HackerTrans
トップ新着トレンドコメント過去質問紹介求人

caravel

no profile record

投稿

Show HN: Agor → Figma for AI Coding (Open Source)

agor.live
10 ポイント·投稿者 caravel·8 か月前·3 コメント

Promptimize for Test-Driven Prompt Engineering

preset.io
2 ポイント·投稿者 caravel·3 年前·1 コメント

コメント

caravel
·8 か月前·議論
Hey, creator here. I built this over the past month to try and stay sane while coordinating Claude Code, Codex, and Gemini across projects.

Quick feature rundown:

- Real-time collaboration with spatial comments/reaction + live cursor sync - Full MCP support + agents are self-aware of the workspace via internal MCP server - Built-in scheduler for agent tasks - Session forking/subsession spawning (sessions shown as trees on the canvas) - Shared dev environment management - Mobile site for prompting on-the-go

Built the whole thing using Agor itself with multiple agents collaborating. Watching agents build the tool they're working in is pretty wild. Happy to answer questions
caravel
·8 か月前·議論
So I built “Figma for AI coding” to stay sane while coordinating agents across projects, git worktrees, AI sessions and my team. Called it Agor the, "AGent ORchestrator". Built it in a month using Agor to build Agor, plus an army of agents. Open sourcing it today. It's a 2D spatial canvas where you can coordinate an infinity of agents (managed git worktrees, shared dev environments, comments+reactions, m-site, + a proper scheduler). Solid docs at https://agor.live . Pretty stoked about this one.
caravel
·3 年前·議論
A new open source project to support testing prompts at scale by the creator of Airflow & Superset. The toolkit brings many of the ideas from test-driven development to the prompt engineering world, so that people integrating AI in their product case assert how it's performing as they iterate on prompts and models. The author talks about his use case where he used this toolkit to test text-to-SQL against a large corpus (thousands of prompts cases) against different models and through iteration cycles.
caravel
·4 年前·議論
This is much more straightforward than your JVM-based, huge infra solutions like Flink. For when you need something that is familiar [python] and just works.