The Exchanges

Q How do you think about that when running, building agent.ai even? It's like, you know, instead of just choosing one, I could like literally just run across all of them and figure out which one is going to work best.

A I'm a big believer. So, uh, under the covers, when you build an, um, because the primitives are so simple, you have some sort of inputs. We know that what the variables are. Every agent that's on agent.ai automatically has a REST API that's callable in exactly the way you would, uh, you'd expect. Automatically shows up in the MC, MCP server. So you're able to invoke it in whatever form you decide to. And so my expectation is that in this future state, whether it's a human hiring, uh, an agent to do a particular task or evaluating a set of five agents to do a particular task and picking the best one for their particular use case, we should be able to automate that. It's like, I just want to try it. Um, and there should be a policy that the publisher, builder of the agent has that says, okay, well, I'm going to let you call me 50 times, a hundred times before you have to pay or something like that. Uh, we should have, Effectively like an audit trail, like, okay, this agent has been called this many times. We also have a kind of human ratings and reviews right now, and we have tens of thousands of reviews of the existing agents on agent.ai average is like 4.1 out of five stars. And all those things are nice signals to be able to have, but the, the kind of callable, uh, verifiable kind of thing I think is super useful. Like if I can just call, uh, give me an API that says here are …

AI assessment note: “Every agent that's on agent.ai automatically has a REST API that's callable”

Q Yeah. Do you want to talk about the chat.com? Thing. I would love just the back story. It's like, did you just call up Sam one day and be like, I got the domain? Did they kind of get back to you knowing that you had it?

A It's a, it's a good story. Back, uh, in the original ChatGPT days, uh, the first thought I had in my head, which lots of people had in their head, is that OpenAI is going to build a platform and ChatGPT is actually just a demo app to show off the thing. And there's been precedence for tech companies that have had, uh, you know, demo apps to kind of help normies understand the underlying technology. And even after the kind of the boost or whatever. So my original thought was, well, someone should actually create like an actual real product. And so I'm like, and that product should be called chat.com because GPT is not a consumer friendly thing at all. Like that's an acronym, uh, not pretty, it doesn't roll off the tongue. And so like, I'll build chat GPT because that was just a demo app back then. So I, you know, got chat.com. And then as it turns out, chat GPT is like a real product. And I was at an event here in San Francisco that Sam spoke at where he launched, uh, Plugins, I think it was the announcement at that time. Yeah. And that's the thing is like, I had sort of suspected, it's like, okay, things sort of be like, there's no way that OpenAI is going to launch plugins for ChatGPT if they were not thinking of it as an actual platform. It's not just about the GPT APIs. This is like a real thing. I'm like, crap. Like this violates the first rule of Dharmesh, which is don't c…

AI assessment note: “Back, uh, in the original ChatGPT days, uh, the first thought I had”

Q Like, uh, how do you think that changes?

A I think, um, so I'm actually bullish on engineers in terms of their kind of long-term economic value. Um, Not despite all the movements in Cogen and all the things that we're, you know, already seeing, but because of it, uh, because what's going to happen as a result of AI, and people have talked about this, um, in, um, even other disciplines, we're going to be able to solve many more problems. So my math guy in me is like, okay, so we always say, oh, well now, you know, agents are going to be doing code or whatever. And so there's going to be a million software engineer, uh, you know, virtual digital software engineers out there. And so the value per engineer is going to go down because I'm just in that, that same mix I as an engineer. What they don't recognize is that it's not just about the denominator. There's a numerator as well, which is what's a total economic value that's possible. And I would argue that's growing faster than the kind of denominator is that the actual economic value that's possible as a result of software and what engineers can produce, you know, with the tools that they will have at hand. Um, so I think the value of an engineer actually goes up. They're gonna have the power tools are gonna be able to solve a larger base of problems that are gonna need to be solved.

AI assessment note: “I'm actually bullish on engineers in terms of their kind of long-term economic value.”

Q Yeah. I think like something I struggled with, with this conviction, you said you pursue things to conviction, but like, You start out not knowing anything. Yeah. And so how do you develop a conviction when there's, you, you find it along the way where you stumble along the way, then you lose conviction and then you stop working on it. You know, like how do you keep going?

A The way I've sort of approached it is that, um, so I don't generally tend to have conviction around a solution or a product. I have conviction around a problem, uh, that says this is an actual real problem. That needs to be solved. And I may have an idea for how to be solved, uh, you know, right now and that I may be get dissuaded. It's like, ah, I'm not smart enough. Technology's not good enough, whatever the constraints are, but it's the problem I have conviction around. It's like, oh, that problem still hasn't gone away. Uh, so like I sort of filed away in the back of my brain and I'll revisit it's like, okay, well, you know, the kind of board changes, uh, and it changes really fast now with AI, like things that weren't Possible before are now possible. So you kind of go back to your roster of things that you believe or believed and say, maybe now, uh, now is the time. Maybe then wasn't the time. Uh, but I'm a big believer in kind of attaching yourself passionately with conviction to problems that matter. Um, that, and there are some that are just too highfalutin for me that I'm not going to ever be able to kind of take on. I have the humility to recognize that.

AI assessment note: “I don't generally tend to have conviction around a solution... I have conviction around a problem”

Q Turn it to 11. You mentioned Vibe coding, so I have to, uh, this is a blog post I haven't written, but I'm kind of exploring it. Is the junior engineer dead?

A I don't think so. I think what will happen is that The junior engineer will be able to, if all they're bringing to the table, uh, is the fact that they are a junior engineer, uh, then, then yes, they're likely dead. But hopefully if they can communicate with carbon based life forms, they can interact with product. If they're willing to talk to customers, they can take their kind of basic understanding of engineering and how, uh, kind of software works. I think that has value. So I have a 14 year old right now and is taking Python programming class. Uh, and some people ask me, it's like, why is he learning coding? And my answer is, It's because it's not about the syntax. It's not about the coding. What he's learning is like the fundamental thing of like how things work. And there's value in that. I think there's going to be timeless value in systems thinking and, uh, abstractions and what that means, uh, and whether functions manifested as math, which he's going to get exposed to regardless, or there are some core primitives to the universe. I think, uh, that the more you understand them, uh, those are what I would kind of think of as like really large dots in your life that will have a higher gravity gravitational pull and value to them. That you'll then be able to, uh, so I want him to collect those dots and he's not resisting. So it's like, okay, uh, while he's still listenin…

AI assessment note: “I don't think so. I think what will happen is that The junior engineer”

Q How do you think about auth for that? Because part of memory is like selective memory. So take like scheduling. Yep. I want you to have access. If I have another scheduling agent, you should be able to access the events you're a part of. Yep. And like what times I have available, but it shouldn't tell you about other events on my calendar. Like what's that layer like?

A I have so many thoughts on this. This is the, and the, like the opportunity out there, like solving these kind of fundamental, like, This is going to need to exist, right? So right now, the closest approximation we have, um, is, is off OAuth, right? Um, and everyone has, it's like, okay, approve. And it's a very, very coarse, uh, set of scopes, right? Like based on the, the provider of the, um, the OAuth server, be it Google, whoever it is, HubSpot, it doesn't matter. It's like, oh, I pick a set of scopes and they could have defined the scopes to be super granular, fine. Uh, but it's sort of up to them, but that is going to move so slowly, right? So for instance, the use case I have right now, Like I use email for everything. I use it as a, um, like an event and data bus for my life. Right. And why I mean that like, literally it's like, I'm like anything that I do, if there's a way to kind of get that into email, cause I know it's an open protocol, right? It's like, okay, I will be able to get to that data in useful ways. Uh, and this is before, so I have three million that I've built a vector store off of, did it solve my own, uh, personal use cases. So I'll give you the example, but obviously I'm not going to build my, all my own software for everything. But if a startup comes along and says, Dharmesh, can you make your, Email inbox available in exchange for these things. I'm…

AI assessment note: “closest approximation we have is OAuth... it's a very coarse set of scopes”

Q What, how do you define the minimum viable agent? Do you already have a definition for like where you draw the line between a cell and an atom or?

A Yeah. So in my mind, it has to, at some level use AI in order for it to, otherwise it's just software. It's like, you know, we don't need another word for that. And so that's probably where I draw the line. So then the question, you know, the counter argument would be, well, if that's true, then lots of tools themselves are actually not agents because they're just doing a database call or a REST API call or whatever it is they're doing. And that does not necessarily qualify them, uh, which is a fair counter argument. And I, I accept that. It's like a good argument. Um, I still like to think about, because we'll talk about multi-agent systems because I think, so we've accepted, which I think is true. Lots of people have said it, uh, and you've hopefully, uh, combined some of those clips of, uh, really smart people saying this is the year of agents. And I completely agree. Um, it is the year of agents, but then shortly after that is going to be, uh, the year of Uh, multi-agent systems or multi-agent networks. I think that's where it's going to be headed next year. Um, yeah.

AI assessment note: “in my mind, it has to, at some level use AI in order for it”

Q MCP usage. I would say my favorite is the Sentry MCP. I can pull in errors and then you can just put the context in Cursor. How do you think about that abstraction layer? Does it feel Almost too magical in a way. Do you think it's like you get enough because you don't really see how the server itself is then kind of like repackaging the information for you?

A I think, uh, MCP as a standard, um, is one of the better things that's happened in the world of AI because a standard needed to exist and absent a standard, there was a set of things that just weren't possible. Now we can argue whether it's the best possible manifestation of a standard or not. Does it do too much? Does it do too little? I get that, but it's like just Like simple enough to both be useful and understandable and adoptable by mere mortals, right? It's not overly complicated. Uh, you know, uh, a reasonable engineer can put a stand up an MCP, um, uh, server relatively easily. The thing that has me excited about it is like, uh, so I'm a big believer in, um, multi-agent systems. And so this going back to our, uh, kind of this idea of an atomic agent. Uh, so imagine the MCP server, like obviously it calls tools, but the way I think about it, so I'm working on, uh, my current passion project. Is agent.ai. Um, and we'll talk more about the, I think we should, because I think it's interesting not to promote the project at all, but, uh, there's some interesting ideas in there. One of which is around, we're gonna need a mechanism for, uh, if agents are going to collaborate and be able to delegate, um, there's gonna need to be some form of discovery, uh, and we're gonna need some standard way. It's like, okay, well, I just need to know what this thing over here is capable of.…

AI assessment note: “just Like simple enough to both be useful and understandable and adoptable by mere mortals”

Q Yeah. Just to like quickly run through it, you can basically create all these different steps and these steps are like, you know, static versus like variable driven things. How did you decide between this kind of like low code-ish versus doing, you know, low code with code backend versus like not exposing that at all? Any fun design decisions?

A Yeah. And this is, I think, um, I think lots of people are likely sitting in exactly my position right now, coming through the Choosing between deterministic, like if you're like in a business or building, you know, some sort of agentic thing, do you decide to do a deterministic thing, uh, or do you go non-deterministic and just let the LLM handle it, right? Um, with the reasoning models, the original idea and the reason I took the low-code stepwise, a very deterministic approach, A, the, um, reasoning models did not exist at that time. That's thing number one. Thing number two is if you can get, if you know in your head what the actual steps are to accomplish whatever goal, why would you leave that to chance? There's no upside. There's literally no upside. Just, just tell me like, what steps do you need executed? So right now what I'm playing with, um, so one thing we haven't talked about yet and, and people don't talk about UI and agents, uh, right now the primary interaction model, uh, or they don't talk enough about it. I know, uh, some people have, but it's like, okay, so we're used to the chat bot back and forth. Fine. I get that. I think we're gonna move to a blend of, uh, some of those things are gonna be, uh, synchronous as they are now, but some are gonna be async. It's just gonna put it in a queue, just like, and this goes back to my, Man, I talk fast. Um, but, um, I…

AI assessment note: “the reason I took the low-code stepwise, a very deterministic approach”

Q Before we move to the next layer of abstraction, anything else on MCP you mentioned?

A Let's move back and then I'll tie it back to MCPs. Um, so I think the open this with agent data. Okay, so I'll start with Here's my kind of running thesis is that as AI and agents evolve, um, which they're doing very, very quickly, we're going to look at them more and more. I don't like to anthropomorphize and we'll talk about why this is not that less as just like raw tools and more like teammates. They'll still be software. They should self disclose as being software. I'm totally cool with that. But I think what's going to happen is that in the same way you might collaborate with a team member on Slack or Teams or whatever you use, You can imagine a series of agents that do specific things, just like a team member might do, that you can delegate things to. You can collaborate. You can say, can you take a look at this? Uh, can you proofread that? Can you try this? You can, uh, whatever it happens to be. So I think it is, I will go so far as to say it's inevitable that we're going to have hybrid teams someday. And what I mean by hybrid teams. So back in the day, hybrid teams were, oh, well, you have some full-time employees and some contractors. Then it was like hybrid teams are some people that are in the office and some that are remote. That's the kind of form of hybrid The next form of hybrid is like the carbon based life forms and agents and AI and in some form of, uh, form…

AI assessment note: “Let's move back and then I'll tie it back to MCPs.”