Building the Foundation for the Agentic AI Era

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Hey, welcome to another edition of the Practical AI podcast. I am your cohost going solo today. I'm Chris Benson. Uh, Daniel's not with me this time, um, but we have an excellent conversation coming up for you. With me today, I have Angie Jones, who is the vice president of the Agentic AI Foundation, which I think is a super cool title to have, uh, at a at a super cool name place. And I'm really looking forward to finding out more about it.

Uh, Angie, welcome to the show.

Thanks so much, Chris.

So, um, like I said there in the intro, and I said it before, before, uh, the the show started and stuff like. Like, if somebody in AI was looking for a a play like the agentic, I mean, like it is, that is the coolest sounding, uh thing you can have. And but before we dive too far into the foundation, I'd really like to kind of hear, like, how does someone like, like, how do you develop in your career so that you end up doing that?

Like, could you tell us a little bit about your background? Um, because that's a that, you know, that's like, that's one of those things. If you, if you went and just said something to, like. I work with tons of people working on agentic AI, but like leading the foundation, people said, I'm just curious, like, how do you get to that point?

Yeah, um, so I'm, I'm your traditional, uh, techie, uh. So I've worked as an engineer for a couple of decades, so, you know, at places like IBM and Twitter, uh. And the last role was at Block in a engineering leadership capacity, and so in that role, uh. One of my tasks was to, uh, basically teach the entire company, twelve zero people, how to use AI agents. And this is as I'm learning myself, because, I mean, there's no book for this, you know, uh, right out the gate.

And uh, that was early, like 2024, so a lot of this stuff was brand new. It was not even common in tech, let alone in other verticals, right? And so, um, I also like, lead developer relations, and so a big part of my role is helping developers worldwide understand new technologies and how to use them. And so, uh, our company block created like this internal AI agent, uh, named Goose, and uh, goose. We were. The developers were using Goose to, like, automate engineering tasks, help with coding and things like that.

And so we were teaching developers across the globe what is an AI agent like. We were very early in this. And so, uh, Jack Dorsey, who leads block, uh, was like, Hey, Angie, you're teaching, like everybody else, about agents. I really would love for everyone in this company to learn how to use agents. And so I'm talking finance, marketing, like, you know, design, HR. Everyone needed to learn about AI, and more specifically, how to utilize agents.

And so, uh, me and the team went like, really deep on this. And then it got to a point like pretty AI fluent company, where everyone is comfortable, uh, using this. I needed to go really deep on the engineering org, and so that was my home. Um, our engineers were using this, but we weren't seeing a big difference in, like, developer velocity, for example, right? And so we we explored that and learned that, you know, we're only at the tip of the iceberg.

We really could do a whole lot more to get to this autonomous engineering org, right? And so I pretty much drank from the fire hose of, like, all of the news, all of the releases, everything that's going out. Um, and I consume that kind of, filter out a lot of the noise and then bring the things that are valuable to the engineers. And so I would say, like, I know a lot about the space. Um, and also at my time at Block, I worked on a protocol, so this was like a cross border money movement protocol.

So those who don't know block, that's the company, the finance tech company that, uh, houses square and cash app, right? So money is our jam. So I worked on this protocol, never thought I would be a protocol girl. Um, but learned a lot about, like, just kind of open standards and how all of that works as well. Also really big in open source throughout my career, I've always, like, believed in open source, contribute to open source, like advocate for it, right?

Um, so all of that kind of came together in this perfect storm. As Openai, um, Anthropic and Block wanted to form a a foundation for agentic AI, they understood that. Hey, some of these standards, some of these open source projects that we're coming up with, we probably shouldn't be the sole authors or owners of these things, right? Um, MCP is a great example, so MCP is the model context protocol. This is what agents use to connect to applications and tools, right?

Which we saw across block. Everyone in block needed MCP service to connect to whatever applications they were using. And so, like Anthropic realized, yeah, this probably should live in a neutral home. And so those three companies came together to form the agentic foundation under the Linux foundation, and so Linux Foundation has been around for decades, everyone knows them. Um, and so, yeah, so this is a new foundation. So once we stood this up, uh, me and our head of open source, uh, came over to the foundation.

And and we thought it was so cool, we we started working here full time.

Very cool. And and and I like the Jack Dorsey name drop there, that was that, that's pretty good. Like, so you, actually, you were actually working directly with him as well along the way. Um, And I and just him being

I see Teal, Yeah, that's right. So I worked with Jack at at Twitter, and then he brought me over to Block when they when they started, um, developing like these open source projects and protocol.

very cool. S I Li I. I wanna back up for a moment, cause I got a couple of questions from things that that you brought up there. And one is is the education cause. I think, uh, educating the organizations that folks are in, like, like you were, you know, pathfinding along the same kind of task that that a lot of organizations are trying to do right now. And that is, you know, uh, especially like every year recently, but especially 2026, has been just insanely, you know, fast.

In terms of the, you know, the the level of progress and, um, the onset of agentics, you know, uh, they were, you know, they were there last year, uh, but this year it just has taken over the world. And so, like every org is dealing with that now. And you have taken point on this notion of education, not just for developers, but for, you know, the the whole org. And and kind of, uh, parts of the org that maybe people aren't thinking about as much, cause they tend to be fo very focused on developers.

Can you talk a little bit about what creating that kind of change looks like in terms of I? And I'm gonna separate it. I wanna ask about the non developers. 1st, like when you're going into finance and and you're going into these other, uh, these other organizational departments that have that that are not thinking about the bits and bytes of AI all the time. Um, and and and you're trying to say, here's a new tool. And like, how do you approach that?

Not not only from the the upskilling, uh, that's required, but also from the um, kind of the like, getting people to accept it. Cause, I mean, you know, you see like people out there. There's a lot of resistance to AI in the general population out there. And so, like, how how do you navigate that? Uh, when you're, when you're, when you're trying to to move the org forward like that?

yeah, there. These were two very big and different challenges, right? So one is the whole change management of it all. Like you're essentially asking people to think differently and do their jobs differently. These are experts in their domains, right? Uh, who? Who maybe been doing this a couple of decades? And you're like, Oh, kind of throw away like your processes and everything, and we want you to do this. Um, not only that, to your point, resistance, right?

Fear, uh, lots of different emotions, uh, involved in that, and then the whole technical part of it. Where, like these tools, like I said, this was very early on 2024, 2025. You didn't have these nice desktop application, you had a CLI, right? You were copying JSON to, like, get an MCP server working. Like this was foreign to folks who, like, don't use these tools every day, so it was a really big job. Um, and and so, like, you have to consider all of that.

It's not just, hey, let me show you how to use a terminal, right? Um, it's helping them understand where they still fit into the process, right with things. It's okay to let that go. Like, you probably should not be doing this anymore because it's not a good use of your time anymore, right? Um, and then also I, I like to say, there's people on both spectrums. There's people that, you know, they think AI is the best thing ever and can do all the things, and there's other people who are like, Oh, AI is stupid, it can't do anything.

I like to kind of be in the middle there, where, you know, I can be realistic about its strengths, its weaknesses, um, what I should use it for and what I shouldn't use it for. And just leading with that helped a lot. Because I'm not trying to get you to drink kool aid, right? I'm saying, hey, here's a different approach that could speed you up, right? Um, that can also give you access to a lot of stuff that maybe you didn't have before, and that part was the key.

So when there's, there's, let's say data, right? Um, everybody needs data, no matter what role you're in. Um, if I say, Hey, listen, I can get you access with this agent. And like some MCP server to, let's say, uh, records that are in this database. That you would've had to go to another team, put in a request and ask for a report, right? And then try to figure that report out yourself. I can get you that data in seconds so that you can go and like, do your best work.

So people are, like, sold on that kind of thing, right? So you take them step by step and give them things that, uh, are meaningful to them. That might not be their core job, so just so they could get used to it and they could start building some trust, right? And then eventually they start delegating a little bit more and a little bit more, um, until they find that right spot of, okay, I shouldn't delegate this.

The AI does not do well. Watch that, that part I'll take right. So that was my my overall approach to it.

I, I really like that, and when I know, when I get in conversations with folks, uh, about this topic, um, one of the things that I often say, which I think is is kind of resonating with with your. Your story. There is that, like, find the place where the human has a distinct advantage from the AI and differentiate the AI. You know, go down through the job requirements and find what where the human is is still better at this point.

And that may be fluid, you know, that may change over time, depending on on that. So, like, having having an open mind, uh, is good, but I think I think that's incredible advice, uh, that you're giving people in terms of like, how to navigate. Because I think that's one of the biggest questions that people that people have out there, based on the conversations I'm having. Um, to flip to the other side of the coin. When you're dealing with developers and you're, and it has, like, even as a and I'm a lifelong developer.

I've been doing it for decades. Uh, and I see, you know, and I, you know, every day on on social media and stuff, I see people. Um, you see the developers that are embracing agentics fully and their their org structure, and then you see the ones that are like, Oh, it still sucks. And you know, I'm, I'm still, you know, you know, you know, all that stuff and like, and how. What was your experience as you dived into the pool of developers trying to to get the embrace going here?

So for a while, um, if we look back, so back then, you're like, Oh, this is great, but it wasn't that great, right? I mean, and and there there. In the early days, it was good for that time, but compared to now, it was, it's not. And so developers who would like maybe try, um, the tools, and they didn't do a great job. You ask it to write a feature or something. It's like, what, this is stupid, you know?

Um, those developers, I found once they tried it once, if it didn't work out well, they kind of threw their hands up. Um, and it wasn't until, like, end of maybe 2025, when the like, um, was it four, like, Sonnet, four, five or four, six? I don't even remember the versions anymore. But it was like this point in about November of 2025. That was And the models, it that, the models, just got really yeah, that's, good, um, but we couldn't wait until then.

Like, I had a mandate to, like, get everybody using AI and to increase our developer velocity. And so what I did thinking back to that change management and, uh, I. It was too much of a lift to get it. Three 500 developers to to lift everyone at the same time, especially when you have all of these emotions involved and you have this resistance, right? And I would say, like, we had quite a few people who were resistant to this.

So what I did? Instead, there's this, this rule, um, it's called the the one, nine, ninety rule, and this rule essentially says that in any community, there's gonna be one of that community that are creators. Think about, like social media, anything like that, you'll have nine that, you know, they'll dabble here and there, the tinkerers, if you will, and then the the 90, the bulk of people are consumers, right? Um, and so I said, if I look at our engineering organization through that lens, let me go and put together the one.

And so I went across the org and I pulled people, and they didn't necessarily have to be the the drunk off the Kool aid, like AI pilled people. Um, but I just needed representation from every major repo that we had, um, you know, our largest ones, our critical ones. Uh, I wanted people from various teams, different types of repos as well, so I needed front end and back end, and mobile iOS and Android. You know, I needed these people, and so I did this little week long campaign, just going across the org.

These people don't necessarily. I'm not their 1st line manager, right? So I need to get buy in from their 1st line manager. That's a totally different conversation, cause a lot of them weren't even bought into this, right? Um, but I say, Hey, listen, you know, you have this mandate, you gotta get people to use AI on your team. Give me one person, um, that I can have 30 of their time. And what I wanna do is one.

They all come together, we learn all of this stuff, but it's not just for them. What I need them to do is build that knowledge back into the systems themselves so that your entire team benefits from this, right? And so they were there with me, we drank it, it was 50 of them, um, drank it from the fire hose. Trying things out because things are changing so quickly, there's so much noise, you don't know what'll work, what won't work, right?

Everything looks great on Twitter in a little demo, but uh, we're working with huge, you know, mono repos with, you know, hundreds of services in them. Like, you know, we're working with people's money, you know. These are enterprise systems that you have to approach this a bit differently and much more carefully. And so they would try things out, we'll see things, we'll try them, some things will work for maybe a specific type of repo, like, Okay, this works great on Um web sucks for mobile, right?

We can't use that technique. But together, the 50 of us were able to, like, try a lot of things, figure out what works. Maybe I do have something that works on my iOS repo. Hey, other iOS repos, here's what I figured out, right? And then, like I said, embed this stuff into the system. So things like context engineering techniques, things like, you know, agent CMD files and and agent skills and all of that baked into the repo.

So that no matter who was pointing their agent at this repo, the agent could work the way that your team wanted it to work. Because it was baked into the system. So we didn't have to, you know, teach everybody how to do this. These champions essentially did that for them and filtered out the noise for their team. So they would bring back the things that actually work, that are tried and true. And then they would do a brown bag session or something with their team.

Like, let me show you guys what I put in the repo and why it's working for you. All of a sudden, you know, um, so that that was the technique, uh, that we used there, and it worked really, really well.

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So that is super cool. I'm going to, uh, to borrow your techniques myself, uh, going by, I bet a few other folks listening, uh, or watching, will do the same. Um, Really insightful there, uh, in terms of how to approach that. Um, as you as you arrived, uh, having gone through a lot of this, and you arrive at the Agentic AI Foundation now, and and you're kind of it's brand new as an organization, yeah, you're standing it up.

yeah, Um, you're yeah, taking on the responsibilities. yeah, Could you talk yeah, I think that's a a bit a great point. about, like, what Um, and was it like to get and the foundation uh, going and get it focused and get the right people? yeah, yeah, Uh, and and I think that's a great know that you were point. Um, and were doing the things and uh, that needed and and what those are.

yeah, so, uh, this agentic AI foundation was formed, um, end of 2025, so it's been what about eight or nine months at this point. Um, lots of excitement, right? Uh? We had dozens of companies that were interested in being a part because everyone sees the need for this. Everyone is also innovating at lightning speed. There's so much innovation that's happening right now. And if you have anything that you're creating, that's like, you know, oh, this, we don't have this figured out.

We need a new standard for this. No one wants that standard being cooked in one one kitchen, right? Um, if we're talking about agentic commerce, for example, it PayPal doesn't want Stripe figuring that out by themselves, right? They wanna work together, or they need to work together, and they know they need to work together. And so what the Agentic AI Foundation has done is provided this neutral home where all of these various companies can come and have these conversations together.

So we have, um, working groups, essentially, where the members they've, okay, which working group do you wanna be a part of? And there's so many of them. There's like, like I said, the agentic commerce, right? So if you're figuring out how agents are gonna buy stuff on the web, all right, I need, oh, I need these, I need, uh, PayPal, I need Stripe, I need. You know, all of these various companies together, and they work on these standards together.

I like to think of it as they are defining the rules of the game and creating the game board together. And once they have that figured out, it's like, all right now we can compete deal, you know, deal me in, right? Um, and so that's what the Agentic Foundation does. It also houses those standards or those projects. So, uh, right now the projects are MCP agent, SMD, Goose, um, agent, Gateway, and then also just this week, uh, A2A, which is Google's agent to agent protocol, um, has come into the foundation.

And so these projects now, you have companies from all over, uh, contributing to these projects, right? Or these standards. You then give it, like, you know, more of a voice. If you, if you wanted to use one of these projects, but it lived in one of these companies, you might be a bit hesitant, right? As a company to build your products on top of this if it lives with this one company. I don't know what they're gonna do, I don't know if they'll like, kill it, I don't know, uh, if they'll.

Just the roadmap will only reflect their goals, you know what I mean? And so this being a part of the Agentic AI foundation gives it that confidence that, hey, this is in a neutral place. I I now can build on top of this, and so that that's what it looks like. We do a lot of education around the projects, the protocols, we throw conferences, uh, in all parts of the globe. And I'll say, like, one one really cool, uh, aspect of this role.

So in my last role, went deep on agents. But I'm also inside of my company, right? Um, a little bit in open source, I'm consuming, but I'm still my bubble is probably North America. Now. This is a global foundation where my job is to pay attention to what is happening across the world. How are they adopting agentic AI in Japan, in China, in Africa? You know what I mean? And so, um, now I have this, this global perspective, which is absolutely fascinating.

And part of the role is also to help these various countries come together, uh, on these standards and protocols and projects so that they're interoperable across the board.

I, I'm curious, so that I that does sound super cool. I I'm curious, with that global perspective that you're that you have developed in this role, like, how, how do you? how do you assess? I think I think it's very easy, um, for for pretty much, I think it's easy for anyone kinda coming from their own perspective and their own little bubble that they're in. To kind of assume I'm doing agentics and everybody else is doing it just like me or has the same needs and stuff like that.

And and so I think it's very easy to forget that. Uh, diversity of location, diversity of life, um, all those things can change the user's need. Uh, for that. And so do you have any, any particular highlights from, uh, that global perspective on things? Maybe that surprised you, or that that caught your interest? I'd love to hear some of that,

so I would say in places like China that are mobile 1st, right? Um, the way they use technology is a bit different than us. Um, so we're in North America, I would say a very like, SaaS heavy culture, uh, whereas everything is like mobile over there. And so now, like they, for example, they have a big need for a protocol like agent to agent, where you need like this app to be able to talk to that app, and they're both agentic apps, right?

Um, and so they could, like, use that, like, for example, like WeChat uses that, uh, you know, with various agents and stuff like that. So that was really fascinating to me to just see, like, oh, even the types of applications you're using, uh, um, essentially influence, like the the types of tech that are standards or or like anything like that that you might need. And so that's just one example. Yeah,

that's, that's cool, I'm curious, so, and this is where I'm gonna be selfish on my part. Um, I, I'm as an engineer and, uh, and a research scientist, I'm very focused on autonomy. And and you're, and as you're getting into mobile and that's getting awfully close to, you know, thinking about edge concerns and stuff like that. And um, and embodied intelligence, you know, is is is such a hot area, it's certainly the area that I'm focused on.

Um, and and you know, the the the rapid rise of robotics, uh, in all domains, you know, whether they're ground robots or flying things or whatever is is truly taking off. Like, like it never has before. Uh, no pun intended there. Um, I'm curious how with with this kind of, and and I I think in some parts of the world you see that more than others, I think in in China, Japan, uh. And there are certain places where you're gonna see a lot more robotics than you will in the US.

For US. listeners or watchers, we don't have nearly as much that's of that here.

that's right.

A And so, like, how does how? When you're looking from from trying to, uh, to take these projects that the foundation has. And you're looking at those different needs. And you're seeing. Well, you know, the Americans and the Canadians and such, you know, K kind of have one way of doing it, and the Chinese and the Japanese and other, you know, like that may have a different way. How do you reconcile? Because that's quite different, you know, in terms of how you're using agents in those ways and the way you're configuring it and the way you're constructing them, and what their utility is.

How do you? How do you approach that? When you're trying to make everybody happy with standards that are truly meant to be global?

yeah, that that is why you need everyone at the table, right? And so, uh, if you only had, like the your your top like FAANG companies in the US. kinda determining all of this. And there's no one from these other countries that, hey, robotics is like a big deal here. Like, we have to think about the physical applications as well, right? Um, then you miss that perspective, right? And and not to say like they don't have places there, but you need leadership from those companies to also have a part in crafting the story, right?

Um, and so that's exactly like what the working groups do, like, find your lane, uh, get into it, you know? Europe is another good example, so they just rolled out the EU AI Act, right? And so that, like, is gonna change, um, the transparency that these systems has, and that's global. If you're gonna be serving anything to someone in Europe, then you have to be able to, uh, adhere to these, these new, uh, legislations. And so that's another example where, okay, I don't care what country you come from, you have to one be aware of this and two also, uh, help define how this should be done, right?

Um, there was a lot of backlash on how Anthropic rolled this out, for example, right? Um, and so we have a working group that is looking at, are there some systems that we could build, or some standards or something? So that everyone doesn't have to reinvent this and figure out how they're gonna do it right? So then you have the voices from various countries together to figure this out and say, Okay, what if we did it this way?

They haven't solved that yet, by the way, but that's a, you know, a active group that's meeting regularly. And by the way, all of these UM working groups are open, so anyone can join them. Uh, just, you know, they have meetings, they're public. You could just like, kinda go into it, see what they're talking about, even, uh, you know, chime in with with thoughts of your own. But these folks meet, and and this is, you have one for security, you have one for identity.

Like, you know, any lane that you care about. Um, there's, there's someone there, like, kinda working on this from across the globe.

Yeah, I know, um, as a as very specific to to that, uh. It was just a few days ago that Anthropic released their paper, uh, along with a blog post on watermarking, um, so that you can detect, you know, AI generated content and all that, which was a fa. Like, if if, uh, we're. This is probably not the only episode that's gonna come up on it. I think we're, we're gonna talk, we're gonna probably do a deep dive on that very soon.

And uh, hint, hint, uh, so uh. But that that is one of those things that, you know, to your point, like, affects everybody. And and there probably needs to be somewhat universal, uh, approaches to what. What is watermarking, how should it be applied, what should it be applied to? How do you d, you know, how do you utilize that? Uh, both as the provider and as the the consumer of that. yeah. Or do you Um, is even do watermarking?

Is or do you there a a do?

better way to do that? You That's know?

right, that's right. So, um, uh, I'm that. I think I. I'm starting to see lots and lots of different utilities. I I imagine the foundation's gonna grow quite a lot in the, uh, in the years to come.

yeah, that's definitely a lot of work to do.

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So as we, uh, as we start, uh, getting to the point where we can. I'd love to dive into, uh, kind of maybe get a high level overview of the of each of those projects that you described, uh, a little while ago, just kind of what it is for people that aren't familiar with them. Um, and then and then maybe dive into, like, where some of this stuff is going, you know, based on where you're at.

I know that you and I have talked about MCP, um, a and other things, so I'd love to. I'd love to go wherever you wanna go in terms of some technical deep dives, uh, cause we love that here.

yeah, sure. So we have, um, agent MD. So this was a standard created by Open AI, and this one standardizes, like how projects, uh, mainly like codebases, communicate their their operating instructions, right to agents. And then there's, um, Goose, which is, uh, one of the 1st open source AI agents, and, uh, this one essentially provides like this agentic runtime. And then there's, um, MCP, of course, which connects agents to, uh, tools and systems, um, agent gateway.

This one was, uh, oh, and I didn't tell you, Goose came from Block and MCP came from Anthropic. uh, agent gateway came from a company called Solo, uh, and uh, Solo, uh, created agent gateway to mediate traffic. So, um, essentially like MCP traffic. A2A. As you're using this stuff in enterprise, you kind of want some controls around, uh, what the agent is doing and what it has access to. You wanna, uh, you know, make that observable and stuff like that.

So agent Gateway is a open source project that does that, and then um, a2A is, uh, the the newest addition. This one is from Google. A2A is the agent to agent protocol. And this one is really cool in that this is how agents can coordinate with other agents. So you can delegate work to another agent, or, you know, um, uh, just be able to collaborate on a given task, right?

That's pretty cool. The I I'm curious, you know? One of the things that that I know in in my world that I've been, uh, exploring is, you know, if you look at late last year and people would just have an agent, you know, to do something. And then, you know, we kinda moved into this year. And people are doing multiple agents that are starting to collaborate a bit and you're starting to have that, that kinda cross talk and collaboration.

And then now we, uh, you know, as we record this, we're in August, uh, and um, and we're talking like, it's gone up orders of magnitude in terms of it's, it's some, and like, that's not everybody. This is some use cases where you're talking tens of thousands of agents sometimes, or hundreds of thousands, or even millions. Uh, are now coming into play. And as you're, I'm curious, like, as you're looking, that that has to be a challenge to some degree from a scalability standpoint.

Because, you know, going back to what you were saying before, we're we are racing along so fast, um, much faster. And I'm, I'm old enough to remember, like, I, yeah, I, I won't, I'm, I'm old. And therefore, I remember before internet was even a thing, uh, and and I was even an adult at that point, sadly. So, um, and so, like, I know the velocity that things happened across each of the various technological revolutions that we've had, uh, over the past lifetime, if you will.

And so this is going so much faster than any of those others, and all of those have had um, processes. You know, that's why the Linux Foundation itself, you know, came into being, and and lots of others where these technologies came. There was the need to get collaboration across competitors, uh, and across, uh, global uh, concerns and needs. Um, but but you've stepped into the fastest moving area ever. And and it's gone in just a space of months, from like singles to millions.

And as we like, how does? How does a working group, and especially considering that these are at the end of the day all competitors, these different members, you know, in their, in their own businesses, how do you manage that? Because by the time working groups like historically, by the time a working group would arrive at something like, sometimes you were so far past that. So how, how does? Is there anything you know like, are there any expected timescales or anything on how to get these things together?

So that it stays relevant, because the speed, the speed of relevance is is just unimaginable now. So in terms of how fast that is like, how does this new foundation address these kinds of of problems that we've? We've had to a lesser extent, but never like today. How do you do that?

yeah. We knew going in when we were standing the foundation up. In fact, that was a question, do do we do? we do? A foundation Foundations are slow, you know,

Yeah, I guess that's how and and this is, people think, this is not Yeah,

slow, this is not a slow moving space. Um, do we do this, right? Um, we. We realize we have to do this because you, you just have to have these neutral homes for things that are this critical. But we cannot move at the pace, uh, that your traditional foundation will move at, so we move a lot faster. Um, and I think it really helps that the folks on a working group, these are not volunteers doing this in their spare time, like it is part of their job, you know, to innovate the future.

And if you know, hey, we, we are trying to build a product on this standard, then you're gonna speed everybody else up. We have to come to some conclusions here, right? Um, and I think that really helps. Is that the innovators themselves are the members of these working groups, and so they have, uh, uh, basically, they, they, they have to move much faster. They have an incentive to, uh, not drag this along, you know?

yeah, it does. Um, I, I'm curious, you know, when you see, uh, when they come into the working group, is it, you know? And you're talking, you know, what are to the rest of us on the outside? Very fierce competitors, you know, you know, OpenAI and Claude, and you know, they're hammering it out and Google's in there, and you know, there, there's a whole slew of them. Um, and and is is the is the is the tenor of the conversation, um, a little bit, uh, is it?

I guess? Cause a they gotta get stuff done, as you said, you gotta get stuff done because everyone's waiting to move on. Um, does that collaboration? Do they kinda just draw? I'm just, it's just as a sheer curiosity. Do they just drop? Kinda that external competitive behavior and just get in and say, y'all, let's just get it done and and is that

they do. It's fascinating. They actually are very, uh, friendly with each other, right? And so like, they, they sure, like, Yeah, our companies just got into this heated Twitter war or something, but you and I gotta figure this standard out, you know what I mean? And

you can let those crazy so, people talk? But we gotta get this thing done right now. it's super, super Okay,

collaborative, which is amazing, it's amazing to watch. Uh, I tell people like, if you wanna see the beauty of like, open source and people working together from competing companies, all you gotta do is go in the MCP Discord server. It's a thing of beauty. There's just like dozens of these working groups within that protocol itself, and you have members from everywhere. Every company that's like doing real work, not just throwing ideas out, but like doing real work.

To, uh, add new features or figure out like how, how to do this other new thing or solve this problem. Um, because their companies depend on those things, right? And so it's beautiful, it's actually really beautiful to see.

so as we start winding up here, I'm curious, like, uh, it, it's just it's just kinda, you know, just the the speed of operation, um, is a little bit mind boggling. As you're looking ahead and you guys have put together this foundation and you're having those really, those really productive and rapid conversations to get stuff done. So that, so that this world continues at the velocity it's at, like, where, what are? What are some of the things that you might expect to see having come along the path?

Cause, I think you're in a bit of a unique position to say, I, you know, you've. You've built into this. You're one of the people that set the foundation up, you've seen it start to work, and you've seen it working well, you know, and and with that, with those kinds of relationships forming and everything, how do you see things moving forward? You know, what, what? Um, and it. You can be a little speculative, it's fine to be wrong.

I say things on the show all the time that are wrong. Um, uh, Daniel and I are like, Oh, oh, got that one wrong, but but we try, but I. But it's fun to. It's fun to try to think, you know where, where might things go? Um, what? What are your thoughts like, where do you think, where do you think we're heading? Uh, uh, into? This brave new world where everyone's trying to figure out, not just like, what, like, no one knows ten years, but like, like, people are trying to figure out what is it gonna be in six months?

Um, what? What if are your thoughts around we, if that?

we look at like you and I, you know, and probably everyone listening to this podcast, um, we kinda live in this bubble where, you know, we're likely very exposed to AI, we're working with it daily. That is not the case across the the world. Like, you know, the general population, uh, like you said, one, they hate AI, and two, they probably are not using it like in their day to day, right? Maybe they've asked ChatGPt a question, you know, they searched from something for Google and a little summary came up, and that's pretty much the extent of what they've done.

So outside of our bubble, like, we have so many challenges right now, just amongst, like, the tech community. Um, outside of that, when you start looking at how, like, the everyday person is going to, uh, utilize agents for all sorts of things, right? Uh, within their lives. You just start seeing all of these other things that we need to figure out, and so the I think that there's a lot we have to figure out. I think that'll consume us for the next couple of years.

Um, I do think that, uh, AI will become a part of, you know, the the everyday person's, uh, day to day, just like mobile phones and internet have. I think the same will will exist. I hope, I don't know, but I hope, um, we're not just giving it all to the agents and we become, uh, workers for the agents, you know what I mean? Um, I hope that we. We kinda get to that middle ground where we find, even though it's capable, this is not a good use of it, and these are the ways that we should be deploying it.

Fantastic, that's some I I, I share that with you. Uh, I think I think we need to find the, you know where, where does the human fit into the equation? and where? where is AI? Uh, a tremendous utility. Um, Angie, thank you very much for coming on the show. This was a great conversation, really appreciate it, gave me a lot to think about. I plan to dive into into some of those projects myself, uh, and learn a bit more about them.

And, uh, thanks for coming on the show. Hope to have you back sometime.

Thanks so much, Chris, I enjoyed it.

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