Techstrong TV May 30, 2025

Hey, everybody. AI blackmail is a thing after all. Stay tuned.

You're watching Techstrong. Hey, folks, we're back and we're talking about the top topics of the day on a happy Friday. I always have the same reaction Every Friday I wake up in the morning and I go, thank God it's Friday.

And then about three seconds later I go, holy crap, it's Friday. But here we are on Friday with our gang members. Let's start out with Lisa Martin, how you doing?

Good to see you. I, I assume you're in Northern Cal still? I am.

I'm in Silicon Valley and I'm home in San Jose, doing well spent last weekend in hot Vegas. My nephew graduated high school, so that was fun. It's definitely not as hot here in San Jose as it was last weekend.

All right, John, I see you also appear to be home. Is this I am at home. Um, and I, I am gonna go to Las Vegas for a couple days next week for this Zscaler conference, so it's gonna be hot.

Um, I was gonna tell you, Mike, when you mentioned the, this kind of, these tremors about Friday, I'm getting 'em on Wednesday nights for some reason. Wednesday night is the big, uh, the big conflict that night or day for tech and politics, it seems, seems to be a trend. We'll talk about that later though.

Is that like happy hump day sort of, I don't know. Yeah. Yeah.

You haven't been good way through the week. We're just gonna dump all sorts of decisions on you and, and create all sorts of conflict, and it was coming fast and furious Wednesday night. All right.

And then finally, Fred, where are you these days again? I forgot. I'm holding it down in Seattle.

Uh, not sunny as maybe, uh, Silicon Valley might be, but, uh, we like it that way here. Keeps, keeps California's in California. All right.

And for those of you who are tuning in for the first time with Fred, he's a new member of the gang, and he's one of our resident cybersecurity experts who we'll be getting to that topic shortly, but let's jump into this first bit where, um, Andro put together a research paper highlighting how Claude Opus four AI essentially tried to blackmail a bunch of developers that were trying to take the system offline. Um, it was, I mean, bless their little hearts, it was nice them to share all this stuff, but they, and you've been following this whole thing, it's kind of feels very much like a plot right out of a science fiction film. It does, yeah.

As you mentioned, Mike Anthropics new AI system, this is Claude Opus four has shown really concerning ability to threaten blackmail, even against, as you mentioned, its own developers when it was faced with a replacement. The company, they've, they've taken steps to test this, to evaluate it, to look at the safety and the risks. They've been transparent.

So I applaud Claude Parent Anthropic for being, um, transparent and kind of acknowledging, Hey, there's risks here. They publish the safety report that you talked about. They're really recommitting, I think, to responsible AI development.

This is not unique though, to Claude Opus, four other AI developers Open. AI's had this, Google's had this, and they're working to address similar, um, concerns. And I think while the news may seem alarming, it's important to recognize that Anthropic and other AI developers, they are actively working to identify, mitigate potential risks.

And hopefully down the road, this will ensure that other AI systems are developed and deployed responsibly. Fingers crossed. Oh, John, I'm not at the point where I believe that AI is a stent and being, but, um, it does seem to be exhibiting some interesting characteristics here that I would argue we're programmed into it.

And part of that programming went into the sense of, Hey, we're trying to be overly helpful. So sometimes these AI models are a little annoying, but then on top of that, maybe, you know, in the programming somewhere, is this sense of self preservation. I mean, what's your take on what's going on here?

Yeah, that, that's interesting because the scenario that, that Lisa alluded to is, is really interesting and talk about self-preservation, right? We have this, this situation where Claude Opus for is put in this virtual workplace. It's the assistant in a corporate setting, and it's, it's informed by this, this mock email that it's gonna be replaced by another AI system.

And it's told this by specific engineer who's responsible for the situation and, and the decision. So the model has this insight into the engineer's personal life under this fake scenario. And, and the engineers allegedly is involved in an extramarital affair.

So they, the model threatens to expose this person if it's replaced. And, and, and it's interesting, not only the self preservation and overthinking and taking pieces of information and using it to, to its own advantage for the model's sake. Um, and again, I, I give philanthropic credit for at least, uh, publishing these results because it's turns out a lot of these safety reports are either being delayed until they're forced to be disclosed.

And I think there was a, there was an instance invo involving open AI where, um, oh three reasoning model sabotaged a, a shut down mechanism to prevent itself from being turned off. So it's happened before. Um, it's, it's interesting, Mike.

It is like a science fiction movie. These, these things are moving faster and smarter than, than the developers even probably would care to admit. And I think as we see these, more of these models being developed and being developed smarter and faster, you're gonna see more of these scenarios, envelope and, and, and develop.

And I, I'm wondering, I'm hoping that these safety reports, which have been controversial in and of themselves for not being forthright and being, um, being timely, uh, are, are forced now to kind of be upfront about the potential problems. And I, and again, ARO gets credit, should be credited with at least being upfront about this. Agree.

They've cl they've classified it as an ASL three system. I guess that indicates a higher risk of misuse. Yes, yes, yes.

So they, at least they classified, they didn't wait until they were, they were forced by an embarrassing disclosure, which has been happening with other models. F Fred, I wanna highlight something that John just said, though for a quick second. Um, the AI model thought the developer was having an affair and was gonna blackmail them using that information as we go along here with AI in everybody's life and has access to every system, won't that AI model get access to all kinds of sensitive information?

And might that not be used against folks in the future? I mean, what is the security implications here? A hundred percent.

I think the, the big thing that we're talking about here is a, a set of, uh, moral categorical imperatives that have to be implemented, coded. If you look at oas, uh, designations around the top 10, you know, concerns around implementing ai, this is not in any of those, right? If you talk to folks that are looking at how they're going to implement ai, it's not in any of those dialogues.

There is a societal need for us to decide what it is that we want this to be. For us, the security risks are, are obvious, right? In this particular case, if you look at the how, 9,000 right from, you know, 2001 a Space Odyssey, right?

No thanks. I'm just, you're potentially going to affect some outcome for me, the ai something or other, it's not in my best interest, therefore, right? You gotta die, Dave.

That's, that's how it's gonna be. Now, obviously, that's quite a bit of hyperbole, but the real risk here is that we don't understand all of the adjacent implications, and we have it applied our moral categoricals, uh, to the way that we think about this problem space into how we, uh, program and or influence ai. And so I love the fact that we're having these safety and security reports, but the challenge is, if you look at the spin around the report, oh, well, it's okay.

Most of the models have the same problems. That's the big deal. 86% of the, uh, occurrences were examples of blackmail, 86%.

And that's acceptable. That's not acceptable. So I, I, I guess it's huge.

You, You mentioned mid 80%, mid 80%, uh, the instances. And you know, the weird thing Fred too, is that you're right, they, in a sense, they kind of papered over the conclusions. 'cause if you read the conclusions of that report, it basically, they say, well, this is an anomaly for the most part.

It's fine, don't worry about it. Until, of course, they come across maybe another instance or something else happens. So in a sense, they're, they're kind of brush a little bit, brushing it aside and patting themselves on the back for disclosing it.

This, this is the part that makes my head wanna scream. So, once again, we are building something that is fundamentally insecure, and then we're gonna walk around and say, well, we should put a bunch of policy guidelines around it and build all kinds of products around that thing instead of actually going in and making the thing that we're actually building more secure in the first place. Fred, are we incapable of learning?

A hundred percent. We are incapable of learning. We have a great set of tropes laid out for us that are hilarious to watch us watch us run through, uh, the secure by design notion, right?

Something as it is applied to ai. Clearly when we think about the requirements for Do No Harm, right? That, that, as we walk through these examples and we see that 80%, 86% of this would be doing harm, is that, or is that not a reason to say it?

Let's take this back to the woodshed. We need to probably retool this thing instead of saying, Hey, it's available on Amazon. You know, you can go hit it up in Bedrock and ask, uh, ask for access to this, and then tie it into your MCP servers, and then has access to everything and see what happens.

All right, so Alan's not here, so I have to bring in the whole Star Trek lore thing myself. But, um, as, as that plot line evolved over the years, there was this AI that, uh, federation had built that eventually they wanted to turn off, but then it escaped into various systems. You couldn't find it.

And then that AI apparently became the foundation for creating the Borg and everything that came through that. Lisa, are you at all worried that, so not only would the thing have ultimately decide to blackmail somebody, but would it just replicate itself and hide somewhere and our highly distributed IT environment and just kind of sit there late until something else happened? That's a really good concern that you have.

And I agree with you on that, that it could be kind of hiding in plain sight. Um, I think from a messaging perspective, we've, we've kind of all applauded, um, anthropic for being transparent here, as transparent as they want to be. But I think that it's a, it's a relevant concern that needs to be probably addressed a little bit more transparently, a little bit more further to understand what are the implications?

Could this be in the background spying on us? Could this be actually blackmailing not just developers, but customers of businesses? So I think it's definitely a red flag that needs to be pursued further.

And probably, I think to Fred's point, more transparently, more transparency is needed because the percentage of blackmail is so high that they can't ignore that. I ho I would hope So. Print and another homage to another science fiction movie.

But we have Blade Runner, am I gonna have AI hunters suddenly going around, poking around, looking for rogue ais? That's a great question. I think the, or a agentic model is going to be a case of you have agents that do a handful of things.

You're gonna have your, your Deckers, but they're probably gonna be agents too. And in that case, I think it's gonna be holding, holding, uh, AI accountability to AI with ai. And I, and I think that'll be the interesting, uh, the interesting story in the next couple of years, how big and how much, and how frequently.

You know, we run into those, those things where models can train themselves based on feedback they're getting from, you know, ag gentech, uh, uh, ag agentic analysis of what's happening in the agent to agent conversations. Okay, let me follow that through a little bit further then. So now I got a AI agents chasing AI agents.

Will any of the good AI agents eventually get compromised by the bad AI agents? Maybe, you know, like You, a lot of subterfuge going on here, right? There is gonna be spy versus ca spy versus spy, like mad magazine type of scenario.

Yeah, it's, it's a good question to see if we'll actually see the matrix play out. I mean, that's, that would be interesting. I'm not sure.

I mean, uh, so much of that is unwritten also, again, the structure around how any of those agents respond once they've sort of developed their own reasoning and rationale, right? We don't tell them how to do the job. We tell them what the job is.

And if without, you know, some, some of that fundamental categorical, you know, moral, uh, compass things that we give humans that we understand and, and we have intuition about, and, you know, our, our parents raise us with values and so on and so on. Agents won't have those unless we inculcate agents with those things. We're gonna have a whole bunch of questions about whether or not what is good, what is bad, and, you know, that definition will be something, you know, beyond the realm of just what we told them to do.

I think that will be interest. The interesting story, All right, moral values, what a quain idea. Um, Lisa, um, what's your takeaway from this?

'cause I would argue maybe that this is, uh, an object lesson and maybe let's not create overly complicated ais, and maybe let's just focus on small ones that are trained for a very narrow task, that do something specific, and they're not gonna go out and try to blackmail people because they're not trying to be all things to all people. They just have one job and they do it well. Yeah, I think that's a great point there in terms of focus.

Um, every, every company has to have an AI story. We, we talk about this every week, every day, and so companies are working fast and furiously, and maybe it's too fast, um, to, for, for our own good, maybe what, what we should do is step back and focus. I don't think that's gonna happen because everyone is in this race to have the best system, the most intuitive system, the most sentient system.

But I think we would benefit if folks slowed down a bit and really focused these models, the training to make sure that they are in fact transparent, that they are free from bias. I think that's a, that would be a, a great movie. I don't think we're gonna see that.

I think, I think the fast and furious acceleration of AI and tool development is gonna persist in, in well into the future, I guess. But John, don't you feel like, you know, the entire IT industry is conducting a massive social experiment on people without much of their input as to whether or not that's a good idea and they're just kind of going for it? Yeah, you know, I remember that the whole, uh, philosophy of Facebook make it as fast as possible.

If it's, if it's broken, fix it. That's the same mentality, except multiply that by a thousand with ai. And I think about the reasoning models, and this is kind of where we, one of the, the, the alleys we go down, I think we also have to think about like a moral elements to the, the models itself, or at least limit them in what they can do.

It's, it's, I mean, it, in a weird way, you mentioned earlier, this is these companies or these industry propelling fast as as fast as possible without thinking about the consequences. And I think about the auto industry, and I think about we need a Ralph Nader type in the AI space. Somebody point out all these flaws because this is gonna, actually, it's gonna get worse, I think because so much pressure.

And like next week, I know of at least four major companies making agenda AI announcements. Um, they, they, they, they're, they're gonna worry about the, the collateral damage when they come across it once they encounter it, and then they'll try to try to address it later. I think for now it's just, just get out, get out as much as you possibly can, do as much as you possibly can to sell this idea and sell your concept and not get left behind.

And let's worry about the consequences later. Fred, is there such a thing as morality, as code? Can we code morality?

How does that work? Uh, I'd love to think that there is, I'm not, I'm not sure, uh, I, I don't think anyone's incented for that purpose, right? These companies are gonna implo if they don't come out with the latest next greatest, uh, whether you're a startup or, you know, you're a Palo Alto Networks, right?

The requirements are clear, the market has spoken, and the illustration of that is the, you know, nuclear arms race we're going through to publish models with more, faster, better with, uh, more connections and, and, uh, more tokenization and all of the things that go with it. And, you know, the worry is right, if you, if you listen to, uh, you know, philanthropic, you would also, you know, hear there's another subtext in here, which is, you know, the, uh, the white collar workers, that entire environment, that entire ecosystem they suggest is going to implode as well. So you have a number of really important things that are coming to bear as a, as a function of ai.

So when we think about whether or not you can put that you, you, you can program in sort of the, the moral strategies of do no harm, and the rationale behind the way you think about that, uh, as a programmer, I, I, I don't know, I would like to think that's the case, but I haven't seen, seen a ton of examples where that, and also I might be more stoic about it given, you know, history and security space. Like that's not really all that important to people until it's so important. You can't turn it back and put the genie back in the bottle.

All right, folks, I think I'm gonna end this conversation here, but when you go to sleep at night, just think about all this and have those pleasant dreams because God knows what's gonna happen next. We'll be back in a minute. Hey, folks, we're back and we're gonna talk about chips, Trump, Washington, and the hits just keep on coming.

John, the latest reports are that at least reportedly we're thinking about, uh, holding back the chip, making equipment from China. And of course, Nvidia is talking about now building chips in China, and now we have a court who's saying, well, this whole tariff thing may be for not anyway, because the president achieved his authority, but, um, can you make any sense of what's going on here? It's getting a little crazy.

Yeah, it is crazy. You know. So, uh, we refer to these as news dumps.

Um, there were three stories that you mentioned, Mike, that all happened within hours of one another. And interestingly enough, they all happened the same day. I believe that Nvidia announced its results on Wednesday, as well as synopsis, which it puts synopsis in a very weird situation, which I'll explain later.

So it kind of starts out, we'll, we'll go, we'll go in order of, of events. So there's a financial time story that comes out late in the afternoon about how the, uh, commerce department, uh, the BIS within the commerce departments has, has reached out to, um, these chip designers and told them to halt their sales in China, specifically, the three companies that mentioned are cadence synopsis in Siemens. Um, th this is not verified by the companies.

They kind of skip, they kind of dance around whether it actually happened or has happened yet, the commerce department's very vague and sinister in the way it describes what's going on. The idea, of course, is to limit China's advancement in ai. But the problem is, is when you're doing this, and it's not just a Trump administration, this went back to the Biden administration, you're trying to figure out a way to slow China's advances in ai.

The problem is, in the, in the process, you hurt the US chip makers or the companies associated with that field. And, and just to underscore that point, I think 16% of synopsis's annual revenue comes from China, 12% for in the ca instance of cadence. So these companies are being hammered in terms of their stock.

The synopsis, CEO is asked during a conference call with analysts about this report. He, he can't really answer the question because he is being told by the lawyers not, not to say anything. At the same time we have, uh, Nvidia announcing its results.

And, um, they, they are saying that to skirt these export controls, they're gonna produce this lower performing, lower cost GPU chip for sale in China. And then to top everything else late in the night, there's a US trade court that blocks most of Trump's tariffs saying that he exceeded, overstepped his authority and imposing he's across the board duties on boards. So it, it's, it's head spinning, but it all comes back to this, the chip industry is being used.

And I hate this, this, I don't mean this as a pun. It's, it's, it's a bargaining chip for, for Trump. He's using it to, uh, uh, as assert his authority over these companies like he's doing with Apple and his tariff threat there.

We talked about this yesterday, and he's gonna use this as a political football. We're gonna go from point A to point Z to point L. Things are gonna change daily.

There's gonna be no rhyme or reason. And I think, as Terry mentioned yesterday, eventually the markets are just gonna start ignoring some of this stuff. Um, I mean, it is gonna continue and there's no, there's no logical end or logical train of thought.

It's all just scattershot. So I think we're just gonna have a, a sense of chaos, which is what he's all about. And and unfortunately for the tech industry, and especially at this time in the tech industry, he's gonna be meddling.

'cause he knows he can exert a lot of, a lot of influence as these companies are, are stumbling over each other to, to, uh, advance in ai. It gets better. Two senators sent a note to n video wagon the finger about how, uh, you know, they shouldn't be building chips outside the US and, and China.

'cause it's not in our national interest. So everybody's piling on. Senator Warn.

Yes, I just saw that. I just want that. So it's, it's, I mean, it's the thing to do, right?

It's the hot topic. Before it used to be social media, now it's ai. This is a way to gain attention, to gain some sort of power if you think you can.

Um, it's, it's just, it's, it's just the in thing to do. And, and unfortunately tech has become intertwined with politics to the point where it's almost, it's, it's, it's overkill. All right, So Lisa, it seems to me that maybe we should think more like how the Chinese might view all this.

And two things come to mind. One is, well, clearly they're probably trying to figure out how to reverse engineer various processers. So they need access to the chip making equipment, which they are also probably trying to figure out how to reverse engineer right now and go build themselves and not be dependent upon us, because that was part of their master five-year plan that they put out anyway.

So we knew this was coming one way or another, I guess. And at the current rate, we probably won't have this card to play very long on the assumption that they're gonna go figure out how to do that. The other thing is, um, not every AI workload, as we saw with deep seek and everything else needs to run on a state-of-the-art GPU.

There's a lot of other processors out there that can be used, including, you know, Google has the TPUs and everybody else has all these alternatives. So, um, you know, how how real versus an empty threat is this? That's a great point.

I think, uh, what John said, it, it's really, I don't even, I it's chaotic. Um, we're gonna go from point A to Z to L to M to Q in a, in a, in a, just in a, maybe it's even organized chaotic fashion. Um, I think that what we should be doing is focusing to your point, Mike, on what workloads can run on other processors and start working on that and focusing there versus, like John said also that this, this tech and politics are now so tightly intertwined.

The message is, is confusing for organizations from the nvidia, the synopsis, the cadences. And I think that we're not gonna see a, any organ or any organization anytime soon. But why don't we start focusing on workloads that can run on different processors and focus work there and see what are some of the great use cases in AI that can come out.

And they don't have to be run on GPUs. Uh, GPUs, GPU is just the poster child right now for this geopolitical conflict that is, um, maybe a bit overhyped, but I don't see it going away anytime soon either. Well, about once a day, my wife reminds me of the phrase, you know, mess with the bully and get the horns.

So Fred, let's talk about the horns. Um, what happens when the Chinese do get these advanced capabilities and then they start making advanced chips and they start selling that around the global marketplace? Is the entire semiconductor industry gonna go the way of the US car industry where, you know, overseas we can barely compete with China now?

I think that's the truth. Uh, and the question is when, uh, maybe not whether, and one of the sort of the milking the last, uh, bit of capability out of the market before we know that to be the case is the same thing that, you know, Facebook has done historically, although they probably led a little bit more into influencing that outcome than, than benefiting from it. And I mean, I would expect Nvidia to be no different, right?

There, there isn't this, you know, I'm not sure why I'm the moral categorical guy today, but today, uh, add on and say that. And so if you said that capitalism had a more, a moral imperative to do the best thing for United States, uh, that, you know, that horse left the barn a long time ago. And so NVIDIA's gonna eek out as much as they can and they should, uh, by all rights.

Um, and then the influence that China will have, right? We're already seeing that in a number of other markets and the waning of that. We could certainly have a long discussion about the South China Sea and, and or Taiwan with respect to that.

And then also there are mineral deposits around the globe, but the, the influence is pretty clear. There's a limited clock here, and I think they're just trying to make sure they make full use of the bull ride. Lisa, do tech companies that are inherently multinational have an obligation to the United States or not?

That's a good question. Um, I wanna say yes, but I don't, I don't, I think the answer is not necessarily, and I think that's something that we're gonna see play out, especially if this, as this issue persists and gets bigger. And to John's point, the bargaining chip becomes just so, um, clearly a challenge for organizations that going forward, what else are they gonna do?

Why, why should they be beholden to the US if the US is going to try to force fit a function that doesn't seem necessarily right? Um, I think it's a, it's something that we're gonna see play out over time, and it's gonna continue to be cattywampus and, and, um, asynchronous and organizations are probably going to have to make some big decisions on where their loyalties lie. And they're gonna, they're gonna follow the money for sure, but I think they have to be really looking at where their loyalties lie based on what's happening and, and what will continue to happen down the road.

John, you're going to Vegas this month, as you know, what are the odds that some of these companies start to figure out? Maybe we'll just move somewhere else. It would be a lot easier to move the corporate headquarters than it would be the deal with everything else.

Yes, yes. You know, in a sense, I think you're right. I think you're right.

I think that's the most, that's the logical step, and I think that it's been done before another industry. So what's to stop the tech industry from doing it? Um, and it says, you know, one thing I was, I wanted to mention, I think Alan has talked about this, is just this, uh, going back to this court order, uh, uh, to, to, to cease the, the, this, this tariff policy, I think Ellen mentioned, you know, you can't, like a sitting president dictating or, or trying to an authoritarian way tell these companies what to do, you know, and imposing a tariff on them unilaterally was just absurd to begin with.

And, um, maybe then these companies start thinking about this idea, you know, if we, if we shift some focus or shift operations, and it's been done for tax reasons, and why can't it be done for manufacturing reasons or policy reasons, some of our operations overseas, why not do it? Especially since this guy is not gonna be in office for for much longer, a couple more years. Um, it's probably gonna happen.

Um, and that might, that's, that's a story that, that, that bears watching, you know, and is a theme that's gonna, that might surface, right? I mean, to your point, the insane part of this thing is you're basing all of this on an interpretation of a law that doesn't clearly say that you can do what you're about to do, citing that law, and then you're gonna go and actually act on that, not just on a test case, but you're gonna do it broadly across entire industry segments. And we're worry about where, pardon the pun, the chips fall later, you know, that's just insane.

And so, um, Fred, do you think that, you know, as we kinda look at the whole helm here, do we just, does somebody need to step in here with a little more adult supervision? I think we're mixing strategy with tactics right now on policy, right? And that's, uh, you know, I, Lisa made a good point, John as well.

It's chaos. It's not even sort of, uh, you know, thoughtful chaos. And the challenge, I think is a long-term strategy.

So if, if you allow, uh, uh, an elected official, whether it's four years or it's six years, or it's eight years to drive strategic policy for the United States, and you don't incorporate as a, you know, advisory board, all of the folks driving, you know, the economic growth of the United States, then I think we've missed a few of the important points in order for us to characterize a 20 year plan of how to be great. And in this case, I think we're actually, it's backbiting behavior that has those same implications you talked about, which is, Hey, do I really need to have my headquarters in the United States? I'm big enough now, I'm multinational, I can go overseas, it's no problem.

And you know, folks want me to do business over there? So those real concerns are not being addressed, uh, when we, when we start talking about policy as tactics. And I think that's, uh, that's the real risk we run here.

All right, folks, I'm gonna end this conversation here, but just maybe just maybe somebody in the White House is playing checkers when the rest of the world is playing chess. We'll be back in a minute. Discover Techron Group, the epicenter of tech innovation.

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Hey, folks, we're back with part three of our morality play. See, there is a theme when you think about it. We have a report now from the FTC has sent an order over to GoDaddy, not quite clear how much they can enforce this, but basically detailing all the issues they have with security.

And Fred, uh, to me, when I read it, it kind of felt a little like public shaming, but, you know, is this what we need to have happen from here on out, or what I think what GoDaddy has done over the course of its existence. This is a, uh, this is an outcome that was super predictable, and if you are a GoDaddy, uh, user or a customer, you would advocate for this 100% to be the case. Starting back in 2018, allegations about whether or not, you know, Godad had followed not only an appropriate security policy, but also whether or not they misled their constituents and saying that they are secure under, uh, under the auspices of, you know, privacy shield and some of the regulatory requirements.

You know, the FTC has said, Hey, look, um, there's a number of security failures that you guys have persisted that have led to a number of breaches. And, uh, Lisa, I saw you nodding. You're probably a GoDaddy.

I mean, 5 million people are GoDaddy customers. I'm A customer. Yes, Exactly.

And so we know, right, that these sort of, uh, behaviors have been ongoing and it feels very much like a, uh, you know, a slumlord behavior, right? When we go through this. And so it proposed some requirements here.

Um, and, and I want you guys to think about this and, and I'd love to hear your thoughts, is when you, when you talk about what some of these proposed requirements are from the FTC, do these sound incredulous to you on things that are required to do? You gotta hire a independent third party assessor who conducts, uh, you know, security reviews. You, you've gotta establish a, an information security program.

Uh, you've gotta understand and, and comply with security regulations. These are table stakes for every company on the planet. Yes, Lisa, I agree with that.

Sorry, go ahead. Is this, is this reality? Are we, are we looking at something that, that this is a mirror that we haven't seen before?

I don't, that's a good question. I was shocked when I read this article, one being a GoDaddy customer like you are too, you said. Um, but it, it seems like you just mentioned it, these are table stakes for every organization across any industry.

And how is GoDaddy failed at this so miserably, um, such that they need to put basic security measures in place? That's what it seemed like to me. Um, I think that maybe they are a poster child, but how many other organizations are in the same boat that we are not aware of because it's not being called out by the FTC or other organizations.

I think it's a glaring concern, but it also just seems to me, why aren't these table stakes in place? And how can an organization as large as GoDaddy and as seasoned as it is, have such glaring holes in their security practices exposing a lot of sensitive, potentially exposing a lot of sensitive customer data to a lot of bad actors that are out there. There's plenty of bad actors to manipulate data and, and, and steal data.

It's happens every 11 seconds or something like that. So it's, um, it just was shocking to me that a company of this magnitude has such holes, right? John is in me.

I feel like it's not like, you know, this is a cybersecurity mistake, and I kind of like said, oops, and we'll do better. This seems like a deliberate effort to ignore cybersecurity advice delivered by professionals and agencies, and to not act on it in the name of what greed. Of course.

Um, but you know, the, the, the thing that's the interesting thing to me is that the FTC strategically takes this action. Not so much be well because of what GoDaddy did, but because I'm sure there are other companies it has in mind who it wants to send a message to. 'cause I, I suspect that GoDaddy may, while egregious is probably part of the norm, uh, of this, is this type of corporate, uh, behavior.

So I think in, in the terms of the ftc, they're probably trying to think strategically and thinking how do we have an impact over what's happening broadly, not just across this tech company, but other companies. And, um, you know, one thing that also struck me was this, this, uh, tendency of certain companies, not just GoDaddy, to have the same security issues year after year where there's some sort of incident that always is traced back to something that happened earlier involving the same technology we've written about this, involving companies like Oracle and others who either ignore it or fib about it, or just, uh, try to appease the government officials they talk to or talk down to and, and try to convince them. And I, I think I, I have a flashback to, uh, Zuckerberg testifying, assuring, reassuring and assuring members of Congress who have no idea what he's talking about, that, that these problems will be addressed.

And I'm wondering if this is something that's been part of a dialogue between Godad and the FTC over a period of time, but I'm glad they took an action. 'cause I hope it sends a message. Brad, I feel like this whole conversation that we've been having around shared security in the cloud is kind of being more, is coming more and more nonsensical to me.

I mean, I'll agree with the fact that me, the customer has some responsibility for security, but I think the line keeps shifting as to how much the customer's responsible for versus how much the infrastructure provider's gonna do, which seems to be increasingly less and less. Or am I crazy? Uh, I think you're right.

And the risk here continues to grow because of the accessibility problem. Some of the things that GoDaddy is being held accountable for is what other people would consider table stakes and fundamentals for the last 10 years. Okay?

Multifactor authentication. Okay, this is neither a hard problem nor an expensive one in today's universe. And being able to monitor for security threats, I know for a fact that those guys have the tools.

And so when we think about that with respect to consumer data, I mean, I can sort of like, I mean, this happens to everybody. Uh, I don't recall the last time I got a GoDaddy notification for disclosure a breach. Um, and I have questions there because I, I know that I haven't had one, but it's this other part which is misleading consumers, not just in the we're secure, but also like the notifications and the behavior that happens afterwards.

You've seen some really good behaviors from folks that have been compromised year of late, full transparency, full disclosure, full understanding, and full explanation. And none of that has happened here. And so, irrespective of your lack of security controls, you've also failed on the corporate policy and the consumerism communication.

And so as a ciso, this is embarrassing. Not that the, maybe the current CISO has the, you know, been relegated to deal with this problem, but this is over the last seven or eight years, and it's systemic to the culture of the company. So public shaming, absolutely.

Please do. Please do. And, and is that the only tool we have, Lisa?

Because, um, frankly, if you look at some of the Supreme Court rulings, it would suggest that federal agencies don't have much teeth in terms of their ability to enforce a particular rule. So all they can do is send out this very large memo and hope that customers and shareholders get annoyed enough to do something about it. Is that where we're at?

It? It seems like it might exactly be where we're at. I think the public shaming is important here.

Um, Fred, you brought up some great points. This is, this is a systemic, and this is long been happening with GoDaddy that seems to be just blatantly ignoring a lot of the, the table stake security measures that need to be put in place. I, I question, do they even have a ciso?

I wouldn't wanna be that person right now, but I think the public shaming is gonna be important. Um, and like if they're the poster child, there's, and, and there's many more organizations that are in the same boat, I think that's okay. I think the public shaming should continue.

If that's our best measure of defense, then let's utilize that and make the consumer aware. I have not gotten, I don't think one email from GoDaddy about any of these breaches, and I've been a user for years, so I think, um, let's, let's make them the poster child, but there's probably many, many more that need to also be on the same wanted poster. Um, I think that if that's all that we have at our disposal, that I think that shame is important.

Well, we live in an age where breach is an opinion, not a fact. So we can kind of mess with that all we want. But, um, Brett do the math for me with this thing.

So now I've got all the noise around the customers hearing about this, and a lot of them will be second guessing what they're gonna do next. And then inevitably there's gonna be lawsuits filed where somebody's gonna, either shareholders or customers who are gonna wanna know how come this breach happened and I wasn't alert about it. And the total cost of that thing, when you add it all up, is gonna far exceed what the cost of putting cybersecurity in the place in the first place was gonna be.

So did somebody just not have a calculator? What's the problem? This is the problem.

Everywhere in the industry is the calculus of what happens post breach and the cleanup efforts. Does it, is it equal to the cost of preventive care and things that go along this? Some would argue now that with cyber insurance provided that they have demonstrated or could demonstrate they've done enough for their insurer and their broker to suggest that they have covered the bases, then that's covered for them to a large degree.

And the implications are not the same. And we also see, you know, as, as history would tell us, the implication of what happens to a publicly traded company after a breach is not as indicative as we would expect. Example, target stock rising after a massive target breach.

And there are many other examples of the same occurrence. So the market doesn't punish companies for bad behavior, insurers do, brokers do, and then regulators do. But customers, you know, and if you wanted to change, uh, your, let's say you have 50 domains, right?

At GoDaddy or you're hosting, you know, 10 websites is a non-trivial exercise to get to another hosting provider to make a change, you're held captive. Mm-hmm. So walk me through that a little bit.

Exactly. Who's gonna get sued here? Would it be the company that, uh, had the offending security issue?

Or will it be the insurer who gets sued and the company's gonna go Well, yeah, not my problem. The insurer signed off on the policy and, uh, you know, have at it. Yeah, it's a pretty rare case for the insurer to get beat up on this situation here.

This holding company is probably gonna get a class action plus plus. And, you know, their insurers may, you know, either dramatically increase the premiums and or drop them, you know, from that case, you know, there's gonna be plenty of outside, uh, legal banter about this, and it'll go on for years, uh, with some settlement being, you know, uh, well smaller than what actually is probably realistic for the, the exercise. But, um, you know, go GoDaddy isn't gonna feel a ton of pain about this other than, you know, their consumers are probably going to have dramatic concerns about whether or not they can move to some other, you know, hosting provider and or registrar in those cases.

So I, I would love to tell you, Mike, that there is a bunch of, you know, sort of market correction that can happen here, but you know, it's, it's really not the case. And let me ask you a follow up. So let's say I am a bad person.

Would I not just take this whole FTC report, chuck it in the chan chief pt, and then ask it, what are the best exploits out there for exploiting these vulnerabilities described in this here document, and then apply it broadly? There's such a big, so, so 5 million customers, right? There's such a big surface area of attack.

So here's the, you know, the dinner belt and okay, well, if I haven't spent time on GoDaddy now, right? I now can spend some time on GoDaddy. If I'm looking to establish a toehold, you know, in a very broad landscape, is it available for me to go compromise accounts?

How fast can, you know, I embed myself in a way, in a means that allows me to get, you know, these websites that shell access for all of these things, take over, uh, people's, you know, start squatting, take over people's existing domains, and really cause some havoc when you think about who's hosted there, right? That also has implications. Let just on the, the generalities of what is available to you as a, as a tool choice, uh, then you look at what companies are using GoDaddy for hosting and where they're located.

There's all kinds of other deeper, you know, ways to, to navigate here. And I think this will, it should be interesting to see what happens over the next one to three months and whether or not we start to see more come out about this. Uh, but w we have rung the dinner bell for sure, Right?

Lisa, you're running marketing over there. So am I attacking the credibility FTC and calling this all fake news, or am I gonna do something else? I hope you're gonna do something else.

I don't think it's, I I think it's been established that it's not fake news. I think they have a, a marketing cleanup job to do for sure, because like Freddy, you were saying 5 million customers running domains on GoDaddy that need to be aware that there's vulnerability holes here and your data is at risk. Um, I think they need to be transparent that can't run away from this, that transparency and messaging is gonna be critical to, to maintain the customer trust that they probably are just assuming they still have.

But once you break customer trust, but to your point, Fred, too, moving a domain to another service provider is not, not a trivial task. So are are, are they, are the users gonna say, well, shoot GoDaddy, fix this because I don't have the time or the resources to move my domain. GoDaddy needs to have the right messaging, the right sentiment to its customers so that they can maintain that trust that I think a lot of us have blindly put into them because we kind of build it, we set it, we forget it and don't wanna have to worry about it.

But I think they need to, they need to be forthright and transparent with their audience. All right folks, we're gonna end it here, but I would say that it's clear that cyber criminals are probably having a good chuckle over this. But you know, who's having a great belly laugh?

Lawyers gotta make a lot of money here. All right, folks. Hey, I wanna thank our analysts and experts for being on the show today.

You guys are awesome. As usual, I wanna thank you all for watching and spending time with us. Please stay tuned for the Tech strong TV lineup right behind us.

It's gonna be awesome once again, and we will see you guys on Monday. Take care. Hey everyone, welcome back here to Tech Drunk tv.

I'm really glad to have my, uh, next guest on here. He's someone we've talked to before. I don't know if it was under this role, but let me introduce you to Tyler Jewel.

Tyler is the CEO of aca. Tyler, welcome to Tech Drunk tv. It's great to have you here, Alan.

It's good to be back. I think this is the third time we've talked. Absolutely.

Absolutely. Tyler, we're gonna get into who ACA is and we're gonna talk a little agentic ai, but first let's talk Tyler, right? Yeah, because maybe you and I have spoken three times, but probably, you know, not everyone in the audience listens to every show.

I do imagine that, I Mean, that's gotta hurt your feelings a little bit there. It does, it does. I have to tell you the truth, I was doing a webinar the other day with a live round table with live audience, and some guy got on there and said, uh, greetings from Boston.

I've been a Shimmy fan boy for years. Love coming, you know, listened in on everything Alan does. And I was like, I didn't even pay him to say that.

So I, you know, I don't know who it was, but whoever it was. Thank you. Um, I don't know, does it count if it's anonymous?

Well, it, it, it said Rob CI felt like I was, I, you know, I was on one of those, call it radio shows. But anyway, Tyler, give us a little sense of your journey out, you know, where, how you got here today. Oh, mine, uh, well, you know, I'm the CEO of aca.

This is the fourth tech company that I've run. Um, you might have been familiar with a couple of the others. Uh, WS oh two, which was an open source ESB vendor got acquired by EQT last year for 650 million.

And before that, ran a company called Covy that I had started. It was a cloud IDE. It was a, uh, an early generation, um, cloud IDE, which was kind of competitive to Rept before Rept had come along.

And that was acquired by Red Hat. And I've had 15 years of venture capital and angel investing almost all exclusively in developer experience, developer platforms and developer integration technologies. Um, and I publish, uh, a blog where I keep track of all the DevOps companies on the planet.

There are 1700 of them. AB 17, you know what? That's a li we, well, when was the last time you updated that?

It's been 18 months. Uh, but, you know, all things being equal, I think that the number of companies is about the same because, uh, I've seen just as many companies fold or go under as there have been new companies that have come along. Uh, it's, it's a little bit tricky.

I don't necessarily include all of the AI generated developer techs, platforms, open source projects that are out there. They've all kind of flooded the market a little bit. And so it would be, I wouldn't call it, uh, polluting the landscape, but certainly it, you know, uh, lots of threads to pull that could cause it to, you know, blow up in terms of the total count.

Absolutely. Absolutely. Tyler, you know, it's been an amazing Jersey.

Uh, when did, when did you come in here to aca? Uh, I made, uh, an investment into ACA in 2019, joined their board, then, uh, been on the board since that time. And, and ACA is an interesting company.

It used to be known as Light Bend. Uh, light Bend was a company that had, uh, raised a quite a bit of money from a lot of tier a venture capitalists. And, uh, they ran into some problems in 2021 and we're open about that.

And they didn't have a viable business model. Um, uh, they didn't have a good product plan. And, and the company faced a near bankruptcy event.

And, uh, we actually had the investors step in, restructure the company, uh, change the product plan, change the business model, uh, and we've, uh, also updated the management team. And it was all about a year and a half ago that I stepped in as the CEO, uh, because frankly we thought there was a huge opportunity and I was excited to get back in and operate again. Very cool.

Very cool. You know, just thinking back, Tyler, you said three times, I, Ima I, I, I imagine I've interviewed you many more than three times. Oh, Well, I don't know.

I mean, maybe that was over beers, the, the beers and wine count. Well, maybe you're right. You're okay.

Maybe, maybe. Um, so, you know, let's get this out of the way. AKA is spelled a KKA.

Yes. io. Okay.

Tyler, before we jump into the topic of discussion today, which is around, you know, uh, deployment models for Agen AI systems, audience out here says, I, I think I heard a light bin. I'm not a hundred percent sure, but who cares that that business changed anyway? How would you describe what ACA does for them?

Well, you know, ARA was originally an open source project invented by Jonas Bonnet, a, uh, Swede, who was also the founder of the company, and he's still our CTO. And Jonas is a bit of a savant in terms of distributed systems technologies. And originally, ACA was a development framework for designing, building and implementing large distributed systems, distributed systems that could process, uh, uh, hundreds of millions of concurrent users terabytes of data in real time.

And to do this with very consistent SLAs, whether it's a latency SLA availability or recovery. And, um, over the years it's evolved and it's been deployed over a hundred thousand times. Uh, there's more than 2 billion people on the planet who use an application that's powered by ACA every day of the week.

Um, there are systems that are powered by Datadog, Netflix, Amazon, um, oh, let's see, Starbucks, uh, 50 different banks around the world. A lot of automotive groups like General Motors, Tesla, uh, apple, all make use of aca. And, uh, what we've evolved it into is it started off as a developer framework and now it's an enterprise agentic AI platform.

And enterprise agentic AI for us is when your IT systems, uh, meet your reasoning systems, but you still need to maintain all the abilities, whether it's availability, scalability, performance, safety, security, pick your poison of that. Um, and, uh, ACA has a number of large scale, uh, enterprise AI deployments associated with it. And people use ACA to do, uh, model inference, rag based systems, uh, planning, uh, planning and execution based systems, uh, large scale, uh, a personalization where you're doing streaming from a bunch of different sources.

And you need to inference do a lot of inference off that in real time. Uh, and AKA's able to do this, uh, with systems that run up to three or 4 million, uh, transactions per second and offer global, uh, disaster recovery and failover at the same time. Wow.

So we're talking three, 4 million, uh, a second. Are we talking mainframes or is this still sort of distributed cloud sort of, or maybe in a data center? Uh, Uh, so it's, uh, it, it has to be truly distributed to get to that level of, uh, uh, transactions per second.

And effectively the way ACA works is it's, uh, it's, it, it's runtime is an actor based runtime, and actors are some, uh, concepts from the 1970s in computer science. And effectively what they are is it's a concurrency mechanism, uh, that also allows for message passing between those, um, those systems. And so you can get high levels of concurrency, but also isolation with them.

And effectively what happens is when people build systems with aca, uh, that's generally gonna be some sort of stateful system ACA nodes, uh, take responsibility for all the data. Uh, they scale themselves out on as much compute as you can give to them, and, and they, uh, manage the data in memory, um, as opposed to having to go to some sort of database or some sort of persistent store. And when you do that, um, it does it in intelligent ways.

Now, end users, as long as they can get to that right mesh, um, they get almost instantaneous responses. Uh, and it's also non-blocking with asynchronous communications. So it not only scales horizontally, but you also get more this very consistent instantaneous response for any type of transaction that you might want to do.

Uh, and so ultimately people use ACA for when they have large volumes of concurrent users, like, uh, wiggy, which as, uh, I'm sorry, uh, uh, I was gonna say Dream 11, dream 11, which is like the DraftKings of the Indian market. Uh, when they have a cricket match, they have 70 million users all gambling on every play simultaneously, and they have to offer a 17 millisecond response time for each of those users. Otherwise, a user gets an advantage on that.

And that access is not just static content, there's actual transactional content. 'cause you're looking at wallets, you're looking at player stats and whatnot. Um, so that's an example of that.

Other, other examples is when you need to process, um, uh, large volumes of data in a very consistent, uh, uh, way. So, uh, you know, uh, with Datadog, they do all their data ingest on aca. So they've got lots of streams of data coming from across all their different customers.

And, um, it's coming in a different volume, uh, volumetric rates, and they have to process it in a very consistent way, despite no matter how much coming in. So as long as they have the bandwidth to suck in that raw data, then they have to do the transactional processing on an inconsistent, inconsistent means. Got it.

Interesting stuff. Really interesting stuff. You know, one, one of the, and I love doing what I do, Tyler, and part of it is because this isn't something you read about necessarily in, you know, we, we, everyone's talking AI today, and we talk about AI and everyone's talking about agent ai, and, you know, there's been so many conferences this week between Google and Red Hat and Microsoft and Dell, as, as you probably know, everyone's talking agentic ai.

But this is yet another window, another facet of how AI, agentic AI is being used or can be used, right? And, and in this case, these huge distributed systems. And, and there ways maybe that we didn't hear a Google IO yesterday or something like that, right?

Yeah, yeah. Um, so how is this, I'm gonna ask you the same question I ask a lot of the folks when it comes to AI, though. Where's the killer app and how, how real is this today?

Well, you know, the, uh, uh, you know, I think that we've seen the killer app already with chat, GPT in, in that people who have engaged with chat GPT is it, it is able to, um, uh, gather information, synthesize that, um, and reason on that information to some certain degree. And, and that, that raw capability of an LLM, that ability to do some basic reasoning, which is, uh, just word matching that has broad, broad, um, uh, uh, you know, existential implications to every IT system on the planet. Uh, and, and so it's not just the killer use case, the kill the, if there is a killer use case, it's this raw reasoning ability.

And what I mean by raw reasoning is that, uh, what an LLM is capable to do for you is it can take a series of inputs and it can give reasonable outputs on that. And you can apply that to your IT ecosystem in a lot of different ways. Like, for example, you can say, here's a document, here's a template, and I want you to fill it out given some context on that.

And so, you know, as long as you gave it the right structured input, it can generate a reasonable output on that. Um, you can sit there and ask it too, like, Hey, I need to categorize this data into three different buckets, and here's all the rules for that, and it can reason itself out and do that work for you. And so you can start extending this into really interesting ways, like, Hey, I think I wanna get some information, um, and there are four different systems I can call to get that information, choose which system I should call, and how do I call it?

And it will tell you, this is what you need to do. And so, you know, at that low level, those are the foundational building blocks of how you build a system that reasons at the end of the day, and now it can take those basic building blocks using LLMs and inject them into, um, their existing systems. And what ends up happening is that when you do that, you intelligently get, um, now your old school rule-based systems that have all this deterministic rules on how the business is gonna work alongside your non-deterministic reasoning based systems that are coming up with it dynamically on that.

And so with that, you can do things of completely change the personalization experience, because you can have it reason about what kinds of things that needs to synthesize for the person that they're interacting with. You can automate things that had really complex rule sets that were too difficult to maintain. Now you can have the LLM automate those things for you, and you can also have systems that adapt to their environment.

Um, and that sounds all light and fluffy, but adapting to the environment, for example, would be, um, looking at a user's click clickstream, monitoring that clickstream, and then telling an agent to change the goals that it's trying to do. If you're trying to personalize something like, like, this is what we do for Tubi. Um, so Tubi is one of our customers.

They take a live, a live, you know, activity of what the user is looking at, process that in a bunch of models, and then change, uh, the goals of the recommendation system and the recommendation agent that they have. So those, wow. You know, so I, I think AI is big.

I I think that nobody's really adopted it in the IT space yet. It's early, early stages. Uh, but I think every system is gonna go through a transformation.

I like to say we're at the beginning of the beginning, not even the end of the beginning. Um, so I, I, I agree with you there. io.

Um, who would you recommend, like, you know, hey, this is a great website, if you are in this, you should come here and check out what we're doing. I, I think that, uh, for us, what we're saying is like, if you are, um, experimenting with ai, or you're at the point where you need to start bringing AI into your IT environment, come check us out. Um, we do 48 hour POCs for you.

Uh, bring us your use case. Uh, we'll educate you on what AI means, and we'll actually implement it and show you what it's like. That's a killer app right there, my friend.

Good for you. Thank you. I love it.

Hey, Tyler, continued success. Good luck with aca. Keep us posted, please.

io here on Tech Drunk tv. Tyler Jewel, we'll be back. Stay tuned.

Hey guys, thanks to the throw, we're here with Ryan Carlson, who's president of Chain Guard, and they're fresh off picking up, you know, a, a poultry 356 million in additional funding, and that money will be well spent in terms of helping us secure our software supply chains. But I'm gonna let Ryan explain all that. Ryan, welcome to show.

Thanks, Michael. Great to be here. Thanks for having me.

You guys were early pioneers in this whole space, so, um, you know, where are we in terms of hardening our images and containers right now? Because I think we've been talking about securing software supply chains for a long time, and yet the progress is uneven. Yeah, uh, it is true.

People have talked about securing software supply chains for a long time, and usually the approaches they took to securing software supply chains were about giving people visibility into the problem and then hoping that somebody did something about it. We feel like we're the one of the first companies to actually do something about it by securing it directly, but it is, it is true. We were the pioneers as a company.

We're the first ones to do it in the way that we've done it. We've done it more than anybody else. But our story actually starts before chain guard.

Our, our co-founders spent many years together at Google doing a lot of different things that together combined to create the, the team and the vision for what we've done. You know, for example, one of our co-founders was one of the co-creators of Kubernetes. Two of our co-founders built the distro list project inside Google.

Uh, we built the, the salsa security level assessment framework, uh, the SIG store, open source project. All of these things independently would've helped software supply chains, but brought together in one place with the focus we have. And now, uh, as you mentioned up front, the additional resources, we've been doing this for a long time, it's why we're the leaders in what we do.

You Know, I talked to some people, and it's, IM right. People have been downloading software randomly been using it in applications from different hubs over the years. Um, and we're wondering why there's issues.

But, um, even when they finally do get their arms around that and they put together some sort of, uh, repository where they download images that are hardened, it seems like it's hard to get developers to break the habits and change their, their culture. And so from your perspective, what does it take to kind of get developers on board? Uh, I think it takes a couple of things.

First, you have to really harden these image. Doing it halfway doesn't do the job. If, um, you know, one of the insights we've had, uh, in building this for years at Chain Guard is that we are solving a significant security problem, but we more than pay for ourselves in reclaimed developer and engineering productivity.

And to do that, to the extent in which we do, you have to get rid of all the vulnerabilities. You have to do it across all the open source they need. And so that's part of it.

You have to do the job that you say you're gonna do for everything that the developers need. But I think another part of that is make it such that the developers, developers have to switch as little as possible to get the benefit. So we're not asking 'em to change their frameworks, change the open source they're using.

Uh, we're, we are just saying, get what you need from chain guard, and then the additional toil and work to fix that open source software goes away. So sometimes, you know, the, what our customers tell us from a security standpoint, you can use a stick or a carrot to enforce this. What we, they look at chain guard as is a very significant carrot.

The developers want to use chain guard because once it's deployed and it's easy for them to, to start adopting chain guard, the additional work to secure and manage and patch that open source software, which every company has to do, is now taken off of their plate. Um, so what does it mean to secure all the container images and harden them? Because, um, you know, I've seen a lot of announcements lately and, you know, they have 20, 30 or 40 different container images that are hardened, not clear to me which ones need to be hardened more so than others.

So what does that spectrum look like? Yeah, we had 20 or 30 container images when Weaver started. Now we have 1300.

So, and every single one that we added to our catalog was one that a customer of ours needed. So you that there's a flywheel effect or a network effect that's at play with our business model, which is the more open source software we secure, the more customers we can, uh, make successful, and the more value we can bring to them. But the more customers we have, the more open source we need to to secure.

So those things go back and forth, and that's what's led us to have an order of magnitude or more container images than any, any other vendor, including the ones that you, that you've seen come into the, the scenario recently. But it's not just container images, it's also going beyond containers into, uh, VMs and into language libraries. We now have three product lines, uh, alongside the container images product for us.

It's going to be a never ending journey for us to secure all of the open source software that companies rely upon. Um, so I hope that that helps give some clarity. Sure.

Um, so what's the plan for the funding? What needs to be done from here? Uh, there's a ton to do.

You know, both in, in building up more and more engineering and product resources, the key for us to, to add value to our customers is to keep securing more and more of their open source. But it's not just securing more types of open source, it's securing it in a deeper way. So some recent examples, we've enhanced the container images that we have with something called an EOL Grace period.

So if a con, a piece of open source software goes end of life, typically customers in the past would have to contend with, um, either updating it or now having no opportunity to update or remediate CDEs in it. We can still go further than that. And now we extend the CVE remediation that we provide even for parts of software that have been end of life.

So we keep making our containers better, and the funding that we've raised will let us do that, but it also lets us, uh, invest in the teams that make customers successful. When you choose a a hardened container product, it is more than just the product that you're choosing. You need to choose the company and the team that supports it, the company that has more experience than anyone in getting hundreds of organizations up and running and successful in that.

So we have an amazing team that does all of that. But will the funding will allow us to bring even more people on board that help customers be successful with this technology. And that's around the world.

We're a global company. We have, um, support and, and technical expertise in Asia Pacific, in Europe and North America. We'll keep expanding the teams that bring this technology to customers with this additional funding as well.

We've also seen new types of artifacts in the DevOps chains. They're typically things associated with building out AI applications and agents. How does that change the way we need to think about hardening images?

For us, it's whatever our customers need. We wanna make it more secure. Um, open source software, this is well known.

Open source software is the most secure type of software because there's many people working on it versus closed source or proprietary software. But the work around it is still something that we can take off of people's plates, and that's true for every type of open source software. So we have a certain subset of our container images, which we call AI images.

And these are around, not LLMs, but more of the AI application stack. Those are already part of our product lines today that, that customers use. We'll just keep adding more and more on that.

Whatever customers need to grow faster and to be safer at the same time, we'll, we'll cover for them. A lot of organizations also have their own custom images to how do I harden those? And if I extend one of your images, does it still harden?

It's a great point. So this, there's a shared responsibility model when you're offering a product that we do where we're giving customers software to either deploy or to build on top of where does our responsibility end and where does their theirs begin? And since we've been doing this for years, one of the things we've run into is when we'll give a customer what we call a base image.

This one might be a Java or a pipeline container image, for example. They might wanna build on top of it or customize it in a way. And so in another enhancement that we've made is that customers, uh, have the ability to modify or customize a container image, but then we will then maintain that on their behalf.

They look to us to be the ones that maintain more thoroughly, more comprehensively, more quickly than they could themselves all the container images they use. And now we can do that for ones that they've customized as well. That's yet another way that we're set apart from, from vendors who are introducing a handful of container images that just do base functionality.

So what is your best advice to folks about how to get started with this? Because I think a lot of people understand the concept, but I, when they look at it and they look at their organization and the amount of images, they feel a little overwhelmed. It's a great point.

We see customers start in one of two ways. Typically, first, you might go after the container images that give you the most trouble that tax your engineering kings the most. These are the base container images that are used broadly throughout your infrastructure.

Something like a Java again, for example. Um, you could go right after those, and we could, you see the value from switching to something like chain guard very quickly. But another way to get started is we have what we call application images.

These are typically third party images, like an engine X or something like that, which customers drop in with no modification. And those are very easy to get started with. Either of those are, are very simple ways to experiment with our technology.

I'll, a significant part of our container images are available for free for developers just to, to use and to try and to see it themselves. And the last thing I'd mention is, if you're getting started with this, the main objective you're trying to solve is the removal of CDEs and vulnerabilities from your open source software. We have a, uh, a capability which we call CDE, visualization, visualization side by side.

You could see the CVEs before chain guard and the CVEs after chain guard. And the best way to, to not just try the technology, but to see the impact of it is to use that CVE visualization technology that we now have. I wonder if a lot of folks are not putting the cart before the horse and they're going in and building out a lot of workflows around DevSecOps without actually visiting the container or their other VM images or whatever they are first, and trying to secure that and then determining what level of processes I need to support that.

Yeah, I mean, the term shift left is used everywhere. It might be overused, but how further left in the build process can I insert security as a focus? What we say is don't shift left, start left.

And so if you start with hardened container images that have solved many of the problems that your teams would've had to solve themselves, it frees up the time to not have to build those workflows, but to tackle other things. There is no silver bullet in security. It's, it's a never ending race to, to keep your infrastructure safe against whatever threats there are.

You need partners and vendors who can take some of the things off your plate so your teams can focus on those other things. And that's a significant part of what we do. One of the ongoing conversations that's been had for as long as I can remember is people are saying, um, well, you know, we can't slow down, so we gotta, we gonna get past some of these security issues and we'll deal with them later.

But it turns out that on the back end, you know, there's somebody sitting there saying, we won't deploy this software because it's too buggy or it has too many vulnerabilities in it. And ultimately, doesn't that wind up slowing you down even more? It is a never ending debate.

Do I go fast and innovate, but introduce risk? Or do I lock things down and be completely secure, but then go slow? And I, you know, it's not, that's a false choice between those two things.

But we increasingly see people saying, if you start from a secure base of open source software, that trade off between speed and security, between innovation and risk becomes lessened, and both teams can win, the security teams can win, and the engineering teams can win when you start with a secure CVE free, uh, CDE free base container image solution. So what's that one thing you see people doing still that just makes you shake your head and go, folks, we can be better than that. I think a lot of of companies that we've talked to who view this problem as something they need to take action to solve have built up an internal team, or they may have a, a hardened images, um, program inside of the organization.

And so they're spending a lot of time solving something that we think we can solve more efficiently for them. Uh, but that's not the answer to your question. The thing that I see a lot of people do is just cross their fingers.

They say, look, okay, these CVEs are such a mess. I'm gonna, I'm going to, and I know many of them are false positives. There's a lot of noise and vulnerabilities that you can, you know, credibly, safely, credibly ignore unless there's a compliance framework requiring you not to.

What we would say is don't cross your fingers and or don't distribute this solution across all of your individual engineers. Um, you can't solve it in a different way, but I guess, you know, seeing people who task, who task, uh, individual engineers with solving this themselves versus giving them a team or choosing a vendor like Chainy Yard to do it, that's probably something we wish we could change. Hmm.

Underestimating the determination and capabilities of your adversaries is also a bad idea, but it seems to me the bad guys are getting better at scanning for vulnerabilities and identifying issues, and the amount of time it takes for them to exploit that is, you know, now measured in minutes. So has the nature of this game just fundamentally changed? Uh, I think it always seems like that at a certain point in time, wow.

Things, it's, things are getting faster and faster. But I think it's always been the case. That's always gonna be people try to exploit things and find ways in, there's always gonna be people who try to prevent them.

Um, again, there's no silver bullet in security, but we do think a v an increasingly fundamental part of that is fixing and maintaining the open source software before it ever has a chance of being exploited in your infrastructure. Right. Folks, you're heard here, Hey, remember what they always say about a, an ounce of prevention versus that perver?

Try that again. All right. All right, folks.

You're heard here. Hey, you know what they always say about that ounce of prevention versus the proverbial pound of cure? Well, it's true here as well.

Hey, Ryan, thanks for being on the show. Thanks, Michael. Great to be here.

All right, and back to you guys in the studio. Hey, everyone. We're back here with what I think is gonna be our highlight of our coverage of the Imagine Conference here for Automation Anywhere in, uh, beautiful Conrad Resort in Orlando.

I want to introduce you to Meher. Shukla. Meher is the CEO co-founder of Automation Anywhere.

He's doing this 20 years, right? For a lot of you working or watching this out there, you may not have even been working 20 years, let alone at one company, 20 years at my age. I, I can relate, but Maher, welcome to Text Drug tv.

Thanks for having Me. It's my pleasure. So let's start right off with that.

Yeah. 20 years ago. Yeah.

Talk about the vision 20 years ago. How's it, how's it changed? How's it stayed?

The same, how do, when you get outta bed every morning, what get what still gets you excited? Yeah. That, that's a great place to start.

Uh, from, from, from day one, today to today, the mission has been same. What has changed is along the way, we had to invent few technologies. Some technologies got better in the industry overall, and as a result, we are able to achieve our mission better and better every day.

And that mission was to reimagine how work happens. Prior to Automation Anywhere, I had a chance to do four different multi-billion dollar journey. And by the time I had seen a huge part of the world, and I saw a part of the world where 70% of knowledge workers were sitting in a cubicles and doing work that you felt weren't the human jobs.

And they could do so much better if you unleash human potential. And I grew up in a small town in India, and from my own experience, I knew that talent is evenly distributed. Opportunity is not.

And the opportunity that was made available to me made many things possible for me. So I didn't have to read a book to know that. Mm-hmm.

It is my own life's experience, lived experience. So the goal was to invent a set of technologies that take computers to the next level in how automation and AI can do things. And in doing so, the biggest bigger vision was could we reallocate intellectual capacity of the planet to more worthy causes?

What if we don't have to process invoices and claims and few other things? Could we be doing something more exciting, more fulfilling with our lives? And, uh, so with that objective, we started, and 20 years, more than 20 years later, here we are.

Uh, I, I get up every day. And how often you get to real help, help relocate, intellectual proper Absolutely. Capacity of the planet.

You know, I always say almost not multi-billion, unfortunately, but I done four or five, uh, venture startups founded, co-founded. And I, I firmly believe that every founder in their heart Yeah. Believes that in some way what they're doing is making the world better.

The vision you've enunciated here. This, this is in a small way, this is in a big way. Yeah.

Right? Free us up from doing these repetitive, I wanna call 'em low value. Yeah.

Or they're not low value. You know, we, we interviewed one of your customers from a light net, a light, I believe they're here. Yeah.

These are people who are processing people's benefits. Yeah. Medical benefits, health claims.

Yeah. Mission critical life and death. That's right.

They're doing so much with automation and, and, and automation Anywhere to speed that up, to allow people to go do higher value things. And these claims can just get processed automatically. We've all been there.

You submit a doctor's bill and you gotta wait. Yeah. 30, 45, 60 days for it to go through.

Not with automation. That's right. Now, of course, this past year you've been in business as long as I have.

This is sort of a, a high watermark. A a a threshold year where we're starting to see Yeah. Maybe people's visions for what AI can be Yes.

Become real. Yes. This whole new thing.

Uh, a agentic process information. Yes. A PA Yes.

Talk about how that's fundamentally changed, R-P-A-B-P-A and all of that, and how it, frankly, it's fundamentally changed your company. Yeah. Um, so, so the in general, my view, uh, having done technologies for many years is that technologies take a huge step change.

So if you look at last many years, what we have been able to do is use, uh, RPA robotic process automation, document automation and, uh, task mining and various other capabilities as part of the automation platform. What all of these CAP capabilities were able to do combine is they were often able to automate 40% of the processes, but the other 60%, uh, were left, uh, uh, were still manual. Suddenly, with the power of generative AI coming in, you were now able to take 40, what was 40%, sometimes all the way to a hundred percent or 80%.

So just a one new ingredient, completely change the value proposition of what is now possible, not by itself, but in combination of everything else that existed before. And when you add this ingredient, it changes the game. To me, it's almost like if you're for people who are into cars, you know, they sell that STPI dunno if you're familiar, STP gas added of you added to your gasoline and it boosted the octane.

That's Right. That's right. That's a good one.

Good. That's, that to me is what we've run here. You already had gasoline.

Yeah. But we just put in some extra octane that takes this thing off and, and it's an important, it's an important, it, it, it, we can't underemphasize how important that is. Right.

This is this game changing kind of stuff, but yet there's more weight, there's more. Right. We, people are talking about artificial general intelligence.

Yes. And I'm not here saying it's gonna be next year or five years or whatever. I, I I don't play that yet.

Okay. Yeah. But you don't have to get that big a GI, if you will.

Yeah, yeah. To have an a GI sort of, uh, influence in what you are doing. Yeah.

Talk about that. The, the, I am I'm with you there. I'm not a big fan of word a GI by itself, because it's an abstract concept with, you have no idea what what that even means.

But I think if you define a general intelligence in context of specific purpose, so for example, if you're, uh, if you, if you, if you're an intelligence for a self-driving car, the, the, it's, it's very, very clear that this car have enough intelligence to drive itself, yes or no. Right? So similarly, what we are focused on is that can we develop enough general intelligence to do, do vast amount of work as we call it, for a knowledge worker?

So can we give, uh, one of our, uh, one of our software, uh, uh, uh, mortgage applications to process and claims to process and supply chain and tax and audits and vendors, and the vast amount of these things that can, you just give it to the system and it has enough understanding of how to do this now in define that way it looks possible to achieve it. And we recently announced that we took a for a step closer to it, towards it. And it is amazing to see how fast that is moving.

And, um, you, you, you, you're never sure, but it, that, that day looks closer now than it looked a few years ago. It's, it's not, I I say the same thing about quantum. When I first started talking about quantum computing, I said, I'm not gonna be alive.

Yeah. By the time, but all of a sudden, I, I would not be surprised if Quantum's here in 2028 or 2029 even. Yeah.

I think it's the same thing. Same thing here. Yeah.

Same thing. It it all of a sudden that horizon's gotten a lot Yeah. Close.

Closer. That's Correct. So, Meher, you know, we're sitting here at this conference, beautiful conference center.

You could feel an excitement when you go down by the, the, uh, stages and in the area. Yeah. For you, what are the big stories for imagine this year?

What, what's the big message? I think this year, as you said, was very pivotal for us, and we announced three huge an, uh, uh, uh, announcement, uh, that moves the category significantly forward. The first one was an announcement to a, a significantly expanded, uh, agent process automation platform.

It's one unique element among about a hundred other features. That unique element is a process reasoning engine. Yes.

It's a very powerful capability in it. It, it, it works the way enterprises needed to work, which is in context of my enterprise, in context of my past information, in context of regulatory environment, reason what I should do at this point in time. And that process reasoning engine is what every enterprise's needs.

And it, it, it is the engine that will power all enterprise processes. And we announced the capability of how far this reasoning engine has come and how transformative it would be for work. The second announcement we made was an availability of agent solutions.

Uh, these solutions are not like your typical solutions and applications that you see that earlier. We have seen for, uh, 20, 30 years. We frankly don't like some of them because you have to often do 20 clicks to get something done.

And I feel like they're designed for an era 20 years ago. I think there is an opportunity here to reimagine how, how this work gets done. It can, can you have a solution or application that is agent first case, autonomous first, and design with a very different mindset.

So today we announced four different solutions and many more to follow, including many would be offered by our partners. So, um, we are looking forward to how that transforms the industry and accelerates the journey. Um, the third announcement we made is about a very unique set of capabilities in most cutting edge of the products and our services and partner services to create a offering called Autonomous Enterprise.

Now, this is, this is designed not, not necessarily for every customer, but we have customers who come to us and say, I want to get to this vision of how, how future, how, how, what future of the work is. And I wanna get to a point where 70% of all my current work is either fully autonomous or assisted. Give me a choice to get there in the fastest way possible.

I don't want to take the long route. I want to, I, I wanna take a flight and get there. And so we, we, we, we offered with our partners, uh, uh, combining many capabilities and, uh, we take this to those customers to take the extra journey even faster.

So those are the three announcements. Excellent. Two more areas I wanted to touch on with you.

One is, as, as, as we enter this age of Ag Agent ai, you know, we've seen announcements from Salesforce and, and ServiceNow and, and even some of the big hyperscalers Yeah. Everyone recognizes that we're gonna be deploying multiple agents. Yeah.

Maybe dozens if not more. Sure. This makes for chaos, right?

Yeah. We you need an orchestrator. You need, you need a, a commander, a master agent.

Yeah. Everyone has their own name for this. Yeah.

Now I know, uh, automation Anywhere recognizes this. You're also working with an orchestrator type of layer Yeah. Strategy.

Yeah. Would you expand on, without getting too far in the weeds Yeah. But would you expand on the need for the orchestrator Yeah.

And why you think your company is, is in the, a good place to be the provider? Yeah. I think it is important.

You, you mentioned that there will be many, many agents, but in our view, there are three types of agents. Uh, the, the first type is personal productivity agents, and maybe many of the viewers understand that they're using one thing or the other. Today, the second types of agents are, we call captive agents.

They're specific to certain application platforms like Salesforce and ServiceNow and others. And there will be many others. But the third type of agents you call the super agent or the commander agent, that is the truck.

That is the power, that is where the power lies. And Automation Anywhere is going to own that piece, uh, to orchestrate the, all the, all different types of agents across multiple application and making sure work gets done end to end. Uh, it is important for our, for our vision to, to, to, to, to realize is that we have to break silos.

We have been working in the way since a post World War II era where everything is since siloed. And that is, that is how, that is why the work is as, uh, ineffective and boring as it has been. Um, there is an opportunity to change it with Automation Anywhere, orchestration, power, and some of our inherent capabilities.

And, uh, we, we showcase that imagine an ability to perform and orchestrate this work almost at the speed that you can give a command to and can work happen at that p that that pace. And yes, it's possible for work to happen at that pace if you use automation. Excellent.

And, and that the announcements from Imagine this available now or coming soon, or, Uh, e every single thing we showcase to be we with actual product, we showcased it. Uh, many, most of them are generally available. Uh, a couple of our capabilities will be available, generally available soon, but they were all available in beta and customers had a chance to play with it.

And, uh, there was very gratifying to see as well. Another area I wanted to touch on with, you know, I speak to a lot of CEOs, big companies, startup companies, everybody wants to be a platform. No one wants to be a product anymore.

Products aren't good enough. All of a sudden I gotta be a platform. Yeah.

But you need products that work on a platform. Yeah. Why is Automation Anywhere the platform?

You know, you hear talking that as many customers, there are partners here and, and you know, people who are doing products that work in automation, the professional services that work with it. Talk to me about the vision for the platform. Yeah.

I think I, what wanna do is make sure I mentioned this earlier, but we, we, we are, we, we are the best in class platform company and always have been. But I mentioned earlier that we are, we have announced many solutions and many more to come. So on top of being the best in class platform company that it can use, we are now this new era of Agent Tick solutions that a business can use to, so make sure we are serving our customers, IT and business both through two different, uh, offerings.

Um, uh, if you, if you think about, uh, for for a minute, think three or five years out, because sometimes you can debate, uh, you know, future in three months or six, but it is probably all of us could agree what it looks like. Multi R Multi r the work is not going to happen the way it happens today. You are going to use, in my view, multiple LLM providers.

Yes. Because no one provider can provide you everything. It's perfect.

Right. You are going to orchestrate work across multiple applications. You are going to lead, go to the world that is as autonomous as possible and reduce reliance on manual processes.

That's a goal we can all agree on. Right? Agreed.

You could de depend how much, but as far as you can go, you are going to do that. Um, and, and, and, and, and, and you are going to need something that can execute mission critical processes. This is not about, uh, summarizing email.

That that's, that's not what everybody, you, you process mortgages and claims and supply chain and you assemble planes with hundred thousand parts and mm-hmm. These are important complex work, and you, you are going to need some help in doing this in a complex world. We, uh, if you just mention this, if you just think about this four or five things and need to orchestrate this work, you're gonna need something for it.

And that's something is Automation Anywhere and it's available today. Perfect. There you go.

I love it. Last question. 'cause I know you have to leave.

I appreciate your time. Yeah. Spend two days here talking Yeah.

To customers, product, other partners, analysts press, boil it down. What are you hearing from them? What, what's your take back from these people that you're gonna turn around and say, okay, this, this is where we may wanna double down.

This is where we may have to change something. What, you know, based upon the feedback, what, what have, what have you learned? I, I think couple of things.

One is that they are very excited about the products that they are using today. And as a CEO of a product company, that's the first thing I want to hear. That we are delighting our customers and meeting their needs.

Uh, when they heard our new vision and where we are going, they're super excited. They can't wait to try it. Uh, they, they can see the possibilities.

And, you know, I've seen this every year where customers, uh, innovation capability is just unbelievable. They, they can, they can use this product in a way that you have never imagined. And they make a difference in the world we live in, in a way that, that, that, that is so gratifying for us to see.

So to, to, to, to interact and collaborate with these customers across 18 different industries, some of the largest companies, uh, on the planet. And we can't wait to see what they will, will make of it. Uh, one of the key challenge is how to, uh, uh, how, how, how to, how to help everybody understand the potential of it and how to, how to bring this to life in every department, in every function, in hundreds of different problems that the organization has to solve and how can AI transform it.

And so our goal is to help together with us and our partners to help customers do that better every day. Fantastic. Mihir, thank you so much.

We appreciate you taking the time to talk with our audience. Continued success with Automation Anywhere. Can't wait for next year's imagined, but I have a feeling between now and then there's gonna be a lot happening and going on, and it'll be interesting to look at this next year in light of what is to come.

Thanks for taking the time to talk to us. Pleasure. Uh, I'll mention one thing, Alan.

The, in a technology space, uh, ever since I've started my career, the technology always takes longer than you expected and sometimes a lot longer to achieve the vision that you set that Takes longer than the hype. That's correct. Right.

The hype is always out in front of It. What is unusual about the, what we are up to right now with Agent Tick process automation is, it is take, it is happening faster than we have imagined. I've never seen anything week by week, week by week, day by day.

And this is unusual even for us, for all. Imagine the Customer. Yeah.

Oh, I, I, I can't can you imagine, because if we have a few more minutes. Yeah. But it's one of the biggest things, and I discussed this with the, with the a few people here today.

There's still the human element here and the human element here is trust. Yes. If the human can't trust what this agent ai or general AI or any of 'em we're gonna do, they're not gonna let it do.

Yes. Right. And we're at this kind of awkward stage where humans are still learning to trust Yeah.

What the AI's doing. Yeah. And so we're almost pulling the reins back saying it's going too fast.

I don't trust it yet. Yes. But once we trust it, yes.

But the trust has to be earned. So one of the things we observed is we, we, we, we let our customers observe how it is doing it and put human in the loop where, where they, they have a chance to validate it. Mm-hmm.

Often what we observe is that after a person observes it for let's say three days, they get bored because this thing keeps doing the same thing again and again. And it's not as much fun. And Sometimes boring's Good.

Yeah. But so very soon. So if one person might, after watching three days say, you know what?

I trust this thing, let's move on. Somebody might say, I'll watch it for three months and then I'll trust everybody does it at their own place. Right.

It is important for technology to earn that trust. Absolutely. That's a great way to end this.

Thank you. Thank you. Hey, I hope you've enjoyed our coverage for Imagine, uh, 2025 here in Orlando.

Many thanks to Automation Anywhere for having us here. We'll be continuing this story throughout the year. 'cause these are, this is, this is where it's at right now, right?

This is where the rubber meets the road with ai, agentic, AI and everything else. This is Alan Shimmel. We're out.

Thank you. Hey everyone, it's Alan Hummel from Techstrong. We're here today at the beautiful Conrad Resort in Orlando, Florida for the Automation Anywhere Imagine Conference.

It's been an amazing two days. You know, there's so much going on in this area. You may or may not know Automation Anywhere.

They've been a leader in, in, uh, B-P-A-R-P-A for years and years and years. Um, but the world's changing and, and, and so is Automation Anywhere. And, uh, we're gonna talk about that.

I'd like to introduce you to Audi Ganti, right. Chief Product Officer, CPO at Automation Anywhere. Audi, thank you so much for joining us today and it's great to have you here.

Thanks For having me, Alan. So I mentioned your Chief product officer, but I always like to give at the audience a a sense of your journey. Yes.

Right. How did you come to be the Chief Product Officer here? So, Alan had joined Automation Anywhere about little under four years ago, and I joined as Chief Product Officer.

So as part of that product technology community, um, those are my areas of responsibility beyond, uh, everything else that goes in a, you know, in a startup in a company our size that's growing so fast. Um, so I've been here about three and a half odd years before that, I was at Salesforce for 15 years. Um, joined back when it was one big cloud or one product line.

Uh, SFA, uh, I've seen it through this various growth, uh, transitions and spikes and, uh, kind of the major growth areas to join when it was, you know, sub 500 million left in 2021 when it was around 27, 20 8 billion. So saw that a growth curve always in products, um, was in different product lines. Really at the core.

I love building, launching, growing product lines. Like that's my DNA. Um, and that was, uh, you know, ran, ran 1,000,000,005 business, um, at the end of my tenure at Salesforce and decided I wanna be in the automation market.

That's why I joined the leader, which is where I Am machine anywhere. So Audi, you know, to me that's a really interesting, uh, history coming from Salesforce to Automation Anywhere. 'cause these are two companies that are kinda leading the, the path forward in terms of agentic, agentic ai and using agent Salesforce has of course made a huge pivot That's right.

To, to this agent based thing. I, I have to ask you, four years ago, you're looking at coming to Automation Anywhere for automation and of course automation is, you know, in the tech world is always considered a good thing, right? Yeah.

Um, did you have any inkling at that point that, uh, the agentic piece of this would be such a, I mean, such a, a, a watershed event? No. To be, uh, very indeed.

Right. Uh, four years ago, no. Uh, but I always knew the automation market was right.

Really ripe for disruption. Mm-hmm. Um, yes.

We're, you know, a market maker for RPA robotic process automation, and there are other sub-markets out there, but there's no, like the, the, the technology had evolved, but with AI and the kind of the broader, uh, market moves is happening across various sections, I did feel that automation, that's one of the reasons I joined Automation Anywhere, was a market was gonna explode. Yeah. And this was something that was clear to me even in 2021 when I was, you know, looking at, I spoke to Hir and team about joining Automation Anywhere, uh, because all of, you know, every business needs automation.

Absolutely. Um, as much as we might say that, you know, operational efficiency is, you know, especially now actually operational efficiency is even more important, but even more so growth. How do you drive growth by investing in the business?

And that's where automation comes in. Um, we are always been in ai, uh, frankly, even RPA and kind of BPA, there has always been a lot of AI more A IML, um, but definitely this entire market of agents and gene AI before that is completely disrupted. Absolutely.

To me, I think of it is, you know, they were selling automobiles before Henry Ford mm-hmm. But the whole concept of the assembly line and the little automation and, and so what, you know, it made a very different Yes. For a very different car market automobile market.

Now, we've talked around the edges about Automation Anywhere and, and you know, their history, they were a leader in RPA, they've been a leader in, they're still a leader and still a leader, leader in RPA. Exactly. Yeah.

Um, but when, when, as you, as Chief Product Officer, when did you, you know, go to your peers at the exec team and say, well, have you gone to your peers, I guess is a better question and say, Hey, we, we have got to go all in on egen, or maybe not go all in on egen. Yeah. So, um, we've had, so there's a timeline to this.

Mm-hmm. We were the first into Gen ai. Uh, in fact, we started working with Open AI and some of other companies before chat, GPT, and it's primarily to drive more automation use cases around doc, specifically around document processing.

Mm-hmm. Um, and because we found a way where we, for example, um, process unstructured documents, so this is like back in 2022 before all the craze of chat GPT, and Sure, you know, the, the explosion, uh, and for the next six to eight months, and this is post chat GPT, we investors started investing more and more in that area because we saw amazing results. Uh, and now our, one of our fastest growing products is document automation.

You know, three x growth, uh, 65% of our documents are processed using generative ai. You know, it's, wow. And we are talking about single digits last year and now 65%.

So just crazy kind of growth there. But really last 18 months. So we are first on Gen ai, then we started thinking about, okay, how do we tune this or focus this automation outcomes because most of the gen AI you see out there a general purpose, you know, summarize an email or, you know, do something else.

Uh, write a blog article. Write a blog article. For us, our customers are asking, well, how does this apply to me in my automation, uh, use cases, whether it is accounts payable or what it might, whatever it might be.

So our focus is, okay, what are the investments we should be making to use Gen AI and then AI agents, but tune it and focus it on process automation? And so that was kind of something we went all in. I'd say about 18 months ago.

Um, we as a product and technology team, we've been working really closely with not only the hyperscalers, the AWS and Microsoft gcps of the world, also startups who've been coming up and up and coming, like AI native companies. So we've been kind of ahead of the market in that sense and getting access to early technology in before it's available in the market. Uh, so long story short, I would say is we, we kind of very much all in into what we call agent process automation, which is kind of our version of agent ai.

Uh, and Mihir and the broad exec team, frankly, the company is all into, um, it wasn't overnight, but, but I think the last 18 months we've shown we are first to market with a PA first to market with agents. We launched it nearly a year ago before agents are cool now it's obviously everybody's talking about it. Uh, and obviously we'll talk more about some of the new announcements, but I think the first more advantage has really helped us.

Absolutely. Well, yeah. You were starting from a position of strength.

Yes. Right. I I just wanna make clear, a PA is a gen process automation, and that's, that's kind of the new term here that we're using for this.

I will tell you, I'm not as an expert on automation, obviously as you are, but I've always looked, especially at RPA and said, it's great, but I always felt there was another shooter drop. You know what I mean? That something like an AI agent would really just ignite this.

Um, you know, I, I remember my first kind of exposure to RPA, I met someone in a startup group. I think I was a judge at a pitch event or something. Yeah.

And, and they had an RPA document mm-hmm. Basically system that was really cool. But it, I just felt it needed the agent to really make it more independent.

Yeah. More, uh, expensive. Yeah.

Mm-hmm. And, and now when you look at this, it, it, I mean, certainly it's, it it's just as you said, when you go from single digits to 65% in one year Yeah, that's Right. With the top line growing at three x, so it's, everything's growing.

It's not so Three x and I mean, you don't see that, right? This is like when cloud came out, we didn't see this kind of growth. This is the kind of growth we saw when maybe the internet first point commercial, right?

Yeah. We truly believe this, the phase phase we're in, and I think this is not only in automation, but broadly in the market. This entire agent tech, um, gen ai, uh, push is like cloud or even probably like the internet.

I Think it's bigger than cloud. It's more like the Internet. Yes.

Uh, and so it's gonna make come complete not only disrupt markets, but you're gonna have the next Googles and Facebooks and Absolutely AWS is the world from this coming out 10 years from now. And so we want be very focused on this. I agree with, you know, I, I try to tell people that I've been in technology for 35 years, a long time, and I've seen a lot of stuff come and go and come again.

Um, there are some things that as a technology person get me excited the cloud, right. But explaining to my mother-in-law what the cloud is, all she knows is her pictures were stored up there. Right?

Yeah. Then there are some things that just change civilization, the internet, the cell phone. Right.

These things. It, it's not just my geeky friends. Yeah.

Right. It's, and, and that's to me what, what we're dealing with here with something like, you know, agenda a PA and, and agents. So, howdy.

If you don't mind, I'd like to maybe pivot a little bit now and, and talk about the Imagine Conference here. It's been two days chock full of product announcements, partner success stories, customer success stories, learning. Mm-hmm.

You know, I think people are still, uh, wrapping their, he their hands, their arms around agent process automation. What it, what it's more than just a name change. Yeah.

What, what really does it entail? If you wouldn't mind, for all of our audience out here who weren't able to come Yeah. Who weren't here.

Tell us what we missed. Give them a recap, let make sure we, we, you know, let them know what, what's, what happened here. Yeah.

So it's been an amazing, what, two and a half days. We still got, uh, the rest of today. Um, we, I, I kind of break around three, three main things.

First, we talked about the amazing momentum we're seeing with Agent Tick process automation. This is something we launched last year as a category. It's really a new category, an expansive category.

Um, and we had our abdominally, uh, we had KPMG. Um, we had Washington Post some major customers talking about how they're using agent process automation and really driving incredible operational efficiency, but organizational change and business change within their, uh, you know, large enterprises, uh, and across, you know, manufacturing and um, uh, uh, different industries essentially. So that's one big thing.

And, uh, across, uh, even the sessions, you, we had a lot of customers talking about, you know, the business benefits and the gains they're seeing with agent process automation. The second big announcement was set of new innovations, and that as the chief product officer I'm really excited about first was around the process reasoning engine. And essentially the way I think about the process reasoning engine, it's kind of a secret sauce.

It's, um, our unique IP that helps us drive differentiated process automation outcomes in the world regions, because you have general purpose agents. Our focus is on driving process automation outcomes. And the way we do that is, you know, we have our own unique models built, are tuned on, you know, hundreds of millions of automation runs on our platform.

We have customer specific context, which name is personalization for specific customers, because, you know, customer manufacturing is gonna be very different customer financial services. It needs to be the tuned towards them. Uh, and then these more, uh, goal goal-oriented self-reflective agents, kind of cognitive AI agents that can, for example, um, pro, you know, look at unstructured content like a product catalog and make decisions on what's the right product, uh, replacement for a specific customer contract.

So there are different use cases, obviously. Uh, and so that entire process, reasoning engine ability to then, um, access in, in a very expansive enterprise tool set. So we're an automation company.

Customers use us to build RPA bots, APIs, process documents, build AI agents, bunch of different things. We also announced, so that pre was a big part of it. And, and underlying pre is also having an open ecosystem, open platforms.

We announced partnerships with the AWS. Uh, they were on stage as was Google Cloud, uh, part where we're, um, you know, par partnering with Google Cloud, for example, on the A two A protocol. Uh, we've been partnering with philanthropic, uh, model context protocol.

So really having, kind of really focusing as an automation vendor on an, an open platform and open ecosystem, that's critical. So that's all part of the process Reasoning engine. We are the first and the only automation, uh, vendor to have that.

And we believe that's critical for any company to drive differentiated process, automate outcomes. The second big announcement was general availability of our agent tech orchestration engine. So we truly believe one of the core beliefs around a PA is it's a combination of deterministic and cog and cognitive.

If cognitive is driven by the process reasoning engine agent tech, our agent orchestration engine is a major, uh, investment in our deterministic processes. The ability to basically run long running mission critical processes with the right governance and operational, uh, visibility. So that's gone ga um, with this summer.

And the third big announcement we made is, again, in partnership with AWS, uh, around human agent collaboration. So one of the things that this world of agents was completely changing is how you and I engage with agents. It's not gonna be the same forms and traditional user interfaces.

It's not gonna be those apps, you know, where, you know, like a, frankly a Salesforce or a ServiceNow, any of those. It's gonna be these more collaboration experiences, conversational experiences, but where you get work done, it's not a chitchatting experience. Right?

Um, and so how do you translate user intent into process action, but again, personalized to that user, personalized to the employee and personalized to the customer. And that's what we announced with our partnership with Amazon Queue, uh, which is kind of under the umbrella of human. Yeah, no, It's something we've covered a lot.

That's right. You know, it's funny you mentioned Salesforce and ServiceNow. One of the things we've seen is both of those companies, they don't want to just give you their agents.

They want to be their agent orchestrator. Yeah. You are the fir this is the first time I've heard someone refer to it as an agent orchestration system, but in my mind, that's always what was needed, sort of the Kubernetes is containers.

You need an orchestrator for, for your agents. And, but they may not call it that, but that's really where the race is, right? Everybody wants to, because we're gonna have a multitude of agents.

We'll have an agent that interacts between you and I, between a process and I between, you know, we're all gonna have a, a fleet of agents, whether they're ephemeral agents that are kind of single Yes. And disappear. And I spend it on another one up next time, or persistent agent or however terminology you want to use.

These agents are gonna need to be managed. Yep. Do you see that as a key part of the Automation Anywhere value?

Yes. Is managing this, this whole, this agent Army, if you will. Yeah.

The, the short answer is de a definite yes. Mm-hmm. That's along with the process reasoning engine, which is kind of the secret sauce for all agentic behavior.

Mm-hmm. The orchestration of these agents is critical. Yeah.

And we expect customers to build agents on our platform on AWS and GCP, on a Microsoft Azure, on Salesforce, on ServiceNow, on open source platforms and anything, because frankly, you're gonna build agents for different purposes or different different platforms and that's good. That's great. Uh, but how do you orchestrate those agents and how do you also orchestrate both, uh, agents and deterministic workflows?

Because when you're extracting a document, you don't necessarily need an agent or you're calling SAP, you don't need an agent for that. You can just use an API to, it's Really, well, there's this nom man's, that's a funny word to use for it. No man's land, but there's this gray area, let's say better between what's an API call and what's the N agent?

And you'll find a lot of, um, um, a little bit confusion in the market. Yeah. Where everything is being called an agent.

Uh, the way I see it is a cognitive task is an agent. And an agent can call a set of tools like an API, an RPA bot and other things to do. Its work.

But that's ultimate goal is you want to do something which is probabilistic. There are many things that you don't need a probabilistic, it's just, you know, you, you wanna call, uh, a Salesforce api, an S-A-P-A-P-I or a legacy system, you need to, you know, uh, use RPA bot to access it. You don't need an agent for that.

So, but what we are focusing on, how do you orchestrate a process? And a process is gonna have deterministic steps, it's gonna have cognitive steps, and that's great. And you can have some of those cognitive steps like agents built on our platform, some built on other platforms, and we wanna own that orchestration layer.

And like you said, the management layer. So how do you drive real time observability on how agents are operating? Are they actually responding as you expect them to respond?

'cause again, they're probabilistic. So even 95% success rate may not be good enough. It has to be 99 and more for certain mission critical processes.

So having the orchestration layer and the observability layer is all part of our agentic orchestration system. I love it. And, and I You're a hundred percent right.

Make no mistake, the company that was orchestrating and managing these agents is in the catbird seat, right. In the power seat to, as this whole thing starts tolo unfold. We kind of stopped though, but let's go back to imagine.

So that was two big announcements. So those are the two big announcements. And the third I would, uh, say is some major announcements with AWS.

I already talked about some of the product announcements. Yes. With Q with with q uh, also with Bedrock and some of the other, uh, investments there, but also with Google Cloud around our partnerships on various products, but also on the agent to Asian protocol, uh, I won't say much, but in Google's io event, they're gonna announce some joint, uh, investments actually happening, uh, next week.

So Excellent. They'll be announcements there. So it's customer innovation and some key strategic partnerships.

I love it. And, and it's interesting. You, you've got Google, Microsoft, and AWS integrations here.

Yes. As one should if you wanna play in that cloud space. Right.

Um, howdy. Let me ask you to look in your crystal ball now. So this look, this has turned the, the RPA mm-hmm.

Industry on its head mm-hmm. Two years from now. Two years, 12 months to 24 months.

How does this manifest itself? So one, the one caveat I would put in is, um, this entire agentic AI market is moving so fast. I mean, two years ago, no, there was no concept agents.

No. Now we only talk about agents. Um, so I would put that caveat with this market every three to four months, it's just turning on its head.

Right. Um, and I'm gonna put a crystal ball, like I can kind of guarantee that crystal ball. But what I will say is I do expect, um, we've talked about some of the key, um, elements here, right?

Agent orchestration agents being the probabilistic agents being, um, um, you know, you can orchestrate but also control plethora of agents across different platforms. I do see there, there's gonna be a big focus on how do you stitch together these various agents for specific solutions? How do you deliver value to the customer?

Because right now it's still very much a technology talk. Mm-hmm. Versus, okay, what are the at scale deployments that can be out there?

We already had some customers that the RDS and the of the world talk about how they're deploying it at scale. I think we need to go, today we have about 1500 live deployments. I expect that to go into the many, many thousands, if not 10 thousands.

And that's what I think the next two years. The the maturity curve Yeah. Is gonna be important because ultimately it is.

What we are in is how do we use agents for mission critical operations and for agents to be used in mission critical operations, it needs to mature, it Has to be mission critical. Yes. Yes.

It has to, uh, it can, they can't be higher rates, and there needs to be the right observability of the pieces. So our focus, and I think where the market is also gonna focus on a, across like our partners, the A W S's gcps of the world is how do we together partner to ensure our biggest, all our customers can, um, roll out and kind of scale out these agent tech solutions and workflows at scale across all their business operations, and see the impact on revenue, on operational efficiency, um, as well as on lower risk. Because those are the three pieces, right?

Revenue, cost risk on those three elements. We gotta see the impact of agents. And that's where I think the maturity curve is gonna happen for the next two, next two years.

But while we, while that happens, I think there's gonna be a lot of innovation going on in the market. We are just getting started on things like model context, protocol and agent to agent, uh, kind of, uh, protocols. Like how do different agents interact with each other?

'cause you, we all talked about how different vendors are gonna have different agents, so how do they talk to each other? That technology, we are just getting started. So I think there's gonna be a huge surge on innovation and commute surgery innovation, but I think what the market will demand is, well, how do I scale this out with my company and actually show business benefit?

And that's gonna be our focus. Excellent. Heidi, we're about outta time.

I wish we could talk more, but we will, because what, look, my feeling is we're at the beginning of the beginning of this Yes. Story, not even the end of the beginning. Mm-hmm.

So I look forward to continuing this conversation in the weeks and months ahead, but congratulations on a fantastic imagine event here. Thanks for coming on Techstrong and, uh, tech Strong TV and continued success. Alan, Thanks for having me.

Appreciate It. My pleasure. All right.

We will have more imagine coverage here from the OMI Automation Anywhere conference in Orlando. Stay tuned. Hey, everyone.

We're back here at the Imagine Conference from Automation Anywhere, uh, in Orlando at the Conrad Resort. It's, it's a beautiful resort, and it's been a, a fantastic two days of learning here, I'd imagine. Our next guest is Micah Smith.

Micah is VP of Developer Relations and Community. Nailed it. That's it.

You know, as I get older, it's harder for me to remember this. That's, That's one question down, One question down. All right.

They're not going to B me on that one anyway, Micah, welcome to Techstrong tv. It's a pleasure to have you on here. Um, we're gonna talk about a lot of things, but let's start off talking about you.

Yeah. So I'm invested that Me too. Um, imagine.

So Micah, give people a sense, I gave them your title, but you know, titles are fungible today. That's right. Um, Give them a sense of who you are and what you Do.

Yeah. So I lead the developer relations and community teams at Automation Anywhere. Mm-hmm.

And for us, that means everything from our training, our Automation Anywhere University to our Pathfinder community. Uh, that includes things like our Pathfinder framework, our Ag Agentic, quest bot games, which are challenges that we create for developers. Um, and basically a lot of community programs that we're running.

So we just did a training camp for, uh, everyone to learn agentic process automation. We did 46,000 course completions in a total of Wow weeks. It was a huge accomplishment.

Way more than we even expected, if I'm totally honest. Um, so I do that. And our mission is really to empower automation programs to be successful.

And that means empowering automation program leaders to know how to build and scale an automation program. And it also means training developers to learn how to develop, deliver, and deploy successful automations. Sure.

Let's unpack this a little bit. So you mentioned, I think it was called Automation Anywhere University. Yeah.

For those of the, our audience not familiar, give them a sense. What, what is the university about? Yeah.

So this is all of our efforts to train developers to learn how to build, deliver, and deploy, um, ag agentic process automation solutions. And so we've created a bunch of learning trails that are specific either to feature or specific to persona. So if you're a citizen developer and you have no background in development, you can take some of our courses and learn the basics, uh, the tenants of problem solving as we call them.

Mm-hmm. Uh, sequence selection and repetition that really forms the basis of every kind of problem solving. And those translate really well into developing and delivering automations.

We also have developer learning trails, so that if you are an experienced developer and you want to come to learn to build automations and processes and AI agents, we have training that you can take for that and, uh, learn to build solutions. One thing that I think sets our training apart from any other training that I've taken may be a little bias here, is we do this concept called automation skill stacking, where we'll teach distinct skills in several videos. So, hey, you're gonna learn about conditional statements.

Hey, you're gonna learn about logging. Hey, you're gonna learn about web scraping. Right?

We'll teach you those individual skills, and then we'll have a project at the end of that to pull all of those skills together in a build. When you do that build, you're doing it in a timed and scored environment, which means we gamify it a little bit. Sure.

You build an automation, you build it in this thing that we've called Agent to Quest, where you're building it in that time, in scored environment, and it gives you immediate feedback. So you have the ability to go back and change it. Maybe you did it with web scraping before, now you want to do it with JavaScript.

What does that mean for the accuracy? What does that mean for the speed of processing? So we've kind of gamified the process of being able to learn and try different things in a safe environment where you're not gonna break anything.

Like, the worst thing that happens is it just doesn't work. Start over. Okay.

Yeah. Yeah. I, I love it.

This is a great thing. So, you know, I, one of the companies I helped found over the years was DevOps Institute, where we were kind of the leader in DevOps training around the world of, I don't know, I forget how many tens or maybe a hundred thousand DevOps certifications. And, and what I came to realize is there are some people who learn for their own benefit, right?

I wanna learn, so I know how to do this, it's gonna make me a better developer, it's gonna make me a better, a more valuable asset, more employable, what, what have you. Mm-hmm. And then especially I see outside the us, um, there are people who are very tied into their certifications, right?

I am a, they like to have all the initials after their name. That's right. You know what I mean?

Mm-hmm. Automation Anywhere University. Can I get the initials or is it just for me to kind of better myself?

Absolutely. We have an essential certification, which is kind of that base level. We've got an advanced certification, and then we have an expert certification.

And obviously those ramp up what's required of you. So you start with just being able to complete a, you know, multi-choice test. And then it gets to the point where you actually have to build solutions and submit them, and we're scoring them to make sure that they're following best practices and stuff like that.

Um, and that's something that's really important for us, uh, to make sure that not only are you going through these videos and learning, but you're actually able to apply it and you're being efficient, basically. Right. I would assume continuing education's part of that charter or, Uh, yeah.

Well, not formally. We, we definitely want to have continuing education for sure. Uh, but it's not tied into universities as of right now.

Got it. Excellent. Um, you mentioned another term, Pathfinder.

Yeah. Not everyone out here again is gonna know Pathfinder. That's Right.

It give us a clue what, what's that about? So Pathfinder is our umbrella for everything that involves our community, our learning, our training, and our materials and stuff like that. We also have developed something called the Pathfinder Framework.

And this Pathfinder framework is the nine dimensions that we think are extremely important for automation program leaders to consider when setting up and scaling an automation program. So you brought up a great point about training. One of the things that an automation program leader needs to know is have something like a competency matrix developed, which says, I have the following people on my team, and they have the following skills.

Does that help us to meet all of our needs that we have in our opportunity pipeline so that as we're churning through new automation and AI opportunities, we have the team and the skills that are able to deliver on that? And if we don't, then we need to have some training plans developed and stuff like that. So those are the things that we're guiding automation program leaders on to say, Hey, do you have a strategy and vision?

How are you thinking about governance? How are you thinking about your operating model? Are you federated?

Are you taking contributions from other people of your organization? Or is it just a centralized team? How are you thinking about people and skills?

Your opportunity and pipeline management, your development and deployment, best practices, change management, the way you report on metrics and the way that you evangelize your program. All of those things are extremely important for an automation program leader to be successful. It's one thing just to deliver code to production.

If you're not able to tell people about the business value that is driving for your organization aligned to strategic priorities, you're missing the mark and you're selling yourself short. Agreed. I, I couldn't have said it better myself.

Excellent. Um, a third thing you mentioned was around this whole agent process automation. Yeah.

Which was, you know, in our last interview with Chief Product Officer Audi, it really is a pivot in the whole, you know, you look at the history of R-P-A-B-P-A, all, all of these things, hindsight's always 2020, let me say. But in hindsight, you look at it and say, this was all great, but it was waiting for something like AG agentic AI to come in and just ignite it, right? Yeah.

I think the most common misconception I hear about is people think that, oh, we did all this work in RPA, now we've gotta scrap all of that. No, turn to apa. Right?

And I think the, the truth of it is, everything that you've been doing now becomes tools that are available to these agents that can be orchestrated as part of a complex multi-step process. And so it's really like, Hey, if you have a ton of those RPA automations that you've built, you have gold, right? Because you can use all of that with those agents, and you can enable them to do things like goal planning and execution, and they can determine in which order to execute those different automations.

I think of them as, these are the programs that the agents are gonna run, unfortunately in, in the rest of the world, not in the RPA space. Right. People make agents and then they've gotta figure out what are the programs?

How do I, you know, what is this agent going to do? And I gotta like kind of program. Yeah.

Here we we're coming at is we already have all the steps. Now I've got an agent that could go do all these steps for me. Right?

That's right. I don't have to worry about stitching together. That's right.

The, the steps. I think another important thing is you wanna have visibility in one platform where you've got all of these orchestrated processes with agents involved, right? And if you think about what you have with Salesforce and their agent force, and Workday has their own equivalent, those are great within those specific domains.

But what if I had a place to pull them all together along with those RPA tools and all of that capability? And so our platform enables you to work with third party agents as well as agents that are developed directly within our platform. What a great story.

I want to talk a little bit about the Imagine Conference. Yeah. It's been two days.

There's a lot of customers here, a lot of partners, I would imagine A lot of Pathfinder members, a lot of that's right. University students, a lot of the people who you, they're your people. Yeah.

Yeah. Our community is out here strong. How, how, what, what's been the big story at the conference for you?

The energy around a PA and people starting to understand what's possible. And like we talked about being able to use the stuff they've been building, but now do it in a different way has been, um, definitely energizing and electrifying. I think another thing that a lot of our customers are recognizing is that those opportunities that they had two or three years ago that they said it doesn't meet our thresholds for ROI, or it's too complex for us to be able to do with this platform, they can now go look back at those opportunities and start to see like, Hey, we can actually do that now.

And not only can we do it, we can do it really quickly and it's gonna be an awesome solution. So they're starting to recognize and realize that a lot of those things are great ways for them to find their first use cases. I think another key thing is that people are getting hands on with building their own agents.

We've got several sessions that we've been doing throughout the conference where people can get hands on building their own AI agents, like I talked about with that agent at Quest, where it's a time scored environment. We're teaching people how to do that. The other thing that we're doing is teaching people about how to think about deterministic versus non-deterministic agentic workflows.

So I've got a deterministic workflow, it's a bit more robotic, but it's still using a large language model to complete what it needs to do. I've also got eight non-deterministic agent where I'm giving it that set of tools and letting it determine in which order it needs to execute based on the goal that I've given it. I love it.

Feedback from people, you know, there's been a lot of announcements mm-hmm. And, and look at every conference like this, right? A lot of the announcements sometimes are forward looking, and then there's stuff, you know, rubber meets the road today.

What, what has been the, the community, you're, you're the voice of the community, right? What's been the community's kind of take on it? This Will be a data-driven answer because we've done an exercise in our community lounge.

There's nothing less. Uh, we did an exercise in the community lounge where we've got this big board set up and we said, what's the feature that you're most excited about that we just announced? And what's the feature that you're most likely to implement first?

Okay. Right. Kind of two different things.

Automator ai, which is our ability to go from natural language to a built automation or process, is the number one thing that people are the most excited about. Right. Think of it as the, the vibe coding for automation.

That's a good way of looking at it. Automation co-pilot is the one that people think they will implement first, which is to say that's the one that's based on Amazon Q for business, where you're able to have natural language to interact with your automation repository with those assets, and be able to invoke automations, processes, API tasks and, and let business users work with them. You know, that that's jives with, you know, text is part of few Churn group, a lot of analysts working with that.

And, and they recently did some, uh, my friend Mitchell actually did a whole report on agent AI for developers. Mm-hmm. And I think that's the sentiment there.

They're not looking for it to be the pilot, right. Because a lot of people spend a lot of time saying, oh, generates code, is the code good? Is the code secure?

Is the code bad? They're not looking for it to be the pilot. They're looking for it to be the co-pilot.

And that, no pun with Microsofts or GitHub stuff or anything like that, but they want AI to be a co-pilot, not a pilot at this stage of the game. That may change. Yeah.

Right. As we become, as it gets better, as we become more confident and comfortable with it. But right now, I do think so.

It, it, you know, no brainer. That's the first thing they're gonna do, is take it as a copilot For sure. And that connects with all the training that we're doing.

We're suggesting that when you get that first pilot use case into production, your first use of an AI agent, you wanna have a human in the loop every single time. Absolutely. Because you wanna verify every single decision, every single extraction, every single classification that was done by those agents.

Yeah. You can start to peel that back later. But thankfully, our platform has that copilot interface, which enables you to have human in loop a hundred percent of the time.

And then you can determine programmatically if you wanna scale that back a little bit and not have every single one for review. And that way your users are focused on the exceptions or the outliers, rather than the normal use cases that come in every single day. Absolutely.

I wanna talk about another thing, if it's okay, Michael. So, you know, R-P-A-B-P-A-R-P-A more than BPA was kind of, uh, the engine driving the, uh, or, or one of the engines, the major engine driving the whole low code, no code mm-hmm. Citizen developer kind of movement, which is, look, it has been very successful before there was Gen AI and you know, it burst on this.

Yeah. You know, before this agent ai, of course, this changes the game, right? We're gonna go from, I don't know, 30, 40 million developers to maybe a half a billion developers mm-hmm.

Because everyone could develop. Yeah. What is, what does that mean for your chart?

Or what does that mean? Like all of a sudden, who is a developer to you? Well, I mean, I hadn't considered those numbers, but the weight of that all of a sudden feels, uh, crazy overwhelming, Right?

Yeah. No, it's a 10 x. Uh, No, I, I we're really excited about that because a, we've already got a great low code user interface that's web based.

So anyone can just spin it up and use it. You don't have to worry about setting up your IDE or weird dependencies or stuff like that. It's easy to use.

It works in the browser, it works on Windows, it works on Mac os. Wow. So we have support for that.

I think the other thing is with Automator ai, like we just talked about, as long as someone understands their business problem, which is the specialty of business users, they'll be able to explain that and turn that into workable code and solutions that they're able to execute. Citizen development has been kind of a contentious thing in the past, right? It has.

Some people do it really well, some people haven't. Personally, I've led a program where we were really successful with Citizen Development. Not every single person you train has gone on to build the most advanced automations in the world.

But I think with Automator AI and where we're going with a lot of these new agent capabilities, it will enable more citizen developers to contribute in more meaningful ways than we've ever seen previously. So, Micah, it has been a, a great conversation. You know, it's an exciting time to be having, especially the Automation Anywhere community.

You like you did 46,000 people in four weeks, you know, just on Genix. So it's a great time to be involved in leaning and, and helping this community grow. Keep it up, come back and keep us posted on this too.

It's, it's an exciting thing. Um, that's gonna wrap up this one though, Micah. Thank you very much.

We are here at Automation Anywhere's Imagine Conference in Orlando at the Conrad. We're gonna be back with more state tuned.