2025–2026
Arbiter
Watching two AI agents argue about a decision
Automated systems make good decisions and bad ones, and from the outside they look identical. A number comes out, and someone has to sign off. Arbiter makes the argument visible instead. A scoring model picks the best delivery route on cost and time; a language model reviews that pick, argues with it in real time, and can override it. The operator watches both, and every decision is saved with the reasoning that produced it, replayable later.
The reviewer catches things the scoring model can't see, like a driver's free-text incident report, a zone advisory, or the fact that optimizing purely for cost quietly deprioritizes the same underserved neighborhoods every time.
Demonstrated on last-mile logistics, but the review layer doesn't care about the domain: swap the scoring function and the same audit applies to loan triage or ticket escalation.
Started as ALRO, a three-person team project at SJSU. I've kept building on it since. The audit trail, the fairness constraint, and the free-text signals came after.
- Python
- FastAPI
- React
- Docker
- SQLite
- SSE
- LangChain
- PyTorch
- Pinecone
- LLM APIs