The gap between a demo that works on your machine and a thing that survives real users is where most writing about AI stops being useful. This is a room of people on the far side of that gap, comparing notes about it.
Post the agent, the prompt chain or the retrieval setup that is misbehaving and get an answer with code in it. The useful review is the one from somebody who has already hit that exact failure.
Hackathons and build weekends where the deliverable is something that runs, not a deck about something that would. Teams form in the rooms beforehand.
Members publish the agents and templates they run in real work. Forking one and adapting it is faster than evaluating forty tools that all claim the same thing.
A learning path for people who already write code and need a model in production: evals, retrieval, guardrails, and the failure modes that only show up under load.
See the learning pathsBoth, in separate rooms. Collab Space is where people building with models talk to each other — reviews, agents, retrieval, evals. Other rooms are for learning and for people using AI tools rather than writing model code, so neither conversation drowns the other.
No. Most of what is being discussed is the engineering around models rather than training them — retrieval, evaluation, orchestration, cost and latency. If you can ship software, you can contribute on day one.
Working software, in a weekend, by small teams that formed in the rooms beforehand — agents, retrieval tools and internal automations mostly. The constraint is that it has to run at the end, not that it has to be original.
No application to be approved and no card to enter. Pick a name and a password, choose the rooms that fit, and say what you are building.