Show HN: Relay – The open-source Claude Cowork for OpenClaw
github.comGenuine question - your README is full of em-dashes, emojis, feature squares and ASCII diagrams - none of which are present in your pre-AI era projects.
Why do you expect a potential userbase to care to read something you didn't even care to write?
Seems a bit disrespectful to me.
Provided he reviewed it and checked the readme is telling the users what it needs to tell them - what's the issue? I've found documentation to be one of the better tasks AI can perform and see no reason why not to use it provided a human is in the loop.
Just looking at the diagrams in the README, the broken ASCII suggests to me it either wasn't looked at or the author didn't care.
I agree, but its tricky as many people seem to not read it and I have seen AI documentation that is so verbose and dense that its almost as useless as not having it. Its a fine line but so long as the AI documentation is reviewed and reasonable then I see no issue.
1. In reality most people simply do not do this, and frankly it's exhausting to be expected to always assume goodwill in a setting that is full of pure vanity.
2. There's a difference between technical documentation, which AI can be quite decent at, and product marketing. A README is usually about 20/80, maybe 50/50 for large FOSS projects. You can have the AI write the sections on how to install the thing for all I care, but as soon as AI is telling me why I should use it, you've lost me. Signals a complete lack of interest in your own product.
It's a strong signal of low quality.
The question is: "Should I spend my time engaging with this project?"
The AI-forward presentation says: "Absolutely not."
Potential userbase... you mean people who use OpenClaw? Not sure if they care.
Probably not the typical OpenClaw user. I’ve had that thought myself.
But I can imagine that medium-sized companies will want to use AI as a backend in the future, without wanting to be dependent on Antropic.
After all, there are already quite a few companies using OpenClaw.
A self-hosted OpenClaw instance (or other solutions in the future) with Relay would be a good alternative to Claude Cowork.
I do think a properly hand-written readme it better, but if not, here's a blatant plug - https://github.com/joelio/plain-english
So this is a wrapper on top of a wrapper on top of Claude Code (which is a wrapper) on top of the API.
Considering that Open Claw requires 2GB of RAM and Claude Code is by no means a "lightweight" CLI either, I would argue that the compounding overhead here is hard to justify when you could just hit the API directly.
Each layer adds its own memory footprint, failure modes, and debugging surface area and at some point, the convenience of abstraction is outweighed by the cost of running what is essentially a Matryoshka doll of Node processes just to send a prompt and get a completion back.
Just a thought.
Actually, Relay doesn't sit on top of Claude Code.
Relay connects to OpenClaw. OpenClaw connects to whatever model provider you choose (Claude, GPT-4, Llama, custom endpoint, whatever).
So the stack is: Your local files → Relay → OpenClaw gateway → Your chosen model.
That said, your point about abstraction overhead still stands. Each layer adds cost. We think the tradeoff is worth it for teams that need always-on agents + local file access + approval workflows. But if you just want to hit an API directly, you're right — this isn't for you.
These seem misleading. Cowork's VM is not on Anthropic servers?
> Local file access >> Relay: Truly local >> Cowork: Sandboxed VM on Anthropic's servers
> The bottom line: Claude Cowork is excellent for personal productivity on Anthropic's cloud. Relay is for teams and companies that need data sovereignty, compliance-ready audit trails, and model freedom — all on their own infrastructure.
You're right, that part is a bit confusing. I'll have to fix it.
I'm not entirely sure what Cowork means by “sandboxed VM” right now. Relay simply has access to the folder you've defined for the project.
better, more, screenshots or video walkthrough would help why something like this is interesting/needed.
The flood of new tools is truly overwhelming there isn't enough time to setup all of them to validate the marketing claims against actual functionality and benefit
Right. I'm on it.
Question to Hacker News admins: Why does AI slop rank so high on the front page nowadays?
Not admin but I assume even slop is interesting because this is a totally new field which we are discovering. That includes discovering what is bad.
If it is in a category dedicated to such content, I'd be fine with it. But ranked #4 on front page?
What makes you think this is AI slop?
The first impression I get looking at the README and the website doesn't suggest much effort went into it.
Who is the troll here? I asked a genuine question and tried to explain why I think this way, and now you're all toxic. Can't you take feedback? If not, then why did you post this project here?