Ships with an Agent Skill for AI coding agents.
When installed, agents use ๐๐๐๐๐ ๐๐๐๐๐๐๐ instead of ad hoc tee/script workarounds.
Benchmark (Claude Sonnet 4.6):
โ With skill: 100% pass rate
ร Without: 28%
๐๐๐ ๐๐๐๐๐๐๐ -๐ @๐๐๐๐๐๐๐ฃ๐/๐๐๐๐๐
We've open-sourced Proof: A visual proof of work for automated code changes.
Capture terminal output and browser interactions as shareable evidence. Animated HTML replays, videos, and structured reports.
Open source. Apache 2.0.
https://t.co/S77OQlAiCP
Why we built this:
Every PR should answer "does it work?" with more than a checkbox.
Proof gives you a 10-second replay instead of a 200-line diff. Attach it to PRs, send it to stakeholders, and archive it for compliance.
VibeProxy: A native macOS menu bar application for managing CLIProxyAPI - letting you run Droids by FactoryAI using your Claude Code and ChatGPT accounts
https://t.co/PLHtNUxSwE
I've been working on a book on building production-grade agentic AI, and I can finally see the finish line on the horizon (draft link in first comment)
Before I wrap it up: What would make this genuinely be useful for you to learn when it comes to AI agents?
Taking a moment to share your thoughts would mean a great deal ๐
Open source AI tools are finally catching up to big tech. For founders, that means better building blocks-no more reinventing the wheel if you want custom, cost-effective smart systems.
Keep your stack nimble, but always audit the risks behind every shortcut.
Claude Code + GitHub Issues = faster, spec-driven shipping.
We built a workflow that turns PRDs into Issues, tracks dependencies, and enables parallel execution.
Claude Code + GitHub Issues = faster, spec-driven shipping.
We built a workflow that turns PRDs into Issues, tracks dependencies, and enables parallel execution.
Open-source LLMs are catching up to closed models - and they're way cheaper to run. For founders, that means high-performing AI you can own and control, not rent from a giant. Stop waiting for perfect AI. Start automating with what you can improve today.
Most performance pain in small tech teams comes not from lack of talent, but from quietly compounding complexity โ๏ธ. Postgres runs fast-until ad hoc queries and untracked changes gum up the works. Fast founders measure, refactor, then automate before scaling up.