Hey folks 👋 We just open-sourced Future AGI - infrastructure for AI agents that improve themselves autonomously. The shift: Most teams stop at observability and evals. We built the full loop: agents that get better from their own production data, automatically, continuously. What we built: • Adversarial simulation (agents stress-test themselves before hitting prod) • Real-time self-correction (learned classifiers block bad outputs mid-conversation, sub-50ms) • Autonomous improvement pipeline (every failure becomes training signal automatically) • Full transparency (inspect exactly how your agent is learning and evolving) Ran this in production for months. Today: fully open source. Why open source? Can't ask people to trust a closed system that autonomously improves their AI. You need to see the learning mechanisms. Also - self-improving AI is foundational infrastructure. Every prod team will need it. Better built once, in the open. https://github.com/future-agi/future-agi Self-hostable. Full stack. For teams ready to build agents that actually learn. Drop questions below - happy to go deep on any part 🧵