Flo Crivello: prediction

Transcript context

…anywhere, frankly? It's like every part of the stack and every part of your process is stretched to its very limits right now. That's just write down tech. You know? Like, I'm sure you've seen the graph. Like, GitHub posted a graph of, like, number of commits posted per day. GitHub was, like, hardly, like, a subscale company. It was really big. It's it's just going vertical right now. It's just going to the moon. You know? And that's that's, like, I think, indicative of of what every company is going through. Our number of PRs internally has, like, PRs per week has tripled over the last three months, and, like, the number of lines per PR has tripled over the last three months. We hardly review PRs anymore. It's just agents reviewing PRs. We insofar as we review basically, what the the way the team is talking about this, like, we'll no longer PR review wheels. We'll, like, PR review wheel review wheels. You know, we'll we'll just review in the machine that reviews the PLs. As a result of that, they're like, this is awesome. But, hey. Now CI is in is in the middle of that. So what do you do? Well, now you gotta work on CI. And so we've we've spent a long time working on CI. Like, for the nontechnical agents out there, like, CI continuous integrations, like, the process that's involved in taking into account your code changes and making sure they're safe and actually melting them into your main product and deploying them. And so we we at first, we started throwing money at the problem like many people do. And so now our CI is extremely expensive. It's like it's a it's a it's just an insulting expense. And and and we've exhausted all the all the obviously, like, we're obviously not running on GitHub runners. We're running on, like, GCP runners, and, like, we've we've done, like, caching of the builds. We've done all the obvious things. It's it's a lot of work to manage CI to make it to make it efficient. And and and so we I was tired of this because it was, like, weeks of messing with CI and and, like, building a hole in our bucket. And we're like, what are we gonna do about the CI thing? And then I was like, wait a minute. Like, why are we doing all of this ourselves? So, like, can't we just, like, spin up an agent to do it? And spin that. The agent was literally and so by the way, that's the other reason why it's important to have a a single agent because setup now is becoming one of the biggest costs because the biggest cost, the biggest bottleneck in any organization right now is human time and human attention. So you wanna remove that guy as much as possible. So you wanna be able to provision agents and give them all the accesses they need without a human in the loop as much as possible. Okay? And so is this agent at the company. It is this AI employee that does everything there is to know by the company Lindy teammate. Right? It's got access to our repository. It's got access to it's got it on the computer. nt at the company. It is this AI employee that does everything there is to know by the company Lindy teammate. Right? It's got access to our repository. It's got access to it's got it on the computer. So we're like, Lindy, can you please, like like, mess with our CI? And it's like, yeah. Let me look at, like, the runners using the GCP CLI. Let me look at, like, the GitHub, like, action and all of that stuff. So it's doing, like, a lot of analysis. It's getting back to us, and now it's literally it's basically like an auto tune, like, an auto optimization thing. Well, like, Lindy is just, like, sending us a graph, like, every day, by the way, using ImageGen to generate. So the graph is, like, really pretty. And it's like, hey. You know, guys, like, look. Like, CI cost is going down. Time time to merge is going down, which is a good thing. And I was like, I can't believe it took us two weeks of just, like, messing with CI ourselves instead of just saying this to Lindy. You know? So I think this is what it's looking like right now. It's like engineers are are, like, less and less working on the thing. They are more and more working on the thing that is working on the thing. And more and more, what we do is, like, we we're setting up this machine, which is the company, which which just increasingly operates itself and and increasingly will more and more like you know, I like to think of it as, like, first, you become a manager of ACs, then you become, like, a director of managerials because at some point, like, the managers are gonna become gonna become AIs as well. I'm hopeful that at some point, we become board members. We can just go to a beach in Hawaii, and we and we we don't have much to do except, like, review the strategy of the company. So we'll have, like, reports of of the agents telling us this is what's going on. This is the landscape. You know? This is all the results we're having, and we'll be able to have much deeper conversations about the nature of the company we're building and the the the spot we occupy is the market. I that's a dream as far as I'm concerned, and that's that's not very far away at all. To answer your question, have we have there been positions we've not hired? Like, yes. Absolutely. You know, we we the team is actually I think headcount has been flat now for a while, and we've again, like I said, we've actually tripled our productivity over a couple of months. I find there is a bold deluxe zone because humans are still in the loop. Humans are still needed. But, obviously, the more humans you add, the more coordination costs you you introduce inside inside the company. And so I I find that actually right now, teams, relatively speaking, are at an advantage versus bigger teams in in a lot of ways. Do you I'm sure you do. I don't know if you wanna share it, but do you have a ratio of not I don't mean all inference spend, like, including your customers' use cases, but, like, your own internal inference versus your payroll. How is that ratio spreading?…

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