Agent Interfaces & IDEs: The Future of Code Management | Agents of Dev Ep. 11

Control. This is agent dev. I'm in position.

Copy that. Dev. Stand by for, go.

Standing by. Hey everybody. Thank you for joining us for another, another episode of Agents of Dev.

I'm Mitch Ashley. I lead the software lifecycle engineering practice at Futurum Group, as well as, you know, techie and and developer and whatever of the day of the week, which I think kind of fits other than the practice name similar for you. Brad Shiman, my co-host.

Good to see you, Brad. Hey, Mitch. Hey, everybody.

Yes. Uh, so similarly, I am analyst slash practitioner slash enthusiast slash uh, lament of, of the same interest sometimes depending on what's happening. And I, I think, you know, today's chat topic for us is one that probably Mitch and I would not be returning to, except we were clawed pack in by that topic, uh, over the weekends.

Nice. Um, nice work. Yeah.

You have a future in broadcasting. That's awesome. It's, it's, uh, yeah, we, we really, I thought, uh, we're moving forward in, in terms of, you know, saying, okay, we get that, uh, this open claw, um, phenomenon is yes, a phenomenon.

And it points to, we think, some, some very important ideas that will reshape or continue to shape, is a better way to put it, the AI landscape, uh, both the consumer side and the enterprise side. However, my Bingo card for this weekend did not have Sam Altman from ai, higher buying, higher buying, uh, the, uh, open Claw founder Peter Steinberger. Mm-hmm.

Uh, for an undisclosed amount of money to, uh, run an undisclosed in undefined, uh, foundation to keep, to keep open claw and open source projects, but to also greatly influence the way Open eye, sorry. Open AI builds software going forward. Fascinating times.

Brilliant move too. Right? Duh.

What a great thing to do. And good for Peter to make some, not only some fame, but you know, hopefully some real good money at this. Kudos to Agreed.

Gorilla Marketing pays off as we have discovered with this case study. It does, and it's more than just a, you know, than a, uh, YouTube channel with a million followers. Followers, but Falls falls on its face when they go in an MAA ring, you know, or some MMA ring, you know, one of those kind is figuratively, figuratively.

Yeah. It, it's, you know, I think, I'm guessing maybe you thought this too. My, my thought was, okay, this is the claw moment.

It'll go, it'll bypass and we'll look at, this would be a great ca case study of what happens when you give a lot of power and some capabilities, some really brilliant thinking, but unfettered of what it can do, and like what do we learn from this? Well, I think we can still learn those things, but Oh my God, it is, it is the, I think before the show we were talking about, this is the new, new crypto of tech, right? It's the thing that everybody thought would die, but it's gonna live on an infamy.

Yeah. Just trust me bro. Trust me, bro.

But anything's bro, and it's official. Indeed. I mean, like, it literally happens to open Claw when, when Peter changed the, the account when, uh, ironically Anthropic sent him a nice cease and desist letter for his use of open Claude.

Um, and, you know, the Crypto Bros swept in promptly, I think within, uh, 60 seconds of that domain name and an account name Switch, gobbled that up and started spewing out their, uh, you know, marketing. Mm-hmm. Let's, let's put it that way.

Um, and it is, it is, and I, and I say that it's, that's the literal side, but we're also looking at this as a, a figurative crypto bro moment in that, as I was just saying with, you know, why would open AI swoop in to buy something that they've been working on with Codex for a while, just as Anthropic has with, you know, Claude, and also more recently with, uh, cowork. Um, well, it's the eyeballs, it's the, like you said, Mitch, it's that investor momentum that really, you know, drives this marketplace. And to me, that that is speculative in its finest sense.

It's not technological in its entirety. Technology plays a part of it. It is, you know, meritocracy in that regard in terms of why we're even talking about it.

It's because, like you said, it does some really cool stuff, like with how it manages memory, for example. So, you know, you treat your context window like, uh, Ram, so you get, when we build software, Ram is this very precious commodity that you don't, you know, just heap and stack that thing to death. You know, you, you think about how you use it, and Clo Open Clock does that, and it does it pretty well.

So it's, it's good that it has that technology, but man, for me, I still feel like this is, this is just that crypto Broad, you know, tchotchke, sorry, um, what's his name from, um, uh, the Fawns Jumping the Shark in Uh, oh, in that old, old timey TV series with Ron Howard. My god, that's going back Yeah. Moment.

So, so let you know, here, here's the thought about this. If you ize it this way, so you're sitting here building these massive companies based on tons of debt and you know, some kid, whoever he is, I dunno how old he is, some person comes along and, and like, builds what you're trying to build, but did it over the weekend, right? Or you know, whatever timeframe.

Yeah. But anyway, it, however long it took to kinda doesn't matter. It, it, it just took off virally and all of a sudden we're like, well, crap.

That's what we were building. Well, if you're, if you're a really large tech company, you do what Anthropic does and says, stop cease. We don't want you to, to do this.

This is ruining our market. If you're an entrepreneur, you say, damn straight, let's go get this guy and get him on our team, and like, he's doing what we wanna do. Maybe it's not the way we would do it, and it's certainly not perfect, but yeah, this, this, let's leapfrog the market.

Let's hop onto this, you know, on this viral thing and write it for not only write it for as long as it can use that as a leapfrog to jump the place on the market. And there's a lot of criticism about open eye, open ai and not being, you know, where they should be compared to philanthropic. So, or, or open pretty damn brilliant.

Yeah. And it's not their first foray into this approach. Did they not hire the design brilliant, you know, the brilliant designer from Apple with the same intent of building devices that were gonna be beautifully designed.

And we haven't quite seen those yet. Uh, but I know that's still happening. Yeah, someday we'll see.

But they always took a long time at Apple too, so, you know, it'll take a long time here, I guess. Indeed, indeed. It wasn't just Apple, I guess.

Interesting. So, so let me ask you, certainly memory is one, one big innovation of how Open Claw does things and, and does it in some really useful ways. I would propose to you that another really brilliant thing about it is it just opened the world of connectivity through all the channels.

Mm. Whether you wanna use Signal, what do use, want to use, you know, discord you wanna use whatever, it'll talk to anything and everything, you know, both output and, and input, you know, egress and, and ingress. Um, and it kind of just made it super easy to work in the world that you wanna work in.

So if you live in Slack and email, okay, yeah, yeah, you can do that too. But no, maybe you don't. Maybe you live in YouTube and, and signal all of that, and that's your world.

Boom, you're there. I think that's another make, take the friction out of the system. It it talk to whatever you want, the file system, the SaaS application to the, to the clients that it talks to.

I think that's really smart. Yeah. Yeah.

It should, you know, the technology should live where you live, as you're saying. And we sort of all have been cramming ourselves into chatbots and CLI interfaces, although, you know, I, I'll defend the CLI for the rest of my days going down with the, a lot on cli. I'm totally, yes.

I'm noun then verb noun, then you up pin a CLI is coming back. It's back. It's, it never left, Mitch.

It never left. Exactly. It's, it's always there.

It's always gonna be there. Um, but, but, um, yeah, I think Peter actually, when he envisioned, uh, what was open Claude at that time, um, that was the idea was to interface with it with what he used, which was I think Telegram. Um, and so he built it.

Yeah. Basically, I wanna be able to chat with what I use to chat. I, I want to have something running 24 7 that's always listening to that chat and is also plugged into other assets that I might use, like my calendar, let's say, or my email or whatever.

And it's a pretty simple idea, is it not? And we've had all these technologies for much longer than Peter has been working on this project. Um, and he's not alone.

And, and when we get to the end of our session, the, uh, tech I wanna call out is, is one of those alternatives, um, for this. It's, and there are many, and you and I, and anyone that's listening to this podcast could stand up our own version of Open Claw this weekend mm-hmm. And have it running.

And maybe that's actually a good idea. You remember when we used to like, do, uh, build, you know, recursive models or regression models, sorry. Uh, you know, just by hand, some of my regression models were recursive, but yes, you're right.

Where's that minimum? Where's that local minimum? Oh, it's everywhere.

Um, yeah, it, it's, it's, it's definitely, you know, I I think taking what you and I talked about with, uh, Claude Cowork, which was that idea that, um, AI should live where you live and work alongside you or in place of you, um, you know, however you want it to work. You, you could set this up and co-work up the same way to, to basically say, these are the limits. This is what I trust you to do for me.

Yeah. And then let it go. And then That's a great idea.

Well, assuming you secure it. Yeah. Well, along the way it'll get secured.

We hope. So, so what it makes me think of Brad, is that, okay, so this happened for productivity, you know, tool a productivity assistant. If you wanna classify CLO that way, I think you could use it for much, much more than that.

Of course. Um, but what's the next thing? I mean, this only happened.

I'm gonna, I'm gonna suppose this, the supposition is that this only happened because you can build it that quickly in the technology that we have now. You could have done it two years ago. This quickly, that expansive that much capability and get it out.

Um, so what's gonna be the next thing, you know, in the database world? What's the thing that everybody assumed that you couldn't do? 'cause it just took too, too complex, took too long.

Or the data analytics world, or, you know, the communications world, what are we gonna see the succession of these kinds of wow moments saying, okay, that was not something we ever thought would happen. It isn't necessarily a new idea, but it's done in a really, um, less friction. Interesting, clever, unanticipated, very easy to adopt.

Clever. Exactly. And, and catch a storm in whatever that is, you know, medi medical diagnosis.

You can, you can say like, what is gonna happen? I think it's turning our world upside down. And maybe in a good way, you would really, and I would welcome that, and I think everyone who's a practitioner working with within, with databases in particular as just one technology area would agree that wouldn't it be great if you could wake up tomorrow morning and, and not have to think about your query plan or shards or you know, how your indexing is working and all of those DBA kind of things.

And, and, um, you know, you would think therefore that, you know, because this is a technology that we have literally kept, you know, close to of the vest for 70 some odd years or longer seemingly, um, that, uh, you know, it would be rife for disruption. And yet, um, like the CLI, it persists, uh, the complexity, I should say, persists because at some point, um, you know, the, the details matter. And when you're talking about, you know, data within a company and what that means to a company in terms of, you know, what it represents and, and the risk that it poses, if it's not managed properly, those details matter.

You know, if, if you screw up with your Claude bot and it accidentally spams everyone in your, you know, email lists, you may lose friends and influence. But, you know, at the end of the day, it's things like that do happen in real life too. Not just in the virtual, you know, agentic world, but with a database, you know, those small things that, that matter the most, I, I think can, can be abstracted, but never, uh, eradicated, uh, because they do matter.

And so from, you know, in the, in my research area, I, I see all the time, um, these same ideas playing out that we're seeing with things like cowork and things like open claw mm-hmm. In that we're, we're trying to take an build another layer of abstraction that allows, you know, the practitioners to stop thinking about the syntax and start thinking about the intent or the outcome. Uh, you know, what they want to happen.

I want my data pipeline to keep running. Might be a nice intent and outcome. Um, be nice.

Yes, it's supposed to, but it always did. It was supposed to work that way. But technology is always shifting.

It's always moving. And because of that, you know, there are known unknown unknown unknowns that we're always gonna bite you. And I, I do believe that, um, the tooling we're talking about, you and I talk about every week is, is capable of not just smoothing out and, and removing some of the barriers and the friction you talked about, but actually, um, eradicating some of those unknown unknowns, or at least addressing them in a more flexible, more comprehensive and more immediate way than we mere humans can.

Mm-hmm. Um, mm-hmm. Will they, you know, evolve into that?

I, I think in small pockets, yeah. I think that, you know, and it's always the case with any sort of scientific endeavor. You need to have a dis, you know, circumscribing universe that you can work with to understand, and then you can make it predictable, and then you can automate based on that.

And so, you know, for specific tasks like, you know, query plan management, let's say we've been working on automating that for a long time. Mm-hmm. And ag agentic AI is, is, and sorry, generative AI and AgTech, you know, I, uh, application of, of that idea to generative AI is, is making that better.

Um, so I think we'll just see that across the board, man. It's not gonna make databases no longer matter. 'cause they're always gonna matter.

And even if you say, well, let's just switch to object storage, we don't actually need relational databases anymore. It's just the file system anyway, you're still gonna be imposing some sort of structure on top of that because the details matter. Knowing that you write a record having that, yes, it did get written, even if I lost connectivity matters, still have to have some governance and some security and some data protection, and some data backup and re recovery and Yep.

All that's true. And then, and then the other side of the coin is, hmm, what if data doesn't have the same gravity that it does today? Maybe what if it could move much more easily?

Right. That's one of those take away constraints. You hear me talking about constraints all the time?

Yeah, yeah. When constraints get removed, that's when things really drastically changed. Just like, you know, the value of code today has gone down is going down every day, not because the code itself is' invaluable, but because your ability to produce it isn't the value of writing it by hand.

That's what's collapsing much bigger. Yeah. And so, you know, it's, it's, I may have said this before.

When I first started with these tools, my first reaction was, wow, pretty much, maybe not this moment, but pretty much, if there was anything that I wanted, I could probably build it if I wanted to do that. If not today, I certainly will be down the road. And not to say everybody's gonna have their own email client that they're gonna build by hand themselves, maybe they will someday, but if they really care about it, they will.

Yeah. It kind of like, if I don't like it and there's not one on the market, yeah, I could, I could say make it like this, but I want it to be this way. And, you know, that, that that's can be true of many, many things.

Um, so let me ask you, if you were gonna start out today, and you were gonna, I want a productivity, ai productivity assistant, and I could go frontiers, if I'm an in an enterprise customer with open ai, I could go, uh, cowork with, with Anthropic, I could do, you know, the Microsoft, I could do, you know, agent Force. I could do all of these things. So there's a business context and a personal context.

Let's talk about it in a personal context. Would you start out with Cloud code today? If you were starting from scratch, would you do or I, sorry, open, open cloud, or would you do something else?

Would you start out with, I'm gonna vibe code and build my thing and maybe I'll try Open Cloud later, or I don't know what, what, what, well, I think, I think knowing that it's a part of, of OpenAI would, would lead me as, as an enthusiast, you know, playing around at, uh, at night, on the weekends, uh, looking somewhere else just because, you know, we, we all, you know, especially those of us who've been in this industry for a while, do tend to see things through a bit of a cynical, you know, lens. And, um, you know, if you, if you are a proponent of, you know, Richard Stallman and, and the i the ethos behind, you know, suck, you know, open source, free and open source software, you might question this acquisition. Yeah.

Um, but it's already happened. It doesn't matter. And that's the beauty of open source, by the way, is that how many forks are there already of open claw, um, thousands of them.

And that's gonna be the case going forward. And there are a number of alternatives to play with, and that's the beauty of technology. And, and like you say, if you collapse that time to, you know, value for building something, um, mm-hmm.

Then why shouldn't you try this on your own? Why shouldn't you say, for my use case, what I want it to do? Uh, I don't need all of open.

I don't, I don't need it to, to you work with 3000 connectors and all that. I just have one use case that I want it to do. Mm-hmm.

You could, I think in very little time and with some degree of, of confidence, build something yourself. So I, I, I would build it. I would build it myself.

I really would. I would just r up with my favorite, you know, and, uh, uh, a agentic, CLI, um, whatever that is, let's say vibe from Mytral, for example. Doesn't have to be mm-hmm.

You know, codex or, you know, Claude, uh, CLI. Uh, and I would, I would just learn how to build an agent agentic, you know, plane, a control plane agent, agentic control plane, because that's a fascinating area just to dig into, like you and I were talking about with how you manage memory, how you, uh, build in connectivity to different sources of information and, and take action in different modalities. That's fascinating.

I think that that's, that's one of the things that, you know, perspective is worth 80 IQ points as Alan Kay, the Apple fellow used to say, I don't know who discovered water, but it wasn't a fish. Right. Um, um, it goes way back anyway.

Well, you, well, you and I approach it like, like I'm sure a lot of people do, which is I not only want, I want that tool, but I wanna understand it and I wanna understand what it takes to do it. And, you know, like, you know, you mentioned agent control planes and things like that, and I have this concept of observability native, and Oh yeah. So I'm already like in the stuff that I'm doing, like, okay, so I'm gonna go, go like, build my own version of this and see what it, see how I would do it, right?

Or what you could do, or what some of the constraints are, or taking it the next level. Not, not that I'm gonna contribute it all back to try to become the next, next open claw famous developer. May maybe I would, but I'm really, some people might wanna learning and experimentation, right?

Mm-hmm. So there's that whole mm-hmm. Wanting to know what could I do?

How would it work? You know, there's that part of it. Well, your general everyday user, I mean, I think you're, you're gonna talk about, um, and then one of the segments of sort of like, the easier, the, the open Cloth for Dummies version, not to disrespect anything, but if you know what I mean, there's, well, that's what Peter wanted to build, right?

He wanted to build something that his mom could use. That was his idea. Yep.

Yeah. I'm, I'm very much of the, do I just like plow down and go do an open claw instance, or like, do I keep doing what I'm doing and I keep doing what I, I keep doing what I'm doing, which is building it myself because I rebuild it multiple times. And one of the reasons why I do that isn't that I'm happy, I'm happy with it, is how I built it to today.

If I, you know, if I use today as the example, and six months ago is a much different process using the same tools, just new generations of them, right? Whether it's philanthropic or open ai, you know, codex or Gemini is, you know, the, the ability and the things we've learned about doing plans and things like that and how to better instruc control the memory of these systems, of these tools. It's doing it today is much different experience than even six months ago.

It's, it's odd to say that, but it's true. Well, it's because like six months ago, if, if I spent the weekend building a tool to do something like, like just drill down into fractals, because we all have done that. Um, so because I wanna fly through the fractal in real time, that's what I want.

Um, but, uh, you know, in the past, if I had concluded, you know, after two days of work that wow, that really wasn't the greatest approach that I took to building this tool, I would never have thrown it out. I would've been like, let's just keep working our way toward getting what I want with what we have. Mm-hmm.

And that collapse of time to value with a gentech, you know, code generation, you know, what is the loss? Just time and tokens at this point, and there that is increasingly a shrinking, you know, uh, asset in terms of cost and time. So I would just redo it.

Yeah, to your point and to your point, the experience, my experience yours probably too, is when you redo it, you can do it faster the second time, the third time, the fourth time now, because you just know it better. You know what you want better. Yes.

That's a big factor. But the tools have changed. I mean, I'm not sitting here arguing with whatever model about, no, that's not right, that's not correct.

That's not what I was describing. Or you didn't do what I asked you to do. You know, you're not, you're not dealing with the same level of things of Yeah.

You keep coding the wrong air fixing, you know, fixing the air that you keep breaking, or r breaking what you fix. Things go, I'm sorry, which, which ar ai are you using? Because that still happens to me.

Well, no, you really wanna know. Okay. No, so, so I, I've, right now I'm doing my development in, in Clot.

I mean, that's what I'm using at the moment. And I think it's four six extended or whatever it is, the thing kills. It's just like, wow.

Yeah. Yeah. It, it cranks and, and you know, and that's, there are some really good things about, you know, codex and, and Gemini and what they do as well.

It just kind of, the ball moves around a little bit. It's like fluid in a, in a jar. You just keep shaking up.

And this one's at the top now. Um, but that's what I did is I wanted to see like, okay, what's the state of this? It's been a few months I've done anything with it.

And it's like, ooh. Yeah, you gotta get to know it. You have to learn the ins and outs.

You have to, yeah. It's just like data. Um, back, back in high school, college days, you know, you need to get to spend time, get to know something.

You, school, college, okay. I was doing computers. Alright.

I'm told kidding. No, I in high school, college, but yes. Okay.

Not to, not to jump on the stereotype, but it's a stereotype. Um, for a reason. Yeah.

For, for a reason. No, actually, um, that, that makes me think about, about, um, call calling out, uh, acquaintances. And, and we, you and I forgot when we started today's podcast because we were, we're so enamored with, with, uh, you know, Peter and Sam's, uh, you know, getting to know one another, uh, that, uh, we forgot to, to do, uh, our new segment on, on the call out, uh, boy.

Which by the way to if those of you, we, we went under the shark. Um, it's, it's not two words, it's one word to call out, like in text, text to call attention to something. Mm-hmm.

Mm-hmm. So you mind, let's stop and do it before, before we forget. Move on.

Yes. Move on to the next day. JLL to our audience, you know, I, I vibe coded my way right past the call out, so let's back up here.

Sign for the call out. Yeah. This is live.

Yeah, there you go. Go for it Brad. Call out.

So, so mine, mine is, uh, a surprise for me. Uh, you know, I took a briefing from a company called Quest Software, which is a bit of a large company, global company that has quite a history. Uh, and they are very much interested in what you and I were just talking about with, you know, what is the gravity of data, what does that look like going forward in era?

They just are getting ready to, by the time this goes live, it will have gone out, uh, this new, uh, solution from them called the, the trusted data management platform. Uh, which you're like, yeah, there are a ton of those. And yes, there are, I actually am going to be publishing, uh, a new, um, signal report on said data intelligence platforms in just a couple of weeks.

But what what's interesting about this is they're, they're really focusing on creating what they call an automated data product factory. So we've heard about AI factories mm-hmm. And this is a data product factory, which everyone that's, you know, a data practitioner or knows one will, will have like, seen them or have lamented themselves the fact that how difficult it is to create data products, even though it is a grail, it is something we all want.

But, you know, push comes to shove, you're like, oh my gosh, just get the access, get them something that works, and let's call it a day and we'll come back to that problem later. Um, but so if you can build data products, especially if you can like tag on SLAs and let's say contracts to say, you know, that it's gonna do this and that, and this is what it represents, and those are important things to business. Uh, that's what Quest is really shooting for here, which I, which I find very laudable and, uh, I wish them luck with this.

It's, it looks, from the short intro I've seen to it in demo, it looks like it's a, a very solid, uh, step in that direction and something that will alleviate a lot of pain for, for DBAs in particular and, and any data practitioner, frankly. Excellent. What about you?

What's your call out this week? Yeah, you know, I actually have two, um, and both act do come from briefings as well, and some, I can talk about some I can't quite yet. But, um, you know, two of the really interesting, and I actually had three really interesting between IBM and, and Red Hat and GitLab.

Um, you talk about different companies at different stages of their development. Of course Red Hat's part of IBM, but they still kind of operate. They are Red Hat product wise, you know, on their own, on their own flow, if you will.

But what the trend that, that I think is happening is, you know, we're all enamored with chips and then we're enamored with data centers and then we're enamored with all the stuff that it takes to run a data center. And then eventually you kind of get to, oh yeah, we need to run things on this, right? What are we gonna put on this?

What we gonna use this for? Oh yeah. Back to software.

What was that again? Let's, let's think about that a minute. And, you know, I was, I sort of jumped my own, my own project here.

'cause I talked about the, um, agent control framework, uh, playing control framework that I'm working on that I will get to you to review. But I jumped it ahead of it and said, no, I'm gonna do, I'm gonna do this idea of observability native first. And then the concept is native, native meaning it's observability is built into the whole stack from the beginning, whether it's development or or what you're deploying operations in your code in this everywhere in the stack.

Because in a, in a world where everything can change because of agent and processes and ai and any part of that stack can be replaced at any time. And the non-deterministic nature of generative AI watching telemetry at the end of the trail, you know, the river's been polluted by the time it gets to you, your, your chances of stopping something just decreased dramatically. Right.

But you may have figured out what happened Yeah. To prevent it from happening. You're playing detective for something, you may not have any data for a crime that will never be recommitted.

Exactly. Yeah. That repo got blown away and it's already something else, right?

Mm-hmm. Um, so, and it's not to be, you know, too overly optimistic about it, but I think we're at a point where actually we can build in p pry and observability in everything as it's being built. And that's what you see vendors stepping up to try to do to get early in the development lifecycle, whether it's a Dynatrace or, or harness or Red Hat and IBM and GitLab.

They're all figuring out how to be part of the whole ecosystem, not the slice, just the slice that they've figured out they wanna be part of. They wanna own. Yeah.

They still wanna own that, but they want, they know they've gotta participate in the full life cycle. And so, uh, just a, a kudos to those companies, all all of them that I've mentioned who are really thinking aggressively about ai. Not just hop on the latest, you know, open club bandwagon or vibe, coding bandwagon, but to really think about how do they rethink their product strategies and reshape it so they are part of how software gets created, how it gets tested, and how it gets deployed, how it gets designed and thought of, because that loop is going and pretty soon, if you're not in it, it's too late.

It happens too fast, it's too late for you to get part of it. 'cause it's already come up with another way of doing it. So I think they're doing it out of necessity, but the also out of opportunity.

So lots of call outs there. Um, but I thought, um, you definitely expect a trend and now it's happening. It's like interesting to see it come together.

Do you, do you think, Mitch, that you know this because I, I love that idea of innate, uh, observability and, you know, even with like o open claw for instance, uh, Peter built into that, this, this observability where every single transaction gets documented. Mm-hmm. So you can replay what went wrong later on mm-hmm.

Mm-hmm. Um, or at least understand it. And I think you could use that to understand what's happening as it's happening, as you said in the stream.

But do you, do you think that, um, if every piece of software that gets built and gets conjoined within this, you know, control plane will need the control plane to be sort of a, you know, uh, like with with catalogs, you have a catalog of catalogs idea. Will we have a control plane of control planes wherein every component is self trans, you know, transcribing what it's doing to be tra to be documentable. Um, but then that harness, not just harness, sorry, that control plane itself is the master of that.

Do we need that? You know, I, I think that's, that's one logical line of thought. And I was thinking that way for a while and I thought, you know what, in our world there, there is no one product that dominates a company in, in large companies, they have everything.

Right. So they're not gonna sign up for, name it, Microsoft Control everything or Dynatrace to control everything or Yeah. Open AI to control everything.

Uh, even if they wanted to, just like everything else, we are an Oracle shop. Well, we just bought this company now we're not, we're Microsoft and Oracle shop. Right.

We're a little less Oracle today. Yeah. Yeah.

We're just squeezed it a little bit, maybe a lot depending on how much you bought. Um, so I think, I think the world we have to anticipate and expect is a control plane of control planes a, a multidimensional, it's called, you know, this is the multiverse of control planes, if you will, essentially, um, you know, which may sound like chaos, but on the other hand, that's, that's the world we're ending up in. I I think that that's unavoidable.

So now how do control planes talk with each other and how do they each operate within their own, with their own, within their own domain, and then when they intersect either intersecting in a good way or intersecting conflicting way, how does that get resolved? And, and I think the reason why that's possible to do now is everything doesn't have to be monitored after it's already been built and done, is you can have observability happening in the system of the system by the system by, by external agents, whatever it is, and be able to direct what's happening while it's happening. Let's say an agent, you know, makes a, makes a call to a, to an LLM and gets a wacky answer, but the guardrail didn't catch it.

But you have an observability guardrail that will also tell you something wacky happened. Let's redirect that agent for a moment. Have it do something different, or have it apply another agent check its work or whatever the response is.

Yeah. Yeah. So it's, it's a much more of a, an organic kinda live system as opposed to a linear, this happens and then we catch these things at these point in time, you know, the river doesn't flow one direction anymore.

It flows all directions with, I think the world we're going to wait is isn't that a flood? Yes. Yeah.

It's called a tsunami or mud side in California. Whatever you, but you know, it's, it's okay because then you're, you're not gonna hit yourself on rocks. You have room to swim.

Yeah. I didn't say it would be easy, but you know, that's happening tomorrow. Me, whenever I think like, yeah, this is gonna be the thing that wins.

Eh, it doesn't usually happen. That's pretty rare for a thing to win. You know, even in the mobile world, there's still Android and iOS, there's still two of them.

Right, right. You know, and there's, you know, the chances of one of them truly, really dominating isn't gonna happen, I don't think could happen. Maybe if, if you know Tim Cook gets elected president, then we'll have Iowa everything.

Well, right. I mean, Linux dominates. Um, well this, that's the choice of the people.

That's the people and, and everyone who's building servers and mobile operating systems and Chrome os and, uh, you know, every, every other os it seems, except one, um, yeah. It's, it is, it is like a, you know, a multi technological landscape, you know, where, where you have to be adaptive and you have to strive toward building software that, as you just described. So e eloquently is able to, you know, see itself to have some, you know, internal reflection.

Like, like I rarely do myself as a human, but as I strive to do self aware Right. To, to, you know, be able to say, huh, maybe if I did this, I might be better off. Let's, let's try it.

So when we, we evaluate software in the future, we'll be evaluating a lot the things we do now, plus the eq emotional quotient. What's the emotion? That's right.

It'd be free association on the couch for your software. Yes. How does that make you feel, Mitch?

It's all good. We should back when I was a young boy. No, that's a whole nother problem, but, oh dear.

Yeah, that sounds dangerous. Different kind of podcast indeed. But, uh, anyway, we, we should do our last segment before we go.

Um, yeah, because since, since we, since we changed our order around so much, we might, we might as well, you know, keep, keep going down that up. So, alright, so time for the drop. Okay.

It's time for the drop. All right. I think I, I don't remember if I went first last time.

I'll jump first time and then you can jump in. Okay. So I mentioned I have a couple things coming out.

The agent control plane framework and then also the observability native ideas. And I'm excited to share that, not just to get it out the door, um, but also get, get some real tests of it and people to say, this is crap, this makes sense. Make it better this way.

We like this, whatever. But my hope is to get, to make what we work on Brad as something that people can look at use as a, as a guide or as a framework for testing and evaluating what's happening in the market right now. Using the frame of, you know, what we know as analysts and also, you know, our own background and experience.

So that's a big one. And then kind of the other one is just marches right around the corner and I start traveling again. I haven't traveled too much, so I got, I'm, yeah, same here.

Getting back out the, you know, getting the band back together, like, okay, what do I have to have in my suitcase again? What do I have to be ready for to leave at a moment's notice? So you'll figure out once you get there, don't worry, Mitch, it'll be okay.

It'll happen. It's like riding a bike. I'll, I'll fall right back into it.

So anyway, so that, that's my drop. How about yours? Yeah, same here for the travel.

Uh, looking forward to that. It's, it's nice to, to see colleagues and, and to work with the vendors that we, we get to spend time with. I really, I feel very fortunate in being able to, to share, uh, in their, you know, everything they share with us and the knowledge they have to impart is wow.

Um, but yeah, so Weekend project, you know, you know how I have said I will not do, you know, open claw, uh, just because I don't have the time or, or energy to, to put into doing it right. And doing it in a way that I feel confident that it's the security is set up, you know, that I could trust it. However, that said, I, I, um, wanna try this with, uh, an alternative.

You know, I mentioned this a couple times today. I wanna play with one of those alternatives. And the one I'm looking at right now is called Nanobots, which comes out of a Hong Kong University.

And the reason is twofold. First is, uh, it's written in Python, uh, like 98%. So I like Python.

I feel comfortable, you know, reading Python much more than TypeScript. 'cause as, as you know, we've talked about, I hate semicolons. Um, but the point is this, this, this is the second part is it's only like 4,000 lines of code.

It does Wow. You know, it's, it's not as aggressive as open claw in, in terms of its scope that it wants to accomplish, but it does the same thing. It's the same kind of, of age agent system.

Mm-hmm. Uh, but it's 4,000 lines of code. And I think I could get my head around that, um, a little bit better than I could with the like 430,000 lines that Open Claw is sitting at right now.

Woo. No bot's not gonna, uh, start its own religion or create a political party. Well, unfortunately, communist Chinese or whatever as Right.

Let's, we should not get ourselves, every model you interact with, every software that you use has a perspective. And it came from someone or some group of people and they have their, you know, agendas and objectives. Yep.

So always, you know, understand who you're, you know, who you're dating, it's the important thing here, but, but friend your friends wisely. You too. And so I'm choosing Nanobot very carefully from that regard.

And, um, it's interesting because it actually has built in the ability to participate, uh, in the, um, what was it called? Um, bolt book, uh mm-hmm. Mm-hmm.

You know, social media, social network, you know, the Reddit for, for these claw bots, the Reddit, the Oh my goodness. Of, of coping. Yes, yes, yes.

Let them date one another. I'm fine with that. Yeah.

So that's, that's my drop is, uh, I'm looking forward to, to, you know, standing that up on a, a nice, you know, uh, UTM in, you know, container, uh, on my, on my spare computer, middle Mac Mini and let it go, because God forbid you can't get one for three weeks right now. No. The wait lists.

Yes. Yeah. Everybody's digging out their old Intel based Mac menu.

It's like, I may, I could do it on this, but anyway, whole nother thing. Well, cool. Well good.

Hey, uh, kudos on, uh, you know, we had our first guest last time, um, joining us, and we appreciated having, uh, folks here and we hope that others will consider being a part of our, our broadcast, part of our podcast here. com website. And we thank you very much for listening and following and just tolerating maybe some of the points here and there too, and just going along with this for the ride.

It's been a lot of fun. So, and it's a lot of fun because I'm doing it with you, Brett, so thanks for being too. I feel the same way as, as our, our producer Corey just reminded me.

Um, we're, we're definitely going place as we, we'll be back with an episode we might call Agents After Dark, uh, given, given the the topics that we've been talking about on this one. So thank you all for joining us on this crazy journey. We love having you here.

We may have to start rating our episodes, so, okay. That's right. NC 17.

Yes. Alright, take care everybody. We'll see you next time.

Control. This is agent dev. I'm in position copy.