Transcript
A (0:03)
Hey everyone. Welcome to a latent space learning pod. This is Alessio, partner and CTO at Dazable. And I'm joined by McCoy Swix, founder of Small AI.
B (0:11)
Hello. Hello. And today I'm so happy to have Solomon Hikes join us. Solomon, you're most famously the creator of Docker.
C (0:18)
Hi, thanks for having me.
B (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?
C (0:32)
So Dagger is I think six. Yeah, six years, I guess sounds right, yeah. It's a workflow engine. It's an automation tool for software teams that want to 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, your 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.
B (1:27)
Yeah, in some ways. Yeah, sorry, go ahead.
A (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 done writing the code and getting ready for production, are those busy, like the two entry points?
C (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 it just, there's a lot of inefficiencies that could be cleaned up in a lot of ways. It's a cobbler, 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 gotta 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.
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