Story · arXiv
PatchBoard: Schema-Grounded State Mutation for Reliable and Auditable LLM Multi-Agent Collaboration (arXiv)
paper · Story page
Agents propose JSON Patch mutations against shared structured state instead of talking to each other, and a deterministic kernel validates each one before it commits. On 630 matched ALFWorld episodes: 84.6% success against 30.8% for LangGraph and 61.6% for Flock.
In plain words
- PatchBoard lets artificial intelligence assistants coordinate their work through changes to a shared record.
- A planning assistant sets the structure of the shared record and the rules for doing the task.
- A separate program checks every proposed change against those rules and each assistant's permissions before saving it.
- In the reported tests, assistants using PatchBoard completed 84.6% of tasks successfully, more than either comparison system.
Appeared in
- Forged control tokens blank an agent's reasoning while the tool call still fires
Sep 25, 2026 · in the sections
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