[AIEWF Preview] Containing Agent Chaos — Solomon Hykes

**Alessio** (0:03)
Hey everyone, welcome to Latent Space Learning Pod. This is Alessio, partner and CTO at Decibel, and I'm joined by Macaulay Swicks, founder of Small AI.

**Macaulay Swicks** (0:11)
Hello, hello. And today I'm so happy to have Solomon Hykes join us. Solomon, you're most famously the creative Docker.

**Solomon Hykes** (0:18)
Hi, thanks for having me.

**Macaulay Swicks** (0:20)
You started Dagger six years ago, and I think originally it was pitched as some sort of infrastructure provisioning thing. I'm sorry, I'm probably totally mangling this in front of you. How do you introduce Dagger today?

**Solomon Hykes** (0:32)
So Dagger is, I think, six years, yeah, six years, I guess sounds right. Yeah, it's a workflow engine. It's an automation tool for software teams that would deliver software faster, more efficiently. And it takes all these workflows that are usually semi-automated with artisanal scripts, you know, your builds, your tests, you kind of end-to-end pipelines.
And it turns them into robust, modular workflows that you can drive with codes, and it all runs in containers. So it's highly portable, highly isolated. You can run them locally or in CI, which saves a lot of time. And we're an open source platform. We've got a very active and engaged open source community, mostly made of platform engineers, you know, those systems engineers that actually design the factory and run it and enable the developers on the team to be more productive. So that's our core community.

**Macaulay Swicks** (1:27)
Yeah, in some ways... Yeah, sorry, Guy.

**Alessio** (1:29)
I was going to say, just to make that clear, these are both pre-development, so spinning up an environment for people, and then also between you're writing the code and getting ready for production. Are those basically like the two entry points?

**Solomon Hykes** (1:42)
We started mostly post-development. So anything that happens after you've saved and you're ready to see what happens next, you know, build tests, you want to take that live. So there's that delivery loop, right? We've been focusing on making that delivery loop more efficient because it's really terrible in most places, and there's a lot of inefficiencies that could be cleaned up. In a lot of ways, it's a cobbler's, you know, the cobbler has no shoes situation. Like those platform engineers, they spend all their energy and their significant experience helping developers get the best possible tooling and the best possible experience, but they themselves for their own tooling, it's sort of like, okay, we got to cobble this together with bash scripts and YAML. So we've been focusing on that post development. Although recently we're getting pulled into the dev loop, in part because of this crazy change that's sweeping the whole market, right, with agents.

**Macaulay Swicks** (2:37)
Yeah, so I think let's kind of run right into that. Obviously there's a lot more of context on Dagger and Docker that you've done prior, but we are an AI podcast, so why not? Let's just go right into it. A few months ago, you messaged me and you were like, I think this is the biggest idea I've had since Docker itself. And I was like, what? Docker is very big. What is your context going into the AI builders? In some ways, I've always said basically to us dev tools people, it is just more of the same. Everything that you wanted, you just need 100x more. So how did you approach this?

**Solomon Hykes** (3:12)
Yeah, we didn't think of ourselves as an AI company. We got pulled into it by our community, our users. Because although Dagger is primarily used to build CI-CD pipelines, historically, we've never thought of ourselves as a CI-CD company. We like to build platforms from first principles, and then we encourage our community to go and apply it. So what we have is an engine for automating workflows, making them reliable, portable, and giving them very clean environments to run in. And the environment is key. And of course, we use containers because that's what we know, and the container tech still today is underutilized, misunderstood. It can do so much more. So that our community pulls us into this AI space because of agents, because these platform engineers start messing with agent loops. They want to insert LLMs into their workflows. And now it's becoming more popular to run agents in the context of your CI, to automate more parts of your delivery. And then they started showing us that everybody wants to use these coding agents now. You know, so if you're a developer, increasingly your job is not going to be to actually develop, but to manage and enable these coding agents. And we're at the very beginning of this. You got this one agent and your IDE helping you, but now you want more than one, right? You want a team of agents sort of doing the work for you and that transition from team of one to a team of multiple coders, that's basically what our community deals with, these platform engineers. So what we're witnessing is developers becoming platform engineers. They have to learn how to enable others to be productive. These others, of course, are AIs. And to do that, they have to give them environments to work in. And you can see the problem when you see someone livestreaming their vibe coding, right? Everyone's vibe coding. But you can kind of make one set of changes at a time. You're kind of, everyone's sort of messing with this dev environment that really isn't cleanly isolated. So what we're doing is we're taking this technology that we invented for CI CD and bringing it into the coding agent's environment and giving your agent basically a perfectly isolated, reusable, and portable environment so that you're not completely locked into this one app connected to this one model running in this one cloud infra provider, right? You want the environment where the agent does its work to be decoupled, to be its own thing that you can manage and look at and then move to another platform if you want, right? That's sort of what happened with Docker in the previous wave when everyone was adopting cloud technology, right? Everyone was building these big platforms and they had everything, but they were highly fragmented. They tried to kind of cobble everything together like a monolith. So you didn't have this portable environment that you could carry around with you. You were trapped in one big platform and the same thing is happening now. So we want to use our experience from the past to enable this new generation of developers to really unlock the potential of these coding agents.