Lindy uses its AI teammate to optimize its own CI

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 53:17

   Yeah. So what does life look like at Lindy internally these days? I think it strikes me that you're now, I'm sure there's been like a dog fooding process. I know there's been a dog fooding process throughout the history of the product, but now you're at this point where it's like, there's no limits to the dog fooding, right? You can do anything. How does that play out in terms of i don't know you could cut it any number of ways right are there roles that you might otherwise hire for that you just wouldn't hire for now are there uh what's the ratio of your own inference spend for the purposes of building lindy compared to your payroll you put your own lenses on it but how has the arrival at the human or at the ai employee stage of this process changed what it's like to be a part of the company?

2. 54:14

   That's a great question. And I think right now, I mean, obviously, AGI is here. And so obviously right now, every company is sort of scrambling and there is that time of transformation that's accelerating. And I will say, and I'm a little bit of a doomer, I'm worried about AI risk. But so far, so good. And so far, it's so much fun. It's honestly so much fun. Like, to go through AGI, and to build this in AGI, it's like, we can move so much fucking faster.

3. 54:40

   I feel like we're moving at the speed of thought now. It's like, there is no obstacle. Like, normally companies, it's like, you think about the strategy, it takes a long time to figure it out, to implement it, to see the results. It takes like months, like that OODA loop is like months long, you know? And obviously, the name of the game at a startup is to move as fast as humanly possible, because that's the only advantage against the incumbents. And now we can just have ideas and see them live in the product two hours later and like big ideas too like not small ideas and i can tell you so our slack now is basically just us and lindy it's like lindy is like just half the messages on slack is just lindy and us talking back and forth with lindy very often like we we ourselves and we breathe this stuff all day and like we ourselves like we are underestimating the platform

4. 55:28

   Like, just last week, we had, like, a problem with, like, our CI pipeline. We have literally many hundreds of runners on GitHub who, like, manage our CI pipeline. By the way, there's another thing right now to answer your question. What's it like to work at Lindy? What's it like to work anywhere, frankly? It's like every part of the stack and every part of your process is stretched to its very limits right now.

5. 55:50

   That's just right now tech. You know, like, I'm sure you've seen the graph. Like, GitHub posted a graph of, like, a number of commits posted per day. Like, D-Type was, like, hard. 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 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, it's like, we're no longer PR reviewers, we're like PR reviewer reviewers.

6. 56:32

   You know, we're just reviewing the machine that reviews the PRs. And as a result of that, you're like, this is awesome, but hey, now CI is in the middle of that. So what do you do? Well, now you've got to work on CI. And so, we've spent a long time working on CI, like for the non-technical 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 merging them into your main product and deploying them.

7. 56:57

   And so at Philz, we started throwing money at the problem, like many people do. And so now our CI is extremely expensive. It's just an insulting expense. And we've exhausted all the obvious. We're obviously not running on GitHub runners. We're running on GCP runners. And we've done caching of the builds. We've done all the obvious things. It's a lot of work to manage CI to make it efficient. And so I was tired of this because it was weeks of messing with CI and, like, burning a hole in our pocket.

8. 57:27

   And we're like, what are we going to do about the CI thing? And then I was like, wait a minute. Like, why are we doing all of this ourselves? Like, can't we just, like, spin up an agent to do it? And spin up the agent was literally... And so, by the way, that's the other reason why it's important to have 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.

9. 57:49

   So you want to remove that guy as much as possible. So you want to 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 knows everything there is to know about the company, Lindy Teammate, right? It's got access to our repository. It's got access to, it's got its own computer.

10. 58:09

    So, like, Lindy, can you please, 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 image gen 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 sending this to lindy you know so i think this is what it's looking like right now is like engineers are like less and less working on the thing they are more

11. 58:54

    and more working on the thing that is working on the thing and more and more what we do is like we were setting up this machine which is the company which which just increasingly operates itself and and increasingly well 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 managers because at some point like the managers are going to become AIs as well.

12. 59:18

    I'm hopeful that at some point we become board members and we can just go to a beach in Hawaii and we don't have much to do except review the strategy of the company. We'll have reports of the agents telling us this is what's going on, this is the landscape, 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 spot we occupy in the market.

13. 59:39

    That's a dream as far as I'm concerned and 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 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 and 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 introduce inside the company. And so I find that actually right now, smaller teams, relatively speaking, are at an advantage versus bigger teams in a lot of ways.