Arbor: Tree Search as a Cognition Layer for Autonomous Agents

In three linesArbor is a multi-agent framework introducing tree search as a cognition layer for autonomous agents. Validated on full-stack LLM inference optimization, it pairs an Orchestrator agent with a Critic agent in a checks-and-balances architecture. Arbor achieves 193% throughput-latency Pareto improvement over vendor-optimized baselines, versus 33% for a single agent that crashes within hours.

Summary generated by Claude — human-verified