Akka’s 20-Year Journey to the Heart of Agentic AI

Hey, everyone. Welcome back here to Techstrong tv. You know, I haven't had my friend here on, I, it's gotta be at least eight, nine months, maybe more.

Uh, you may know him, Tyler, jewel, Tyler, and I know each other now. I don't know Tyler. Seven years, eight years?

Maybe longer, maybe more. Yeah. Yeah, it's been a while.

But Tyler's also the CEO of a company called aka, which is a really interesting company he's gonna tell you about. But speaking of interesting, Tyler's led sort of a charmed, interesting career. Tyler share, if you don't, I don't wanna embarrass you, but share, if you don't mind, a little bit about your career path here.

Oh, wow. Uh, well, I spent, uh, 10 years, uh, as product management for some really interesting dev companies, BEA, uh, Oracle, um, uh, my SQL as well. And then I've done, uh, four startups.

Uh, this is the fourth one that I've run. And all three previous ones were also dev dev platform related, and they've all been acquired, um, by some really interesting companies, uh, along the way. And it includes WS O2 and Code Envy, uh, which was a company I started in the Cloud IV space.

And I've been an investor, uh, started investing, um, maybe in 2009, I think was the first investment. And I've done about 15 investments and deployed, uh, about $150 million of VC capital. And, uh, all, all, again, in developer related businesses.

I, I think there's just something interesting about dev platforms. Very cool. Hey, time out.

Tyler. Are you expecting someone in here? Jack Bar Barick, something?

Uh, no. I mean, it's probably the pr PR person, so he doesn't, you know, you can, Should I let him in or just ignore him? Uh, you can just ignore him.

It's fine. Yeah. Yeah.

I tell them you did it. I didn't. Okay.

All right. Paul, we, we took a little break. Just mention.

Okay. You know, Tyler, you're, you're being humble, but Yeah. A little bit, a little modest, but yeah, you, you, you've, you know, the very kind of definition, a serial entrepreneur and startup guy who has been at boat, you know, at the board seat level as the investor to the hot seat level as the CEO founder, right.

Trying to make it happen. And, and you've had a tremendous amount of success. Kudos to you.

Thank you. Um, I remember what the first interview I did with you when you first joined aca. 'cause ACA was a company I didn't know.

Yeah. I'll be honest. You know, you, you made me aware of them.

Make our audience aware of aca. Give us the ACA backstory, Tyler. Oh my gosh.

Well, the company is now almost 20 years old. We're just, yeah, just shy of that. Started, uh, by our founder and CTO Jonas Bonnet.

He's out of Stockholm, Sweden, of all places. And, uh, it was originally named Type Safe back in the day, and then it became known as Light Bend, and then we rebranded to aca. But ACA was an open source framework that Jonas invented, uh, to make it simple, to build concurrent applications on multi-core compute.

And, uh, 20 years ago, that was a really hard programming problem. Uh, it required almost a graduate level of computer science. And he simplified it, uh, using some 1970s computer science called actors.

And the framework became wildly popular. Uh, it's been downloaded a billion and a half times. There's over a hundred thousand systems that have been built on ACA on any given day of the week.

2 billion people use an application that has ACA under the covers. And, and what it does is it's a distributed system programming framework that pushes your logic and data out into the application, and it allows the application to decouple itself from its underlying infrastructure. And when it does that, it inherits these properties that allow it to adapt to the unexpected.

And so when there's a network disruption or a hardware failure, or a burst of unexpected user activity, the system, the ACA system knows how to adapt to that. And as a result, our clients build systems that get, um, uh, no downtime. They have like six nines of availability, massively numbers of concurrent users, huge data pipes as in like petabyte scale of data processing and synchronization.

And, um, and it's been used. It's, it's basically battle tested and hardened. And over the last number of years, we've, um, been transforming the company from an open source development framework to a, uh, platform, uh, that we now sell to the chief AI officer, an AI platform, uh, for, uh, building, uh, building and managing, uh, complex agen AI systems on that.

Why am I not surprised? You know, you, you, uh, went there and, and, and got right into the heart of where we are now in the world, and, and it certainly, what an exciting time. Well, it was, You probably sit there going like, well, how, how do you make the leap from distributed systems open source programming to, you know, well, I said it, I'm not surprised if anyone's gonna do it, Tyler's going to do it.

But yeah. Tell us how, well It turns out, I mean, uh, uh, of an agentic AI system, you know, where you're gonna unleash a swarm of agents to solve problems on your behalf, that is a distributed system. You, you know, you've got these agents that are talking to each other over a network that is a form of coordination, and they're sharing context that is distributed state.

So, uh, uh, Jonas didn't realize this, but he has been building an AI platform for 20 years. He just didn't realize it until ai AI came and knocked on his door. Unbelievable.

Right place, right time, man. Good for you. Thank you.

So, of course, the stuff we, you know, we're, we're playing with the Genix here in, in Techstrong. I'm, I'm really, I tell you about it off screen, but I'm pivoting the whole company around agents doing a lot of the dreary work. Mm.

Right. The, the, the nuts and bolts of taking videos and editing and posting and descriptions and, you know, all of the stuff that goes with that. And around our webinars and our newsletters and content.

You know, it's silly not to just as you would Tyler. Absolutely. You guys recent, go Ahead.

We, we, we ourself have been, um, uh, a huge embrace of, uh, ai, AI first, um, task work, uh, particularly in our engineering org. And our engineers, uh, have really kind of encountered, uh, sort of two, two realizations. One is, uh, they're about four times as productive as they were a year ago with it.

That that is, you know, just stunning. And most of that productivity has really happened in the last few months. It seems that, it seems like Claude Code every three months is doubling in its competency here.

It's, it's really remarkable. I, Yeah, I agree. Yeah, November, December, I think was watershed and not just Claude Code Codex too.

I mean, to give them their fair share, right? Claude code, I think is the developer's tool of choice, but, but OpenAI codex around the same time also made a bit of a leap. Made a bit of a leap.

Yeah. I mean, and they're, they're, they're obviously all, everybody's learning from each other, uh, on this. Oh, yeah.

And that, that is somehow accelerating the flywheel effect that's going on with it. But we, we actually have this sort of second realization that, that has happened for us, which is there's a, a cognitive overload that, that, you know, a lot of the people on our team are dealing with because we're now doing so much work, um, uh, you know, within an hour that they're, people are struggling to try to figure out, well, how do I just juggle doing, being able to do this much work and staying on top of that? Right.

And so, uh, you know, the people who have A-D-D-A-D-H-D in our group are having a ball of a time. Everybody, everybody else is like, okay, I, I'm having a hard time managing all this. I just try to keep all of my sessions, you know, in, in some sort of order.

'cause I, I hop like, yeah, I, you just described my days. Tyler, um, hey, you guys recently though, engaged with a company called Manulife. Uh, I, you know, kind of, we wanna call it a case study, an engagement, a customer engagement.

Yeah. Uh, let you know, let's hear about that. Well, Manulife is one of the world's largest insurance providers.

Uh, they're based out Toronto, uh, Canadian company. They're, uh, they own, uh, John Hancock in North America. Oh, okay.

So John Hancock is, is kind of, uh, their North American insurance operations. But, but Manulife is a global beast. Uh, they, uh, they operate in 30 countries around the world, uh, you know, and a quarter, a quarter of their profit comes out of Hong Kong and mainland China.

So they've got a massive presence in, in Asia and their, uh, chief AI officer and their, uh, chief technology officer is leading their company through an AI transformation. And, and not just ai, uh, on the productivity side for employees, but they are rebuilding most of their IT systems to be a agentic powered on that. And so they needed to lay down a platform for what will be over, uh, 2000, uh, developers and data scientists to have a consistent, repeatable way to build agen systems and then, you know, get them into production safely, given the very strict regulatory controls that they're under.

And, uh, uh, they partnered up with us, uh, Deloitte and Microsoft, and, uh, arise, uh, and, uh, to basically deliver this platform. And ACA is the agen, the agentic runtime. And we're deploying ACA in over 20 regions around the world and in, in a live ha DR configuration.

So that what you can do is these agentic developers can come along, they'll use cloud code to design, uh, a complex syngen AI system. It will test it, and it will be able to deploy, uh, into one of their regions. And that region will have the active, active replication to other regions so that it has full HA and DR so that, that you can, they'll be able to run, um, run these agents all around the world and they'll never, they'll never fail sort of thing.

I love it. I love it because you, this is what we're short of right now, we're short of real life stories of not just people tinkering. Like I consider a lot of what I'm doing here, still at the tinkering stage.

Yeah. I haven't quite, I haven't quite industrialized it. You, You, you know, I, I would, I would agree that a lot of, a lot of AI is still in the personal productivity space.

Uh, we, we, we are focused on enterprises and, and particularly enterprises that are in heavily regulated environments like banks, uh, health, healthcare industry. Um, and, and when you're in those heavily regulated environments, there are very, very tough, uh, bars that you have to, uh, pass on terms of AI reliability on that. Um, and, and you know, it's, it's kind of funny.

That's, despite all the hype that you hear on ai, when we engage with enterprises, most enterprises are exactly in that spot, which is they know that there's something powerful here. There's, they know there's something they need to do, but they're not quite sure what to do. And they're, wait, they're waiting to see some of these enterprise stories come out the door because they're, they're like, and we wanna see what was successful and what wasn't successful.

So they can model that and mimic that. But Isn't that the way it's always been, right? That, that the, the crossing the chasm model, right?

Yeah. The 30 and, and let me see what my peers are doing. Let me ask you a question, though.

One of the things we're running into, and we're hearing a lot about is security around these agents, right? Yeah. We're, we, we've installed some agents and as I, as I mentioned to you, we're, we're doing a lot of things.

Now, we're part of Futura and the Futura IT team, I asked, I went to them 'cause I didn't want to do it as a skunk works. I said, Hey, we're using these agents, I wanna make sure we're in sync with any security policies that you may have. Yeah.

They didn't have any. So they went to the AI and said, what are good security policies for using an agent? Yeah.

And of course, you know, AI could be ose. Oh yeah. It gives you, gives you a huge dump.

Yeah. Uh, and I'm looking at, I'm saying I could see, you know, I, most of them make sense. They're kind of commonsensical.

Yeah. Some of them I think are wearing belts and suspenders at the same time, not necessary. What are you seeing, Tyler?

You, you're, you know, in highly regulated industries. I mean, that's security's job one there, right? Yeah, yeah, yeah.

And you know, you, you frame it as security, but the way the big enterprises look at it is it's a, a risk management concern on that all Security Is, and, and, and risk management is actually, uh, in some cases a legal, a legal function rather than governance, security or InfoSec where they're just looking at, you know, kind of the, uh, the strict isolation of it all. But, uh, and it was kinda interesting when we, when we filled out the RFP for manual left, 'cause there was an RFP process. The old classic one, the, the security and risk management questionnaire was 360 questions deep.

Oh, Jesus. I mean, it was, it was, it was, it was very serious. And so what, um, the, the, the way, the way I kind of frame this for, for people is that you have two obligations.

If you're going to de design an ag system that's gonna run in your enterprise, right? You need, uh, one, you have to have a system that, uh, self-explaining, uh, because your, your number one regulatory requirement is that, uh, every decision that the AI makes has to be, uh, expl, uh, explainable. So you have to have chain of thought reasoning.

Uh, you have to have, uh, immutable tracing. So you have to be able to trace all the interactions that took place. There's a, there's these things called interaction logs and intent based logging.

You gotta do. And, and there's this sort of causal, causal analysis for that whatever decision was made, whether it was a good decision or bad decision, you have to be able to trace back to where did it go off the rails? Like if it went off the rails, at what point and what caused that.

Um, and, and furthermore, as part of that, you have to capture, um, all the access controls that every agent had at any point in time because agents are, uh, not a reflection of the user. An agent is its own identity associated with that. And so these agents have these sort of dynamic, constantly changing access rights.

So on the self-explaining part, um, there's just all sorts of things that you gotta do. And that's a regulatory requirement. Then, then you want to have a system that can self contain itself.

And so a self containment system, one is, you know, at an infrastructure level, it needs to be kind of a zero trust and penetrable network on that. Um, so that you can't have any sort of outside actors influence it. Uh, but then you, you've gotta do the basics where you have guardrails and, uh, sanitizers, like PII sanitizers associated with it.

But then ultimately where it lands at the end of the day is that since you have, uh, these sort of teams or swarms of agents that are independently making decisions, you have to put a a, uh, basically a policy enforcement engine that teaches the swarm on how to contain itself. And so that you can layer down all kinds of policies. They could be ethical policies, cost policies, behavior policies, whatever that may be.

And the swarm then takes an obligation, a contract among itself to make sure that those policies are never breached. Or if they are breached, then what is the cure, uh, associated with that? And so, so if you, if you look at the system and those two lenses self explain and self-contained, then you have addressed the security problem that, that, you know, and you're gonna pass regulations.

I all, I love it. Tyler, I could talk to you about this stuff all day, but we're only supposed to go 15 minutes. We're probably overtime.

I apologize. That's all right. I'm in Puerto of Vallarta where we just had, you know, that little experience with the cartels a a week.

Oh my God. Yes. Well, thank God you're okay.

I told you my first interview this morning got cut off because of an error. I, uh, and of a, a, you know, a, uh, a bomb shelter, uh, warning, now you are in Puerto of, and geez, I'm glad I'm sitting home in Boca, man. You, you, you know, it was really what we have in breakfast, you know, and it's in part of our, it's just a lovely place and it's, we're backing back to our, our condo and you know, there's some guys with machine guns and ma and masks and they're just setting these, all these vehicles on fire.

Hundreds of them all over the place. Oh my God. And I have to tell you, they were, that, they were the nicest cartel members I think I've ever come across.

Yeah. 'cause they were, they were making sure to get the public out of the way. They weren't doing anything threatening you.

You know what, you gotta honor among thieves. But there was honor Among We Hey, be careful, dude. Who, who am I gonna talk to?

Come on. Get, get home. Be careful, please.

It's a, it's a beautiful place. It's very safe here. Yeah.

0 very. I is, it's, it is beautiful. And it's a shame, you know, I wrote an article why we Can't Have Nice Things.

It, it's, there's so much good in our world right now. There's so many exciting things. And then you get things like wars and cartels and violence and all the rest, man.

Anyway, Tyler, it's good seeing you. Keep up the great work. Come back on and keep us posted about what you're doing, please.

It's been too long. Take it easy, Alan. Alright.

Tyler, Jules, CEO of Vaca here on Text Drunk tv. We'll take a break. We'll be back.