How Warp ships 2,000 PRs a month with AI factories | Zach Lloyd (CEO, Warp)

Claire Vo (0:00)

Can I give you a hard time that humans really are the bottleneck? Because if you look at kickoff to PR time, it's 35 minutes. But if you look at PR to first human review, it's three and a half hours. And when you're doing, I think it was like over 2000 PRs in the last month. Like, how do you keep things in the team from going, as I say, like chaos reigns?

Zach Lloyd (0:20)

What is a software factory? For us, at least, it's an actual noun. It's like a product concept where it consists of a bunch of repos, a bunch of like MCP servers, like a bunch of configuration and then a bunch of agents, essentially, so like a code review agent design, different agents, different automations, and it's all defined in code. Scoring happens across all runs, but then there's a second loop, popular thing on Twitter right now called self-improvement, where you have like an observer agent and it can then create updates to your factory that will try to prevent the particular failure mode. One of the things that's most helpful is like you could have these factory agents do computer use verification. So in this case, it made a video. I'm just like talking to this thing that is doing this job that I've done for the last 20 years, and now it's like doing it kind of better than me.

Claire Vo (1:11)

Spoiler alert, the humans are the problem.

Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive, here on a mission to help you build better with these new tools. Today, I have Zach Lloyd, CEO of Warp, and he's going to show us exactly what he means by the software factory. He's going to show us how you can kick off tasks in Slack, what it means to go beyond the software development lifecycle, and how a technical CEO uses non-technical tools with AI. Let's get to it. This episode is brought to you by DX. In a recent study across more than 500 engineering organizations, DX found that spend on AI tools has grown 28x over the last year. The share of AI authored code is climbing, but overall innovation has remained flat. As teams generate code faster, new friction in code review and validation is offsetting those early velocity gains. DX tracks speed, quality, and cost together across the software development lifecycle, giving engineering leaders clear visibility into how AI impacts delivery, and whether those investments are translating into real value. Download the full report at getdx.com/how I AI. That's getdx.com/how I AI.

Zach, thanks for joining How I AI.

Zach Lloyd (2:38)

Thanks for having me. Excited to be here.

Claire Vo (2:40)

There are a lot of trends on the timeline right now, but one that I think is going to be big for 2026 or seems to be big for 2026 is the factory. The factory, this fantastical idea that we have that we're going to input tokens and output enterprise values, something like that. At least we'll output code.

I'm excited for you to show us as CEO, as engineer, as builder, what to you is the factory and how it looks inside Warp.

Zach Lloyd (3:12)

The factory is definitely trending. I actually don't love the term factory, but it is the thing everyone is standardized on. It feels a little bit dehumanizing to me.

But yeah, the idea is exactly what you said. It's like how do you, in a world where we have these magical agents harness their power in a more organized way to have them basically build software for you from your ideas. So yeah, excited to show you how I use factories and what it means to me.

Claire Vo (3:48)

I was at Lenny's Summit recently, and I think Marty Kagan also said he hated the word factory. I wonder if it's more like Santa's workshop, right? Like we have magical elves that craft wonderful things that spark joy and are delivered gift wrapped for us. So I'm gonna say the AI magical workshop.

So show us what does this look like for you? Yeah, you just say you put in your ideas, you output product. Is that real? How does that really work?

Zach Lloyd (4:19)

Yeah, so it kind of works like that.

The way that I think of factories is like there's basically two types of personas who are using them. So there's, I'll show you basically how we do this in Warp. There's like the builder persona. The builder persona is someone who is contributing ideas, wants to build stuff, and from that persona, it doesn't look, at least the way that we have it set up, it doesn't look that different from like how one of these engineers or designers or product people on our team might build with a local coding agent. The big difference, you can see here, so this is like, this is our Slack, is that most work is starting in a public place. And so the way we think of factories is like, you basically can say in a public Slack channel, you can tag, we named our factory Wilson. You can tag Wilson and be like, okay, I want you to build something for us. And when you do that, what Wilson will do is like, essentially do not just like the direct build, which is what you might get if you're using like Cloud Code or Codex, but we'll also do a few other steps. So what it will do is it will kind of go through all the steps of like, first it will triage whatever this is. So it'll treat it as like an input to the factory, not just like a direct thing to build, meaning it will, for this one, Harry's saying he wants to change the way this feature looks. He gives like pretty detailed instructions. He attaches an image. He says use computer use. And this kicks off a flow where the first thing that the factory does is actually kind of open an issue. So you can see over here, it's like we use linear in addition to using Slack so that everything gets tracked. So the factory integrates not just with Slack, it opens an issue.