[shykes]

Thank you. Yes, I worry about muddling the message. We are looking for a way to communicate more clearly on the fundamentals, then layer use cases on top. It is the curse of all general-purpose platforms (we had the same problem with Docker).

The risk of muddling is limited to the marketing, though. It's the exact same product powering both use cases. We would not even consider this expansion if it wasn't the case.

For example, Dagger Cloud implements a complete tracing suite (based on OTEL). Customers use it for observability of their builds and tests. Well it turns out, you can use the exact same tracing product for observability of AI agents too. And it turns out that observability is huge unresolved problem of AI agents! The reason is because, fundamentally, AI agents work exactly like complicated builds: the LLM is building its state, one transformation at a time, and sometimes it has side effects along the way via tool calling. That is exactly what Dagger was built for.

So, although we are still struggling to explain this reality to the market: it is actually true that the Dagger platform can run both CI and AI workflows, because they are built on the same fundamentals.

[oulipo]

On another note, I'd love if you open-sourced your timeline / log UI component :) it's quite pretty, and could be useful in many contexts haha

Or I'll ask v0.dev to reimplement it, but I think it'd be more complete if you did it

[oulipo]

Hmmmm... so I think the crux of the matter is here: that you clearly articulate why your platform (for both containers and agents) is really helpful to handle cases where there are both states and side-effects

I can understand what you're trying to say, but because I don't have clear "examples" at hand which show me why in practice handling such cases are problematic and why your platform makes that smooth, I don't "immediately" see the value-added

For me right now, the biggest "value-added" that I perceive from your platform is just the "CI/CD as code", a bit the same as say Pulumi vs Terraform

But I don't see clearly the other differences that you mention (eg observability is nice, but it's more "sugar" on top, not a big thing)

I have the feeling that indeed the clean handling of "state" vs "side-effects" (and what it implies for caching / retries / etc) is probably the real value here, but I fail to perceive it clearly (mostly because I probably don't (or not yet) have those issues in my build pipelines)

If you were to give a few examples / ELI5 of this, it would probably help convert more people (eg: I would definitely adopt a "clean by default" way of doing things if I knew it would help me down the road when some new complex-to-handle use-cases will inevitably pop up)