Docker Agent

Interesting seeing other people's approaches to orchestration.

I've been working on Pullboard and just open sourced it: https://github.com/pullboard-dev/pullboard

To me, orchestration is not really the core problem. The bigger challenge is handling agent coherency over long periods of time, (drift) so my solution is a living forum-like system where agents shout to one another, document work in items, and follow doctrine handed down by the developer and work against a known specification that's checkable. I have used this workflow in several large projects that MUST be correct, and it works for me. Currently cleaning it up for other users.

Last year (2025), I lost count of how many times I tried using an LLM to set up Docker. It was still the era of prompting, then copy-pasting the response and seeing if it worked... and it almost never did. It’s great to see this new Docker agent. For me, it would be even more appealing to see an agent and a model specialized in Docker working together, capable of proposing advanced configurations and getting them working on the first try.

I'm honestly getting lost between what primary usecase/workflow each of these is intended for: 1. https://kagent.dev/ 2. https://github.com/kubernetes-sigs/agent-sandbox 3. https://github.com/docker/docker-agent (this project) 4. https://docs.langchain.com/oss/python/deepagents/sandboxes#s... 5. https://www.cloudflare.com/products/sandboxes/

While I love new open source dev (especially in Go!), agent harnesses are turning into JS frameworks from yesteryear.

All the cool kids have one!

I tried really hard to make this work for me a couple of weeks ago but it was the brittlest harness out of any that I've used. I'd come back when it's more mature.

https://docker.github.io/docker-agent/configuration/sandbox/

If, like me, you couldn't find any security-related info on the linked page.

they hope they can annoy and email every person in the org asking for money , same way as they did it with docker.

looks like a weird abstractions. why do i need this if i have modal.com, e2b, cloudflare that use original docker + some toolings around + way to run + isolations on network level.

Docker Agent could be beneficial for research studies. For example, while writing a ML paper about agents I need to rerun experiments so that: - others can repeat my results - validate that variability from LLMs is not causing overconfidence in the results

But currently uv is good enough to create isolated, repeatable environments. And it isn't limited to Linux like standard Docker. So when I want to test small samples on my local PC's GPU (Windows or mac) before running on beefier hardware, I can do that easily.

>What it is, what it isn’t

Yep, open ai sol model wrote that.

What does this have to do with Docker?

Why can't we set the harness? Seems like the missing piece

Pretty vague

very weird. why does this have dockers name on it? might as well use an agent harness from kohl's or steak n' shake. odd..

gimmick

What's new or interesting here? Docker's AI story ought to be around sandboxing, yet the word appears nowhere. Oh, and it's YAML, which I despise.

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> Go

Nowadays there are only two justifiable public languages you should be using for anything a) C++ b) Rust

Rust itself is dubious due to abysmal compile times and the fact that the only guarantees it gives you are of security (aka a skill issue). Modern LLMs write C++ that is as safe if not safer than Rust. Any other language choice is objectively wrong.

* For those inquisitive enough the keyword "public" is doing all the heavy lifting here. Pretty much everyone should be developing and using an in-house DSL at this point.