GraphBit- Rust + Python framework for production-grade AI agents
We built GraphBit after running into the same issue with every agent framework we tried: they looked good in demos, but collapsed in production.
Crashes under load, context loss mid-task, and no real concurrency support made them unreliable for real-world use.
GraphBit is designed differently:
Rust execution core → lock-free scheduling, atomic counters, resilient concurrency
Python API → keeps it accessible for AI engineers
Production primitives → state, retries, timeouts, observability baked in
Multi-LLM orchestration → run multiple providers in a single workflow
Patent-pending architecture → optimized execution model for scale
Repo: https://github.com/InfinitiBit/graphbit
Docs: https://graphbit.ai
We’d love feedback from the IH community. In particular, what do you see as the hardest scaling challenges for agent frameworks?
This is exactly what the AI agent space needs! The Rust core + Python API approach is brilliant - you get the performance and reliability of Rust while keeping the accessibility that AI engineers are comfortable with. The production-first approach really resonates - so many agent frameworks feel like demos that break under real-world conditions. The lock-free scheduling and atomic counters show serious attention to concurrency issues that plague most agent frameworks. Looking forward to seeing how the multi-LLM orchestration works in practice. The GitHub repo looks solid too - great documentation and clear examples!
Thank you! You nailed exactly what we set out to solve, moving from fragile demos to true production-grade systems. The Rust + Python combo lets us balance performance with accessibility, while lock-free scheduling + atomic counters tackle concurrency head-on. Excited to hear your thoughts once you test multi-LLM orchestration in practice!
It's so obvious that a lot of the current Python codebase will transition to this perfect Rust core + Python api combo.
How was the development of the tool? Are tools like maturin mature enough to make it easy?
Great point, we see the same shift happening. Development was smooth overall, and yes, tools like maturin have matured a lot. They made bridging Rust and Python far easier than it used to be, especially for packaging and distribution. Still, we had to build custom layers for orchestration and concurrency, that’s where most of the heavy lifting went.