SHIFT Method for Per-Query Multi-Agent Harness Construction
October 1, 2026
SHIFT utilizes a local LLM architect and Monte Carlo tree search to build custom agent harnesses for specific queries. It replaces costly real-time execution searches with a policy that predicts utility by balancing accuracy against execution cost.
HOW THIS AFFECTS YOU
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builderYou can deploy more efficient multi-agent systems by tailoring toolsets and instructions to specific tasks at inference time.
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researcherThis approach moves agent design from manual or brute-force execution to learned policy optimization.