment, uh, and have work done. And so there's this opportunity to go beyond, um, just the development environment, uh, and, and tackle kind of wherever software engineering lives. Um, another thing that, uh, people often find is, you know, that, that the documentation is inconsistent, uh, with a software or somebody is coding something outside of security policies, um, uh, inside of a code base.

Augment could pick that up. Like we can identify when documentation is not current, uh, incorrect, when there is a se security policy violation, uh, and then lead, uh, engineers in the right direction toward delivering a, a better product, more reliable software. Love it.

Very cool stuff, Scott. We're about outta time and these things go quick, I apologize. But first of all, congratulations.

You know, lifelong programmer, right? Coder doing the CEO thing, right? It's, it's exciting, it's fun.

And, um, what, and it's also, the fact is, I, and I tell this to people all the time, what an exciting time to be in, in the software engineering world right now, right? With all, and not just software and in tech in general with what, what I is is, you know, the the promise of, of changes to come and, and new, new vistas to explore. Um, you know, keep us posted, keep up the great work and, and we're interested.

It's gonna be interesting to see how this all shakes out. Absolutely. I think we are in an extraordinary time.

A, we've gotten to see internet and mobile. Um, I'm convinced AI's gonna be bigger than the combination of them. Uh, there's so much potential to, uh, unleash human creativity, uh, that we are on the cusp of, so can't, can't wait to keep you posted on all of that.

Of course, you saw this all coming when you were doing your PhD back in the early nineties. Not even close, but I'm really glad to have gone. Exactly.

Glad to be part Of it. And sometimes it's better to be lucky. That better to be lucky than Smart Scott, right?

No question. All right, man. We'll see you soon.

Thanks again for being here. Best of luck with augment code. Thanks, Helen.

Appreciate you having us Alrightyy. We're gonna take a break here on Ontech Drunk tv, Scott Deon, CEO of augment code here, and we'll be back with more. Bye-bye.

Hi everybody, and you've joined us here on DevOps Dialogues, where we talk to tech leaders, practitioners, folks that are into the world of DevOps, software development, all aspects of that. So my name is Mitch Ashley, I'm VP and practice lead for the DevOps and app development practice at Futurum Group. And I am joined by a special guest today, uh, Johnny Halife Fe, who is CTO, and also founder with South Works.

Welcome. Good to be talking with you. We've talked a few times, Johnny, it's nice to talk again.

Yeah, it's great to see you again, Mitch. You as well. Uh, so tell us a little bit about, just introduce yourself, tell us a little bit about South Works and what kind of things that you all do.

Yeah, so my name is Johnny, and I'm CDO with South Works. We've been in business for 20 years. We are a software development firm.

Uh, we work with companies all sizes from startups to enterprise, working on these, you know, fantastic world of DevOps and multi-cloud and everything that has to do with this new wave of infrastructure. And I'm excited to be here talking to you today. Very good, very good.

You know, having worked in DevOps a while myself too, and we do a lot of research around DevOps. We see a lot of data that shows that organizations have really done a lot of adoption, Mac fact kind of moving into more maturity levels of it. Not everyone, but, um, you know, it's been, it's been around for a while, you know, almost a decade.

I, I'm curious your experience as you work with customers. I'm sure you work with folks who are maybe getting started, kind of have somewhat of a practice going, maybe they've been doing it for a long, long time. What differences do you see DevOps making in how software projects are going and where, where do you see those differences?

That's, you know, it's a great question and, and oftentimes when, when we meet companies that are not so into it, uh, we see, uh, I would say resistant or a pushback because you are working for the software, not in the software. And, you know, uh, after 10 years working on this, I would say that, uh, it's that feeling of going slow to actually go fast. Uh, we see that the business value for these people has to do with like lesser or more control, more predictability when it comes to deploying system, very complex systems.

And, you know, you need to get into it because I agree with our customers when they say like, you're working for the software, not in the software, but at the end of the day, we see a lot of value on that predictability, on that ability to know that things will follow like a natural cadence, if you will, every time you are deploying. And, and we see that also as, you know, the agility on the business. We see a lot of our customers when we meet them that they are like, you know, we prepare our release trains and this takes three months and we have our customers bagging us for X or Y feature, and we have no way of deploying that within the timeframe.

So, you know, it's a maturity level for the company. It's a peace of mind for the SRE, DevOps infra it, I've seen all the names. And it's also, um, a very like, interesting upside for the business because it's your ability to cater fast to your customer needs without having to say like, sure, that's planned for release X, Y, Z, that it's coming six months down the line when we are done with our current release train.

So, mm-hmm. Um, but it takes a lot of education and training, right? Like it takes a lot of, like, you need to be doing this.

And, uh, oftentimes it takes these like, trust me, it will get better, uh, trust me, it will pay down the line. Uh, but once you get into it, I think, uh, the, the, I would say the results speak for themselves, right? Like, people are like, yeah, how, like, how are we just getting started with this?

This has been around for 10 years. I even read the Phoenix project, but I never thought it applied to us. Mm-hmm.

You know, and there can be a lot of drivers for why people might adopt DevOps. A lot of attention is paid to how many releases or deploys that you do per day, per week, whatever. And that, that can be a driver, but most organizations are not ready to do, you know, 10 deploys or 50 deploys a day, right?

Like maybe a Netflix or, uh, others would be. There can also be just being able to, uh, make improvements faster. So fix bugs faster that you're in the development cycle, find out, get feedback quicker earlier in the process so you can make course correction changes.

Maybe it's also a direction in where the project needs to go. Here's the new feature. We're gonna, you know, prioritize this over other things.

We can pivot without, you know, course correcting the whole project and incurring a big cost to do that. So I'm curious, what, what are the benefits that you see people wanting to get by implementing DevOps As, as you just said, and, and I think that's like, uh, right on point. I don't think the driver being like the number of releases, that's just like a consequence.

I think that the major driver has to do with like, the complexity that it takes to deploy a modern system with microservices and bunch of the cloud dependencies and stuff like that. So that predictability and, you know, we see people like, you know, we are going to deploy everything quiet and all that. Uh, that's like number one.

And the other is that without a practice, like an active day of practice, all the, I would say agile or, you know, lean startup, uh, speech goes to waste because everybody, as is just said, right, like you are, you are in for the feedback. You want to iterate quickly, you want to deliver value to our customers, uh, integratively and incrementally. But if everything comes down to this big one milestone process that you will do every three months, and it has a lot of risk and it's super complex, and your teams try to stay away from it as much as they can because of all the stress that it takes, um, it kinds of water down.

Like, why are we working this way? Why are we doing like agile weekly sprints? Why are we doing an MVP and iterating over it?

If by the time it hits the market, it will have been like six months. So I think it's, it's a matter of alignment with the business priorities in terms of like, we wanna work this way and be through and through with it, like trying to go to market as soon as possible. Um, I think that removing the complexity and the stress of what it takes to, you know, deploy a complex system will be number two and all the rest about like, you know, um, doing this contention nets to make sure that you're not introducing new bags or doing 10 deploys a day.

And those sort of things are more like an accident or a consequence of doing that rather than the primary driver. It eventually happens and it start happening without you noticing it, but I think it's more on the value side. Like, Hey, we have this bag for which we are getting 10, 15 tickets a day.

We know it's a quick and easy fix. It will take us half an hour. It cannot take us three months to get into production.

I think that's kind of the primary driver and aligning the rest of the organization because everybody's, you know, chasing the agile way or the lean startup way and building this iteratively and incrementally and all that. But if that's, if, if that doesn't go to market as soon as it should, then it doesn't make sense. Talk a little bit about, you know, uh, DevOps is a contact support, yeah.

Participation, doing it with others, but also learning from others that have done it before. I imagine you enter a lot of projects to build software for customers, deploy things in the cloud or whatever it might be, uh, but you end up in part helping with the DevOps processes, you know, streamlining workflows, maybe learning some techniques about how you do microservices as part of, you know, a flywheel faster, right? To be able to deliver some of those, uh, software into test and into production, um, or iterate on improving quality, things like that.

So you end up kind of a little bit of consulting as a, as a DevOps consultant while you're there as a software leader. Is that true? Yeah.

And you know, uh, one of the things that I like the most about getting into this world and, and that I enjoy the most is working with people that have their own ways, right? Like, uh, when you have a complex system, uh, it's not a re, DevOps is not a recipe. There is no like checklist of the things that you should do.

There are a lot of web practices, there are a lot of things that we would recommend doing, but we found these amazing, you know, techniques, uh, that our customers implement down the line, like versioning and how they deal with multiple API versions and how they enable roll back and how they, you know, uh, deal with dependencies and reuse the deployment surface to make sure that, uh, things are changing the least they need to change and all that, that it's amazing. And, and it keeps amazing me because it's like, sure, you can bring Argo and streamline the way you are working with containers, or you can do, you know, intra network builders bringing the GitHub DevOps runners within your private network to reduce latency and stuff like that. But then there are the, you know, I would say the, the tips and tricks or the practices that are acquired and, and, and they are part of the business that like these, like versioning on how you change traffic or how you roll out and do AV testing as you go to reduce the complexity of the deployment while also, you know, making sure that you're hedging for the risk of releasing a new version or how they do API versioning and those sort of things that are amazing.

And I, I think that there is a baseline for everything. Like, hey, sure, you need like a build server and you need to do, you know, uh, pick up, uh, git flow in any flavor and those sort of things. But then there is a reality of the business.

So I remember working with things that are real time, so how would you change traffic without affecting those that are connected to the system real time? And those are the problems that are unique to each and every system and learning about those while coming with our, you know, uh, proven practices for all these, it's, you know, that thing of like, Hey, I'm here to help you, but I enjoy the ride learning about you. And how are you dealing with these complex problems?

You know, You know, in today's world of software projects too, it's, uh, the success of those projects are even more important to the business. 'cause so many, it isn't just back office, it's business strategies, uh, really outcomes that they're looking to achieve, get into a market, be more competitive, deliver new capabilities. Uh, you know, given your experience of doing software for such a, you know, large time, large period of time, what are some of the things that you and kinda the South Works team do to help increase the, the chances of success?

Two or three things that, that has been, uh, that have been working for us. One is the crawl, walk, run sort of thing. Like, uh, you know, start small and then increase the complex, the complexity as you need to increase that complexity, not for, for the sake of future proofing solutions, because that ends up being like, you know, a lot of work to introduce the smallest change and you actually don't need it, right?

So that would be one. The other one is that pay the tax of having a sounding workflow for delivering and controlling your software lifecycle early on, because the hack and slash sort of days are gone. Like, you cannot live with that.

And the later you introduce all these practices, the hardest is it becomes, because you have a lot of moving pieces, dependencies become buried into, you know, the complexity of the actual system, and nobody wants to pay the price. And it's like, yeah, we've been doing this for a long, long time. Why, why would we, you know, care about it right now?

But at some point it's, you know, um, live or die sort of decision because you need to keep up with the business. So we would rather pay that tax of, you know, having the pipelines and understanding how we would go from development, staging, production, how we would test our changes, how we would know that things are working and so on and so forth early on, even if it's a small prototype, we want to set the pipelines and see them working, because if you introduce that later on, it becomes way harder. So I think that in between those two things, that sounds quite like an oxymoron because I'm saying like, don't worry about what, you don't need to worry, but be prepared for the future.

Finding that, you know, middle ground or that sweet spot is what we've seen as success because crawl, crawl, walk, run, it's great, it always work. It comes from, you know, extreme programming, TDD and all those practices before we even talk about DevOps and all that. But I, as I said, I agree with our customers when they said like, Hey, you're working for the software, not in the software, uh, and you need to work for it like during a period of time.

And that increases the level of confidence for your team, for your business, and even from the non-technical people, those that are, you know, crafting features and talking to customers and have that assurance that that thing that is, you know, bothering you or been bothering you for, I don't know, three, two weeks, we are going to fix it tomorrow. And you can say that and you have the confidence, you know, that you have the process and you know how to get that into production. So I think that finding that sweet spot is kind of key to ensure success.

Sometimes you need to pay the price, but you know, the other engineering it, it never pays off. Hmm. How about, how about some common pitfalls?

Where do you see, uh, causes project DevOps projects or implementations to stumble or maybe even fail? It's a, it's a great question. Uh, I, I, I wouldn't call them failure because I think everything is, you know, um, learning as long as you can capitalize on it and you can, you know, course correct, it will be, uh, harder or it will be more expensive, but everything is fixable.

There is nothing I would say like, Hey, let's drop and start over. Um, but I see this, you know, eventually we will have a multi region multi thing. So we need to figure out how we will align this.

And every system is a living up breathing organism. So as with your body and everybody telling you to go do exercise, this is the same thing. When you build pieces on your infrastructure that you don't exercise on regular basis, they become like stain and you lo like you lose confidence and it, you know, you ended up working to fix them when you never need them.

And they become shows showstoppers. And that, I would say this, trust powers up to a management, Hey, you told me you would, you know, create this because everything will flow like a pipeline and everything will be fine, and we will, we won't have to struggle with getting this into production and those sort of things. So I think that, um, failure is when that working for the software becomes excessive and it's no longer delivering business value.

I mean, we need to be conscious all the time. And it's something that I talk with our teams and with our customers, that it's a price that you need to pay to have a, you know, healthy, well tested infrastructure process and the ops process, if you will. But it needs to be active and you need to be exercising it constantly.

It's also intuitive and incremental. It's something that you will, you know, make more complex as you move forward, but everything that you put in you will need to maintain. So when you end up maintaining things that you don't use, and these become blockers for delivering actual business value, that's where everything crumbles.

Uh, well, let's look forward a little bit. We're at the beginning of 2025 when you and I are talking here. And, uh, there's a lot of anticipation about AI's use in software development also, you know, using AI in our systems and our applications.

Well, that's just one area. I'm curious about your thoughts on where we're headed with DevOps. What's next?

What do you see as the next evolution or challenge of it? I think that, um, leveraging AI to do a, that continuous optimization by looking at logs, by looking at things that, you know, might fail and, and, and course correct quicker, it's an opportunity. Uh, I think that, um, as you just said at the beginning, we are almost 10 years in.

So as it matures, I think we will start having a more, uh, comprehensive view of what it is. And, and it will become a crucial part of delivering business value. I think we will no longer have to explain why we are doing this, why you need to be doing this.

There has been a lot of literature over the last 10 years explaining, you know, continuous delivery, continuous integration and stuff like that. Uh, I think, um, this art or craft will become a real practice within companies where you will have people looking at it. As we look into security, as we look into developer productivity, as we look into patterns and practices for building complex systems, DevOps will be its own entity.

It will no longer be this, you know, dangling thing that sits in between developers and IT pros old school that just care about net networks and hardware. It will be become its own practice. I think it will eventually evolve to, uh, when you and I talk like, uh, I think two months ago, and I, and I was saying about this platform engineering concept where we as developers would start taking more and more responsibility over it.

It won't be this like, sure, I believe somebody else will take care of delivering it. I think it will be a more vertical approach where developers will need, will, must think about the full life cycle of whatever it is that they are building. So it will become integrated, it will become its own entity and it will no longer be like, uh, something that developers and the traditional IT people will fight over, like who owns it, right?

And we are the one who hold the keys to production, or we are the ones writing the software. I don't care about that. So I think it will emerge.

Uh, i I like to call it like platform engineering and thinking about this holistic view that has to go down to the networking level up from the app level. Uh, it's the evolution of full stack. And I think that's where we are heading.

Every time that I go to events like the Q con, I see more developers into it. I see more people that actually write software thinking about like how to make their software resilient, how to take that software into production, how to make sure that it doesn't become a headache down, down the road. Who's going to maintain it, how we are going to version it, and all those things that were like, you know, sitting in between over the last 10 years.

Because traditionally you have like the IT people, the developers, and we would just, you know, pass something along. I think we will verg into a more, you know, mature practice that will develop its own standards and its own, you know, patterns and practices. And, and it's here to stay.

It won't change, it won't go back to what we knew as like, I'm a full stack developer. Uh, same thing as we don't say like, Hey, I'm a UI engineer or a backend person. That that has changed.

We talk about full stack. I think that we will start talking about platform engineering from an end-to-end perspective more and more and more as we go into the future. That might not be that far away.

Yeah, I and I, and agree, I agree with you especially about the platform engineering and DevOps kind of converging, whether it's one group or, or a combination of folks doing it. There's a lot of synergies. And of course DevOps has helped to kinda elevate a lot of things.

Helped, you know, platform engineering, I think, you know, a a come to of age, but also elevating testing, elevating operations, elevating security, software quality. And I think also as AI is introduced more and more into software as well as the pipeline, that'll help us get there. It's a lot easier to improve something you do consistently as opposed to different every time.

Correct. Exactly. And I think one of the things that, that they will have brought into the bigger picture is increasing the level of consciousness for those, writing the software about how it will run, how it will go into production, even as, as if you said, right, like it's a bigger squad in which you have like dedicated people working on that.

But you need to be aware, you need to be aware those things of like, hey, how we would deploy these or how we would run or they're working or the ports or the things that as developers we thought we didn't have to care. It's gone. Like we have that, we, we are conscious about it right now.

And that is an important piece. It will converge. And as you said, it might not be the same person like the, the, there is no Swiss knife developer I think, but you are aware, and that's like the most important thing because, uh, that waterfall that we've been fighting for the last 15 years in terms of being agile and using Scrum and XP and TD and all those sort of things need to transpire into infrastructure to production and making sure that we are a sounding team.

So I think that's one of the benefits of DevOps that it has brought into the picture, increasing that level of consciousness about everything that's going on with a piece of software that you're writing. And I think that will become the gold standard. There is no way back.

We think about things more systemically, more holistically. Yeah. Well, Johnny, it's been, uh, fantastic talking with you again.

I always enjoy our conversations. Hope we'll have you back again on DevOps dialogue. Uh, folks wanna learn more about South Works and how to engage with you and your team.

Visit the website, is that correct? com. You can send us an email, an inquiry.

We are always happy to chat with customers and as I said, right, we learn a a lot there. There is like, we don't hold the truth. We are just there to accelerate people goals and make sure that they are confident about what they're doing and they can scale and deliver value to their customers.

That's what we do. com. Fantastic.

Johnny Halife Fe, CTO with South Works. Thank you to you and the South Works team. And also thanks to everybody for watching and listening today on DevOps dialogues.

We'll see you on our next episode. This is Techron tv. Hey guys, thanks for the throwaway here with Scott Trevino, who's vice president of Cybersecurity for TriMedX.

And we're talking about, well, what to expect in the coming year and beyond with the new administration as it applies to cybersecurity and healthcare. 'cause there's lots of regulations and well, the regulations are subject to change. Scott, welcome the show.

Thanks for having me. So what's your read on what's happening here? There's a lot of, uh, people focused on what's happening around regulations in general, and maybe not everybody's paying attention to what's gonna happen in healthcare specifically, but cybersecurity folks, you know, they kinda live and die by a lot of those regulations in that particular sector.

'cause we have things like hipaa. So what's going on? Well, there's a lot going on, as you are probably well aware, there were a number of, uh, increasing cyber events last year in healthcare.

Uh, maybe towards the top of the list. We might all be familiar with change healthcare and the significant impact there. And as a result of, uh, that continuing, uh, tough environment for healthcare, um, we've seen a number of legislation introduced last year.

Um, you know, not the, uh, the least of which was some healthcare infrastructure security and accountability act. We saw Healthcare Cybersecurity Resiliency Act, and a few other key pieces of legislation that were proposed. And I think that's a natural outcropping of what's, what's going on in the environment.

We're seeing hospitals in the US with, you know, almost 2000 attacks per week, uh, coming after them. Healthcare information's highly lucrative. Uh, the sector as a whole per critical infrastructure is the highest, you know, it's the highest targeted, the most lucrative data to obtain.

And unfortunately, it's probably one of the more immature critical infrastructure is creating a, a pretty rich environment for the bad actors. The Supreme Court has also taken aim in some of their regulatory authority of a lot of agencies, and I imagine that, uh, healthcare is gonna be one of those affected eventually. So are those regulations going to get reviewed at some point if they were enacted by the agency versus something that was passed by Congress?

I, I think that's a great question. And you know, one, one example, or case in point is, uh, health and Human services through the, uh, OCR, uh, released a proposal on updating the HIPAA security rule. And, uh, it's a significant change that, um, you know, has been proposed.

It's in the 60 day, it was released January 6th, and there's a 60 day window for commenting, and I think the proposal's about 400 and, uh, almost 500 pages in total. So it's pretty, it's pretty meaty. Uh, does some things to align the security role with, you know, modernized cybersecurity practices.

It creates, you know, things like the requirements for inventory, network mapping, uh, better controls and requirements around patch management, encryption of PHI and so forth. So that, that's a significant proposed change. I, I think, you know, I'm not Nostradamus I think with the new, uh, you know, uh, white House and new administration, some of the new appointees, I think it's gonna take a little bit of time to see, I think, you know, give it 90 days to a hundred days to see some of the confirmations are done.

What does it mean? You hear some things out of the, uh, the new administration to eliminate 10 regulations for every one new one? Um, you know, so I think there's gonna be a few things that shake out.

So that's one of the big ones that came, uh, you know, came, came out on in January 6th. So that's right at the change in the administration. It'll be interesting to see what, uh, the new the new group does.

Uh, I would say that there's a need for better, uh, application of legislation and regulatory requirements for cybersecurity and healthcare in particular. Um, just given the nature of the things I mentioned before, I think there would be a benefit there. However, un you know, unfunded mandates legislatively are, would be bad.

Uh, so requiring, you know, the application of rules and essentially the introduction of significant cost to implement without funding or a way to recoup, some of that's a challenge. So if I use the, the HIPAA new new proposed rule example as way of example, uh, that's estimated to cost, I think upwards of $9 billion in the first year, and then about four or five every year after that. So, um, there's a significant cost to prepared by the, uh, those who have to apply and abide by HIPAA rules.

Uh, and although you can avoid the pain of a breach potentially through implementation, uh, that's a cost avoidance versus, uh, covering costs to implement. So you still have to outlay the investment there. So that's what I'll be looking at as I study that and, and comment on that further To your point, we're kind of torn a little bit about some of this because, um, we kinda like the idea of more regulations if it improves security, but if they're not funded, it becomes a bigger problem.

'cause a lot of these healthcare organizations, I mean, some of them are huge, but by and large, most of them were kinda mid-sized to small and maybe marginally profitable. So can they afford these kind of fundings? Yeah, that's another very, uh, important aspect to this.

And if I, you know, were to share a bit about rural healthcare, there's roughly 1800 rural hospital systems, about 80% of those, uh, or just about are, you know, 25 beds, uh, hospital systems. So when you look at the challenges a rural system faces, there's a multiplicity of factors here. Attracting the right talent, uh, you know, delivering good services and, and staffing, not to mention, trying to get access to talent such as cybersecurity professionals.

There's a huge shortage of cybersecurity talent, uh, within the US and globally as well as biomeds to help maintain your equipment. And when you combine those two needs, uh, you're really looking at a highly specialized individual. And, you know, the, the rural health systems suffer with that, uh, you know, probably to a greater degree than some others.

Uh, you know, we're keeping an eye on this as well. When a cyber event happens for some of those smaller systems, they may not have the resources to endure the financial impacts. Uh, and I see a real risk of after a breach or some cyber event that that would contribute to closing down some of our more vulnerable systems.

To that end though, it seems like, uh, in the last year, especially that cyber criminals are especially focused on healthcare organizations and I don't know, is that because they're gonna get rich off it or are they just that the value of that data is a lot higher and they can sell it somewhere? Yeah, I think there's a couple factors here. Uh, one, the data is very valuable.

That's, that's one. Two, it's a, uh, target rich environment to my, you know, comment before if, uh, you have, you know, a, a number of vulnerabilities or you can socially, you know, mini manipulate folks to get access into a system and do it at fairly low cost with high reward, uh, that makes it a very lucrative, uh, you know, area to focus on versus some of the other sectors. Furthermore, I would say the US is in particular, um, you know, targeted more than any other country in the world from a healthcare standpoint.

And there's, I think, some factors that play into that versus, you know, if you have nationalized healthcare and you got the full weight and consistency of, you know, government run health system, uh, going after some of the bad actors or at least applying rules in a consistent way. I think that, uh, you know, our, our system here in the US I think lends itself to having more valuable data, a more complex environment, uh, with some, you know, a potential need for, uh, you know, more consistent, uh, regulations as well as more consistent operation across, uh, different government agencies to help support. Do you think maybe we need to take a giant step back as a government and look at healthcare and say, maybe we need a, a different approach here that is led by the government to secure all these hospitals versus just asking the hospitals to fit the bill because ultimately, isn't this a form of, you know, national security or citizens are under attack?

Yeah, I think that's a conversation that's, uh, you know, come up for some time and maybe gaining some, some interest because you have nation state actors who are targeting our critical infrastructure, which, you know, happens to be, you know, a, a number of nonprofits and other systems versus, as I mentioned, fully nationalized healthcare. So of course you've got, you know, DHA and the VA and other government run health systems which would fall under, uh, you know, the military or, you know, the, the, the defense department. Um, I, I think that's worthy consideration to say, what can we do?

What should we do to protect our most critical, you know, infrastructure and healthcare being right at the top, uh, that directly applies to access to care, uh, treatment. You know, imagine if you're in route, uh, in an ambulance to a level one trauma unit and that hospital system is shut down because they've been breached, the elevators are shut down, can't move equipment, can't move patients, and you have to be either rerouted to a less than level one trauma center or maybe have to take another hour or two hour ride in the ambulance to get there. A lot of the people who work in healthcare are not cybersecurity experts.

They're, uh, most of the time they're just nurses, doctors at attendants who are just trying to do the right thing. Are we expecting too much of them in terms of their cybersecurity acumen to fight this fight? And maybe that's part of the issue here is that, um, it's not just about how many cybersecurity professionals we could find, it's also about people who work there.

You know, they're all intents and purpose, they're defenseless. Yeah, I think, you know, I think of we need to raise all boats, and it's not just the healthcare industry, whether you're, you know, in banking or any other industry and including your personal life, you need to be aware, if you haven't had a phishing email come, you're probably a rare breed if you haven't gotten a letter from one of your banking institutions or a phone company that's lost your Rutgers, I think we really do need to raise the level of education for all employees, in particular in healthcare. We already have training around HIPAA and patient information privacy.

I think, uh, there is definitely a need based on some of the more recent events where you look at social engineering manipulation to get access to passwords or a reset password to make a breach versus some other form of more complex and costly and difficult attack. Um, I really do think there's a need for that, whether it's in healthcare or in, uh, other industries. And I think it's unfortunately a part of the new, you know, the new norm, if you will, in terms of understanding what it means to be more skeptical of emails and other forms of potential manipulation, or just be aware of, you know, the sensitivity around the data and the other risks.

If I assume that everything that comes to me in the first place is false, I'm gonna spend a lot of time verifying stuff. So that may add more time to their workflows and make things even more complicated. I, I think that's, that's very true.

And there's a number of programs, you know, we implement, um, tools that actually generate those to help you practice, uh, and detect those, uh, and sort of train you on being skeptical to do that. And it's fairly, fairly quick. You, you basically hit an icon to say, Hey, report this as phishing and, and, and so forth.

And I think programs like that, education, uh, that's, you know, basically annualized training and other, other forms of, um, cyber education, um, go a long way. Do you think with the rise of ai, it seems like it's getting easier to create these, uh, fraudulent attacks and phishing schemes and whatever else is going on. So might things get a little bit worse before they get better?

Absolutely. I, I think that's, uh, that's, uh, gonna be something that's growing in prevalence that you see and read about more and more, uh, being able to fake, uh, somebody's voice, uh, and generate a phone call that sounds just like me. Uh, it's incredible about how, how well that can be done with so few words, if you will.

And, uh, it's very difficult to detect those things. So, um, there's a number of potential things that you can do to combat against that. Awareness is good.

Having, you know, your own, let's say called private key. I, I know of an example where, uh, a business owner, uh, actually had somebody impersonate them their voice while they were on a flight. They knew they were on a flight and, uh, emailed their admin to approve a po.

Uh, and they went so far as that CEO had a specific word, the, the admin would ask when asked to do those approvals as a double check, and they knew what that was. So, uh, things are getting quite sophisticated. I know that's an anecdote, but it's happening more and more and it's, you know, it's, it's very real.

Gives new meaning to the phrase safe word, right? That's right. So when you look at all of this, what is your best advice to cybersecurity professionals in the healthcare field?

Uh, 'cause it's easy to be overwhelmed, it's kind of, maybe it feels a lot like you're always fighting a losing battle, but what can you do to kind of preserve your sanity? Yeah, I think that's great. And, you know, I'm a big fan of the keep it simple methodology and it, it sounds very simple, but I think with some, uh, basic approaches here, you can make headway in what can seem like an overwhelming environment.

Um, and it really comes down, I start in this order always, which is, um, you gotta invest in your people and help educate them. And we talked a little bit about that because it all comes down to your folks and the processes then that they implement. So I think, you know, getting a few good cyber professionals or investing in some augmented support to put people with the expertise in place to look at and do a, a formal risk assessment and understand what your risk profile looks like and where to go first and where to start, uh, will help you look at what was previously maybe an overwhelming environment and not knowing where to start, uh, to come back with a risk treatment plan to say, okay, here's what my overall risk looks like.

Here's a risk prioritized approach to go after it and then go implement that. And it really combines those people with those right processes, uh, and leveraging maybe some key technology, uh, that kinda round out your overall, uh, information security ecosystem for a hospital. Um, I think one area of particular interest is the medical devices are unique compared to other OTIT.

So you can't just do remote software patches. In fact, most medical devices, many medical devices may never get a patch for a known vulnerability. So you have this environment where you have to mitigate, not remediate risk 'cause you don't have a remediation, and you have to take those, those folks will have the right expertise and the right processes to know how to go do that, which can help re you know, improve your overall risk posture.

All right, folks here, heard it here. Cybersecurity anywhere is a tough gig, but in healthcare, especially the folks that do that kinda work, it's, they're unsung heroes. And so reach out to them at some point if you can and help whenever and however you can't.

Scott, thanks be on the show. Thanks for having me. I really appreciate it.

All right, and back to you guys in studio. com is the number one online destination for DevOps education and community building. com covers all aspects of DevOps, including DevOps, best practices and tools, DevOps culture, DevSecOps, business impact, continuous testing, continuous delivery and more.

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Hello and welcome to the Techstrong AI podcast. I'm Amanda Razani. I'm excited to be here today with a partner of Costanoa Ventures.

Martina. Lao, how are you doing today? I'm Amanda.

I'm doing great. Wonderful. Well, we're here to talk a little bit about a survey that you put out, but first tell me a little bit about Costa No Ventures.

What do y'all do? So Costa Ventures is an early stage VC firm based in San Francisco, and we focus on B2B investments largely in the infrastructure that help companies transform. So for example, if you are an insurance company and you wanna get more intelligent in how you're doing claims, not just more efficient, we invest in companies that build that infrastructure.

Or similarly on the IT side, if you know, all of a sudden your data's been hijacked and you're needing to respond in 30 minutes and you call it department to try and get their help, how does a human insert themselves in that as opposed to just having the typical response and going through a, a chain a, uh, the typical chain of things you'd have get to, to actually talk to a human. How do we build technology and infrastructure, AI enabled infrastructure that helps us be way better at dealing and responding to circumstances like that? All right, wonderful.

Thank you for sharing. Well, so you recently did put out a, an AI survey. Can you share a little bit about the survey?

What, who were you surveying and then a little bit about what information you were trying to gather from this survey? Yeah, well we are definitely in this whole new era of what we are calling AI native companies. So they've been built in this era of large language models, which means they're building their companies differently.

They're, the whole product backend is different. So we were trying to get a sense of, in this new era, how are companies different and how do they build differently? How do they think differently?

So an example of, one of the things we were trying to understand is, well, how many models do they use? 'cause everyone thinks, oh yeah, they just use, they use large language models. Well, one of the interesting findings was over half of the surveyed companies, and these are all early stage, so seed, uh, seed and series A.

So quite early in their, in their lifespans, over half of them were using four or more models. And so that was a really interesting result as an example. Okay.

So, um, what should business leaders take from this survey? Were there any key, um, details you wanna share from the results? Any information that's interesting to, to business leaders?

Yeah. Well, I think what is interesting is a business leader is gonna have to make a decision. I mean, the, the entire application, what we call the application stack is being rewritten with by these AI native companies.

And so business leaders will have to make decisions about companies they feel comfortable working with. So if you don't feel really savvy in this whole new world, what are the types of questions you should be asking yourselves about? Is this a company I should trust?

Are these innovators that are really leaning in and are keeping up with how much has changed? So an example of how you might use some of the data we're finding is how many models are they using in how they build their product? It doesn't mean that there's a a set minimum, it just indicates the sophistication of the organization you might be doing business with.

So an unsophisticated one will be using one model, A more sophisticated one will be using multiple because it makes them more computationally efficient, which means you get better costs, uh, or pricing. So these are things that would be invisible to you if you didn't know what was behind it. But they're the types of questions you can ask when you're trying to make a decision.

Do these guys really have good technology? Absolutely. And were there any, um, key stats that, that you have access to that you could share from the report?

Yeah, well, uh, one that I showed earlier being that more than half of those that we surveyed were using four or more models. I think what was interesting there was how many, so about 40% were using both Claude and Llama, if that's, uh, you don't know what that is. Those are the, the new models from meta that is open source.

And Claude is, is developed by Anthropic philanthropic, very well funded, but the fact that they are used by so many I think is interesting and might be interesting to you as you're trying to get savvy on how do I assess the businesses I might be working with. And I'd say also where they are based has an impact on the talent pools they have access to. I think we were surprised, not surprised by the fact that over half of the company surveyed chose the Bay Area as the place to to be.

But I think what was interesting there was that 33 per that second time founders were 33% more likely to be based in the area area citing talent and access to investors as the primary driver. And so again, it's, there is this whole new wave of technology and how we are building that is sweeping the startup community and for business leaders understanding how do I assess these companies and know that they are really strong and what they claim to do. These would be the kinds of things that could be indicators for people that don't live in the world of technology.

Absolutely. So this, of course, we've seen this AI technology advance very rapidly only over about the last two years. What do you see for the future of this technology as quickly as it is advancing?

Well, I think that's the big thing, is we have to make sure that the companies that we are working with or that we invest in know how to keep leveraging and take advantage of and keep up with how much things change. So it requires an amount of humility that I think many people aren't used to having in the technology world. Like I know how the te where the technology is going and I know what I'm gonna do.

We're surprised all of us by how quickly things continue to evolve. And so we just have to be ready to dive in and and adapt. And I think that's one of the biggest shifts.

I I've been in technology for over 30 years. This is a, this is a place where nobody is an expert and we're all figuring it out together. And the people that are figuring out the fastest are those that just dive in, put their hands on the technology and try and figure it out.

'cause things are just changing so quickly. Uh, from your experience, is there an issue with, um, that kind of fear of AI from people? Um, they're, they're a little hesitant to dive in because they don't necessarily trust AI still?

I, I think it's merited. I think we get different results at different times and that, that makes us decide how much we trust what we get in response. I will say that is one shift that I have noticed in the last year is the consistent quality of the answers I'm getting outta large language models and products that use it, that evolves very quickly.

So what I would say is it is absolutely appropriate to be skeptical, uh, but we can't stick our heads in the sand on this one. This is one where everyone's like, even if you tried it six months ago, try it again because the models have improved since then. And you might be surprised by what you see and learn and how quickly the models are getting better.

So I would just encourage everyone, no matter how skeptical or concerned you are, to dive in and be unafraid of trying and ex and having your own experiences so that you know how to judge this technology yourself. Wonderful. Well, if there was one key takeaway you could give our audience today, what would that be?

I would say be curious. Be curious. Don't trust others to tell you what is the best, what is the most interesting, try it for yourself and know that everybody's learning at the same time, which is a very unique moment in technology history for all of us.

All right, wonderful. Well thanks for coming on and sharing your insights and some of the stats from your recent survey. And thank you again.

I look forward to speaking with you in the future. I Look forward to it as well. Thank you so much.

Alright. And also thank you our audience for tuning in every week. Stay tuned.

There's more. Welcome back to Text Run Unplugged. My name is Ca Kin and today we have Luca Muli.

Nice to meet you. Can you introduce yourself? Yes.

I'm Luca Muli. I'm a software engineer. I'm 40 years old.

I work for a company called Red Hat. It's the largest open source company in the world. And um, the opinions are on my own, but I somehow represent the company.

So. And do you wanna talk about, uh, your involvement with Java user groups? Yeah.

How things are there. Yeah, I'm the administrator. I've been the administrator of the local, I live in Milan, Italy, so I live, uh, uh, I has, I was the local administrator of the Java user group since, uh, something like 15 years I think.

So I saw the evolution. I joined when I was, uh, at 25 years old. And these days I'm a 40 years old, so the things haven't changed that much in the last 15 years, but, uh, it has been, uh, interesting so far.

Um, do you wanna talk about your opinion on like getting young people? Yes. We have mostly two problems with, uh, the Java user group currently.

The first one is to gather new people, especially fresh kids. I would like to see like young people join the Java user group, but unfortunately it seems that Java is, as a programming language is not considered cool anymore. Perhaps by, by some, I dunno, from some developer.

And, uh, but at the same time the format is mostly, we have mostly 30 years old or 40 years old. And, uh, so I think it's kind of strange for 20-year-old to, to join our group. And this is especially important because we want to hear the, the approaches of the new generation when instead we're just hearing always the same people talking about perhaps always the same things.

And, um, so, and that's a shame. I personally trying to push newer generation, uh, to Java in general, because you probably know that Java is the language in which Minecraft was originally developed. So I think that, uh, my talking about Minecraft could be like a way to start talking about Java even with, uh, the younger generation.

But, uh, I haven't tried yet something that I will do in the next years, Uh, Minecraft is how I got into Java. Right. Nice.

I think it's worth a shot. It works then. And the problem with, um, I see the problem with mine that I see with Minecraft because I'm strongly opinionated, is that, uh, of course developers want to monetize over mods and, uh, new programs.

And so they've tried to build all these kind of marketplaces. And since, uh, I see that the new gener, new generations are really attracted by new mods, new skin and stuff like that, they just want new thing. They don't necessarily want to create new things.

So I think the important stuff is to make them, uh, understand that, uh, by knowing Java, you can actually create your own, which is, I think, important thing instead of consuming content that has been done by other, other people. And, uh, to do that, I, I would suggest personally that's what I do to every parent or every young, uh, people using Java to avoid using the, the better condition of Minecrafting, which you actually buy for mods, but instead, uh, rather using the original Java editioning, which can install what you want. But, uh, sometimes it is, this is hard.

No, I Definitely agree with you. I actually learned some programming on the Java edition. Mm-hmm.

I ran my own Minecraft server and I got to learn some like command one. The problem I see with, uh, Minecraft Java edition is not necessarily easy to, to install new mods. It's complicated.

You have launches, you have to check the versions, you have to check, um, all kinds of details that probably somebody doesn't want. It's just too much convenient for, for somebody to launch the, the bedrock edition, go inside the store, buy stuff with a parent's credit card, unfortunately, and, uh, like use them. Uh, so again, this is about gatekeeping, right?

We want them to, to learn new things, to learn Java, to learn development, but at the same time, we don't want to get, keep them from using this. And of course, if, uh, to start, uh, to start using Minecraft, I have to know what Java is, what a Java vector machine is, what a version is, what's the change log, what, uh, I mean it's kind of complicated. Yeah.

There's a lot of challenges involved. Like all the challenges of Java. Exactly.

Let's say that I would recommend this to a 7-year-old without having a parent that will help you in the first place. But the beauty of this is that once you get over the first part, you get everything for free. I mean, because this is the beauty of open source, right?

We create all the mods, all, uh, the things are mostly open source and uh, so there are tons of things you can try like without paying anything. I think that's, that's useful for both parents and kids. Yeah, I would agree with you.

Nice. Uh, anyway, I diverge because I started talking about Minecraft and I'm really opinionated about Minecraft. Uh, anyway, we're talking about the Java user group.

Uh, so the way I see these days, Java user group will become like the evolution of what has been. I think that if we want to focus on the next generation, and for example, Minecraft in general, we need to create a user group. In fact, what I wanted to do in my local community, my local town, uh, I think it could be useful to create something like a Minecraft user group and like to start in teaching them programming like in disguise because, um, I dunno, we still have many biases and many, uh, stereotypes about programming in Italy.

I guess I'm just speaking for northern Italy, and we still think it's something for geniuses or something for male geniuses, for whatever reasons, or ma geniuses. Uh, you know, these are the stereotypes that my generations will bring forward because we were growing up with, uh, this idea in movies of, uh, having the small boy that, uh, I don't know why it, it was always a boy and never a girl by the way. I know.

Whoa. It's just like the movies like that that could solve problems because their parents couldn't use even use a computer, right? So we are like children of those generation and I think things have changed, but we still, uh, have those stereotypes.

Yeah, I can see how that's still a problem. Yeah, Most definitely. And uh, I think in Italy we have even a bigger problem because perhaps this is just my idea, my personal opinion, I'm not sure about this, but it seems like the US you have a higher technical competencies.

While in Italy, computers are still considered something for the younger generation. So for example, my, my parents, which are 70 years old, so like baby boomers as you would say, like they don't use the computer at all. Like they don't even know how to use computer.

They just use smartphone these days, but they use it like randomly. So they still call their their sons and their daughter to make them help and they use stuff. So we have, perhaps we have even bigger stereotypes.

I think Java user group has other problems, such as, for example, we are lacking diversity. And diversity in Italy is, um, perhaps not just a matter of nationality, because we consider mostly ourself members of a European union and we don't really check whether somebody is from France, so for Germany or from Spain of, uh, or if their parents are from Africa or they're from China or whatever. We just don't care about this.

Uh, we, we are lacking diversity. We're definitely lacking diversity in gender because in the local job user group, we just have a few girls, a few women. And uh, that is a problem.

It's kinda problem because I can't, I can't believe that, uh, there are only that few developers. But, um, I mean it happens. I mean it's, it's kind When we get the younger generation to come to the Java user groups.

Yeah. Also get the girls to come. Yes, most definitely.

Um, when we join like conferences in universities, we see many girls like join university, uh, even in, uh, what we call stem. I'm not sure whether it is a term that we use in Italy, is science technology. It's pretty Wide way.

Ah, it's fine. Okay. Because sometimes in Italy we use English terms like wrongly.

So I'm not sure whether this is correct or not. Anyway, stem in stem, um, faculties and uh, so I really hope for the next generation to be more diverse from that perspective. Perspective.

And are you giving a talk here? I have given a talk like yesterday. So this was recorded on Friday and uh, we spoke about, uh, Java performance, which is the niche of a niche.

Apparently nobody really cares about it. Uh, since, uh, we didn't have many attendees, no, joking aside, uh, this talk was, uh, was perceived differently here from uh, when we started doing this in Italy. I think in Italy there was more a bit more interesting regarding performance here.

It wasn't that well received, but I guess different audience, different people. It could just be like the conference format and just like the flow of people. Sorry, can you repeat the question?

It Could just be like the way the conferences were organized and the flow of people just other computing sessions. Yeah. Probably in your session is bad.

No, yeah. Perhaps it's bad. I suffer from imposter syndrome.

So perhaps I think that just, uh, it's just bad. Anyway, um, what we're talking about. Yeah, it's just probably, it's, it's kind of a hard, hard topic.

It's not general purpose. It's not something that you would care, like when you're starting, it's not a beginner topic. So I guess that if you put such talk at the end of, um, of a, of a day, like perhaps people are posted.

Do you think this topic is important? Okay. So thank you for the question.

It is a very interesting performance are important specifically in the Java world. Um, because we try to have stereo, we, we mostly have stereotypes about Java and I don't understand why. I mean, knowing the story, I could understand why we have such stereotypes.

But, uh, anyway, we think that Java is a slow language by actually it's not. I mean, it, it was used to, to code Minecraft for example. Perhaps it wasn't the, the the best choice.

That's why they decided to rewrite it in a different formula language. Anyway, Java moves something like 90% of the internet. It's like random numbers.

Of course they are not scientifically proven. But, uh, Netflix uses Java, apple uses Java, Amazon uses Java. So Java is definitely moving the internet at the backend level.

So it's really important to know about performance. Um, I heard, I'm telling you a story. I heard another talk, I won't tell you the name of a talk, um, at the beginning of a conference.

And he say like, we all know that Java is low, but this is actually not true. I mean, Java can be fast. Uh, it's main purpose is not fast because it was born as a language for portability to have the same code to be able to run the same code in between different, uh, Java machines and in, uh, different architectures.

Um, but Java in 2024 is definitely fast. The problem is most developers don't really care about performance for various reasons, because we mostly care about speed of ness of use of a programming language, uh, speed of deployment, uh, of development. I'm sorry.

I think we can solve performance with bigger and bigger graphics cards and processing units. Yeah, it's, there is also the problem we try in, in the last 20 years, we had like a gigantic explosion of uh, uh, CPO processing power. So most of our solution was like to put more CPUs and more computer.

The same thing. Like without, I, I'm sorry. I started to feel to to sound like an old man.

But, uh, uh, when I was young we used to code on a 4 86 or, or a pento. I mean, and it wasn't, the experience wasn't that much different from computers these days. Like, um, perhaps my memories are wrong and perhaps it was different, but I remember wrongly.

Anyway, what I'm saying is that even if we have computers that are like far more powerful, like order of magnitude more powerful than we had like 20 years ago, master interaction are still measured in seconds. And if you think about it, it is just crazy. I mean, what you're using an app and it will take something like one second to open an app.

That's impossible. We have computers that are like considered super, the CPUs in the smartphones are considered supercomputers would be considered a supercomputer. It's something like 15 years ago.

And why we should still wait one second to open an application. Sometimes it happens. And, uh, because developers don't care about performance, I personally think that we don't have enough engineers to care about this kind of thing.

Perhaps we're still lacking people and perhaps in the future will be, I dunno, double, triple the amount of engineers that we have today. So we could have like people focusing especially on the performance and other people programming, but it's just my personal opinion. I do Think performance would be an issue.

Like I'm surprised that they're not really addressing it. Yeah. 'cause it sounds like a problem if you're waiting a second or maybe even a few seconds just for an app to open.

But, but think about how, how often does it happen for you to have, uh, an application that takes once every day? Yeah, every day. If you think about it, it's crazy.

And you're probably using an iPhone that runs on native code because with this compiled to native code, it's not using Java. But instead, if you were using Android phone, it would be even worse 'cause you're using Java. And we know Java is low.

Joking aside, uh, the work that Google has done to make Java run fast on Android is remarkable. But still we have a problem because engineers don't care about performance. And also there is, uh, this thing I have to talk about is about climate change in general, like sustainability.

The less CPU we use, the less energy we are using, the less energy we use in the less we are consuming the planets. Unfortunately, this is strange to speak about in 2024 because we're using LLMs and LMS are like burning forest each time you make a request with LLMs. But, uh, yes, that's another thing that we should address eventually.

I never thought about relating like the amount of power we use on our little devices like climate change. But it still is a problem. Like, uh, if you think about it with a lithium battery, you can like last, uh, all the day while if you're using a desktop computer, like it's using much more power.

Yeah. And sometimes the room heats up when you use a desktop computer. Yeah.

And you need to turn it off just for that. Yeah. So I can see how that like, it's draining so much power.

Yeah. Performance is really important. Uh, I really appreciate that there are companies such as Apple, apple computer, apple in general that is taking care of, uh, sustainability.

If, if, you know, the new CPUs from Apple drove far less power than the previous one. And I really hope that for the future, everybody will focus on this. But again, saying this in 2024 where everybody's talking about AI and AI is order of money to consuming much more power than all the other stuff is kind of strange.

But yes, maybe we need sustainable ai. Exactly. But we are still at the very beginning of AI and, uh, of AI as we spoke about in 2024.

And by that time, we mean at L Lamb are mostly generative ai. So yes, eventually we have to address this problem. I think we've had a really good chat today.

Yeah. So thank you. Thank you very much, Cassandra.

Hey everybody, this is Mitch Ashley, welcome to DevOps dialogue. This is the podcast, the interview where we talk to the most interesting people about topics that are really top of mind. So we're, I'm very pleased to have, uh, Mehdi Daoudi, who is co-founder and CEO of Catchpoint joining us.

Good to be talking with you again. Thank you, Mitch. Thank you.

Happy New Year's. Good to see you as well. And thank you for having me.

Absolutely. Happy, happy 2025. Good to see you.

Me, me and team. We're at the tech field, Dale events. I think you're gonna be at some more, you're having to tune to that.

Be sure and do that. Some great content there. Great.

So it was interesting this morning I was having this conversation about we're a wash with data, but we're not a wash with information. We have a lot. And that's probably true, I'm guessing from a, from application performance monitoring standpoint.

I know there's a lot of lights, but who knows what that all means, right? When something's blinking or that's not blinking, which give us, give us first of all, tell us about you and, and, uh, Catchpoint, and then we'll dive into how do we deal with this and a little more, uh, holistically. So Mitch, thank you again.

So my name is Maria, co-founder, CEO of Catchpoint. Been, uh, launched Catchpoint in 2008. So we've been at this in past 16 years, almost, uh, worked at DoubleClick and Google where I was in charge of actually monitoring.

So I was on the buying, building, deploying and using the tools to, to keep, uh, uh, the ad technology system that, uh, double click was known for alive and performing super well. And, uh, I love monitoring, uh, whether we call it observability monitoring, et cetera. The reason why I love it is because when we do a good job, um, you deliver better services, you deliver, you have better outcomes, and then the monitoring becomes an enabler for running a better business.

And that's what I saw firsthand. Uh, and I was very proud of being part of that, of creating what often is called the culture of performance, which is like, hey, how can we be the best at doing what we do with the most reliable, the most available, the most fa the fastest, et cetera. And so, and uh, throughout that journey, of course we learned a lot of stuff.

Uh, which is one of, of the, for example, you, you mentioned it's too much data, right? The data overload, uh, because as humans, uh, we go through some kind of outage and we regret that we didn't have the right data. And so the immediate, uh, knee jerk reaction is like, okay, we're going to log everything now, right?

And we're going to lot, but nobody for nobody thinks about how much going to cost. Mm-hmm. So then there is usually A-A-C-F-O coming down on, on you and saying, okay, you just spent like x number of millions of dollars on storage just for the monitoring system.

But the other thing is like, it's, it's nobody knows how to interpret the data. The correlation, the causations, the connecting the dots becomes even more, uh, difficult to make, right? So the more data you have, the more cardinality you have, the more like, I don't know, what am I looking forward?

And, uh, and so I was just on the phone with the customer earlier and literally the, they were talking about how, you know, we went from looking for a needle in a haystack to looking for a needle in haystacks. Mm-hmm. And, uh, and so more data, more silos, more people, et cetera, can, can lead to problem.

Now the bad thing is like, it takes longer to detect a problem, identify a problem, and resolve it. So I think, uh, I think we're in too, for some recalibration of that. What I talk to customers is they're trying to figure out a solution to end that either through, uh, you know, of course, uh, wouldn't be 2025 without throwing ai, but those are the kind of tools and capabilities that are hopefully going to allow us to go through a lot of data faster and then maybe helping us connect the dots better.

I remember a day when we used to say the best way to provide the highest quality is don't change anything. Well, that's not, that's not even possible. It's all changing.

It's like, you know, it's no longer a solid, it's a fluid, it's under constant change, different, and Even if you don't want to change Mitch mm-hmm. The internet is changing. Your, your third party providers are changing.

Amazon is AWS is making a change, GCP is making a change. Your SaaS applications all. Exactly.

And so how do you get ahead of that? How do you, how do you keep up with the constant changes? And oh, by the way, you can't go to the principal's office.

I say, well, it's outside of my control. I'm not responsible for availability, performance, or reliability. Mm-hmm.

You're still in the hooks, right? I can't point the finger and have that me make any difference. Well, so where does a PM kind of end its usefulness, its useful life, and then how do you fill in that gap?

I mean, I remember AP PM was, oh good, I can have some w servers out on the internet, load my webpage and measure them how fast it loads it. Right? We're in a much different world now, but yes.

I mean, a PM even means a lot more than that. Well, I, first, I, I think, uh, uh, what I usually tell folks I talk to, especially on the customer side, is, you know, terms, terminology sometimes can be limiting in the way we look at things, right? Mm-hmm.

So if you think of your house as your application, you have valuable stuff inside. You need to secure it. You need to make sure that you have your humidity monitors inside the house, et cetera.

But then you also need an alarm system. You need to, you, you need to make sure that, uh, can, can, hopefully nobody can get it. Um, so, so thinking about that from, from that perspective allows you to say, okay, what pool do I need to get the job done?

And the job is very simple. You need to be up, you need to be fast, you need to be, you need to be, uh, available to all your customers, right? So if you have users that are worldwide, you need to make sure that whatever tool you have or whatever perspective you have is a, is represents what the end user, where your end users are.

Uh, and so, so I think it's first like walking backward. What are we trying to accomplish? What are the metrics we want to do?

Maybe say we need to improve avail availability, then what are the tools I need to do to, to do that? Uh, but a PM is still the best. Uh, and tools like Dynatrace and, and, and, and New Relic, et cetera, do a fantastic job at, at making you understand what's going on in your house, right?

Being to understand when a, when a, somebody does a search, what database it's called, how long it took to query the, try to map the dependencies, et cetera. But the challenge becomes for some companies that, that rely on many, many other third party services who's keeping an eye on the internet stack, right? The, the same way you have an application stack.

Uh, what happens to CloudFlare? What happens if CloudFlare is having a problem? What happens if Akamai is having an issue?

What happens if the network in India is congested? Again, being able to understand all of that. So it's not, uh, I think it's understanding what each tool does, right?

Uh, I don't use my toothbrush to comb my hair, obviously. Maybe I think it'll work for me, but a bad example, Mary, but you know what I mean, right? So it's like you need use the right tool for the right job.

Interesting. Yeah. It, it's a, it is a great point, and like your analogy, it's sort of like driving down the interstate.

I know my inside of my car is all looking good, but the road conditions can change drastically, whether, correct. Yeah. So any things outside of your control really Correct, essentially is what a lot of that is.

Well, so talk about Catchpoint and some of the lessons you learned, you know, at, uh, at DoubleClick and at, uh, at Google that informed you of, okay, here's the next approach we have to take to answer the rest of the equation of what's going on in this picture. Right? So very fortunate enough to have been part of, of the beginning of the internet kind ofish, right?

From a commercial standpoint in 97. And, uh, and so, and then Google, of course had a super, uh, focus on the end user, right? So if you think of Google, you think of that, that search page that needed to load in, in Subec subsequent.

And uh, and I think that set the stage for the, the whole concept of like, everything needs to be available. And Yahoo too. I mean, Yahoo spent a lot of time inventing a lot of the tools and the concepts that, uh, exist today.

So the end user is where it matters the most. It doesn't matter. And this is what happened to me at double click one day.

Uh, I walked into our, no, our network operation center, and I, I saw my team chilling and, uh, you know, as if nothing was happening, uh, and double click was broken. We were not serving ads, which are live a livelihood, but all the systems were green. Like literally all of our internal monitoring was showing, okay, uh, no network issues, no database issues.

The servers were fine, 15,000 servers were, were up and running fine, et cetera, but we were not delivering ads. And, and so that's where the monitoring is, like, what are you monitoring? Are you monitoring for an outcome?

Are you monitoring for CPU and memory kind of stuff. Mm-hmm. And so that's was my big aha moment when it came to, you need to monitor what matters from where it matters, right?

Uh, it's, it's, it's so critical and it does what, this is the philosophy that still drive us today. So, um, and that was one of the biggest lesson is again, monitor the end user and monitor where the end user is. And then also if you're an e-commerce, then can I buy something and add it to my cart and check out, right?

If I am a sneaker company, can I, if, if, if every time I go and pick size 10 you have an error, then something, you should do something about it, you should first know about it and then fix it. So I think driving the outcomes monitoring, should you be here to help businesses run better, right? So align the monitoring strategies to the business outcomes.

That's I think, one of the biggest things I've learned. And, uh, and when I see customers, some of the customers and partners that we do that for, it brings a lot of joy to me, just like to see that, that causation between better monitoring, better observability to direct impact to, to, to business outcomes. It reminds me of the metrics we always create for our technical organizations.

As you know, me, time between failure or whatever it might be, these kind of response things. That's what they're all important. Yeah.

That doesn't mean the customer had a great experience though. Correct? Because failure, we live in a world, failure's gonna happen.

It isn't avoid failure at all costs. That's impossible. It, it just so much is out of our control, right?

Talk, talk about, so how do you, how do you do this from the end users viewpoint? So you really are measuring as much as possible, or you really assessing, I should say, the experience that you're delivering. So with the concept of we, we want to monitor from, from as many places as possible to simulate where the end users are.

So that was one of the design philosophies of Catchpoint. So we do what is in the industry called synthetic margin, which is a robotic process of monitoring. Um, it's like digital mystery shoppers, you know, mystery shoppers have existed for a hundred years, uh, where the digital version of it.

So we have them, uh, located in the right cities, the right ISPs, the right carriers, the right telecom carriers, et cetera. And those things, uh, those machines, they do very simple tasks. They basically simulate what an end user does, uh, and they do it across all the different stacks of the internet.

So your DNS your network, your application, your APIs, your third party services, et cetera. And our job is to really, from there, help customers triangulate the problem. So if you show up at your doctor, God forbid, tomorrow you're going to show up with a symptom, my head hurts.

Great. A good doctor is going to go through, okay, based on what I see, let me see if it's this, that, or whatnot. So monitoring and the data that we provide that needs to help the customer go through that triangulation as fast as possible so we can reduce the meantime to repair.

And so what's also very important in our business is the data quality. So we focus on the data quality, the signal, what we call this, the signal to noise ratio is very, very important because you don't want false positive, right? I mean, no hospital can deal with like people showing up at the hospital every time they cough, that you have to have fever, this, that whatnot.

So, so it's very important for us to deliver the right qual, the right metrics and the right quality to be able to drive better triangulation. So that's one thing we do. The other one is we married, we enriched the data with other things.

So for example, synthetic and rum. So real user monitoring, um, fantastic, uh, uh, vast way of, of answering the question. So what, right?

So the robots say there is a problem in Saudi Arabia, RUM should be able to say, oh yes, holy cow, it is a big problem. And oh, by the way, we dropped by 30% the traffic. Uh, so again, it's like, how do you put all these things together, uh, in one dashboard, et cetera, to answer the question, what's broken where?

And whose fault is it? Right? Is it us?

Is it the internet? Is it, is it a particular third party? And all of that needs to happen super, super fast.

You know, we do this SRE survey, we've been doing it for seven years now. Uh, and I'm very proud of the work that team does. And this year, something that, uh, was very interesting that came up and this performance is the new doubt.

Uh, so we went from like availability, and I've seen, we've seen that with some other customers where, you know, the, on the maturity side, they cared mostly about, am I up? Are we up? Is the stuff up and running to now performance, meaning that after three seconds, even though the site or the application is up, it's actually done because the person, the customer is not willing to tolerate that.

So the, the level of, of how much you're willing to tolerate slowness is going to be an indicator of, of availability. Uh, so again, how can we do all of this stuff as quickly as possible so customers can get to fix things as fast as possible themselves? Well, if we can wrap with the AI question.

Yes. On all of our minds, everybody's talking about agent ai. It seems like we're not very far away from synthetic users that are AI agents and you know, a world of of, you know, I'm, I'm actually out there doing multiple things 'cause I've got agents correct.

Where my business does is, is there anything that customers or organizations can do to kind of prepare for that unknown of what that future may look like? I, I would imagine the more you understand an instrument and understand the experience that you're delivering today, as you add a new factor into it now, now you can assess how to manage it better or understand it better versus, I don't know what I'm doing now that just makes it worse, Right? So I, I think it's an excellent question.

So, uh, let's, let's answer it two ways. So the first one is, what are we doing to prepare for a world where now there's going to be a combination of humans using the internet and then synthetic agents, right? Uh, uh, that are going to be also doing stuff like, uh, there, I was reading an article where Microsoft is, is allow you to create a robot to literally answer emails on Outlook without, without you doing anything.

So, so I think that doesn't change the way we look at things, which is like availability, reachability performance, reliability are, are, are pillars that exist in an AI or non-AI world, right? I would say, I would even argue that in an, in an AI world, the tolerance for speed, reliability, et cetera are going to go down and people, we, we need better, we need faster, et cetera. So I think, I think that is a fundamental thing.

Uh, the other part of your question, the way I look at it is when I talk to our customers and the SREs, the DevOps, et cetera, uh, we're all trying to do our job better, faster, and be more productive and more efficient. Ultimately, that's what the, the promise and the revolution of AI is. And so what we are seeing, uh, is we're seeing customers that have, uh, a more methodical approach to ai.

Like, okay, pick three problems that we want to solve, rather than like peanut butter kind of thing. Like, let's put AI everywhere. So it's like, okay, what are the areas where we're having a hard time finding talent, we don't have enough manpower, uh, and let that drive, uh, uh, for example, either automation or whatnot.

Uh, but on the monitoring side, et cetera, there is definitely some incredible efforts that are being led to connect the dots faster, better, right? Being able to pull all the data and solutions. Like we're seeing a lot of that in Databricks where customers are pushing all kind of data into Databricks and then being able to connect the various dots at, at scale over there.

And people are seeing some really good benefits so far, Databricks, snowflake, et cetera. I think that's one area where we're going to see a lot of stuff. Now, the benefit of that, which is we're going to have less issues where people missed an alert, because I see that a lot with our customers.

Oh, we, we got too many alerts, or somebody took a large break and we miss something, that stuff is going to go away, or it's going to supplement or, or, or augment, however you want to look at it. But I think that's one of the benefit. I think that AI is going to drive better availability and reliability to, to, to a lot of companies.

Uh, Very exciting. Yeah, it's interesting time and you live in interesting times up. This is one of the correct, most funny funnest times in my career.

Funnest is a word. Um, yeah, maybe, uh, tell folks where they can find out more about Catchpoint and learn more about what you all do and get engaged with you. Sure.

com. Obviously we're on LinkedIn, Twitter X, sorry. Uh, our blog is fantastic.

Highly encourage you to, to search that, uh, and, uh, read some of the content we produce, whether it's the SRE study that, again, 70 in a row, uh, super impressive and or the reliability and resiliency report we publish. org. I'm sure some of your listeners, uh, know about WPT.

Uh, and uh, so that's another free tool that, uh, that we have for the community to test your performance. So again, slows the new down. So start testing.

Very good. There you go. You heard it from the expert.

Well, thank you, Medi, it's great to chat with you again. Thank you. And we appreciate everybody tuning in to this episode of DevOps Dialogue and look for Medi on another RUM event or a techron tv.

He's around. We like having him on. Thank You so much.

Take care. How can you, everyone again.