Model Releases
This is a great paper from AWS AI Labs. They show that multi-agent coding teams raised their test pass rate by 28.2% and cut wall time by 16…
This is a great paper from AWS AI Labs. They show that multi-agent coding teams raised their test pass rate by 28.2% and cut wall time by 16.5% without changing the model. The authors achieve this by
This is a great paper from AWS AI Labs. They show that multi-agent coding teams raised their test pass rate by 28.2% and cut wall time by 16.5% without changing the model. The authors achieve this by changing how the agents communicate. In free-form agent teams, shared findings are just context. Agents can ignore them, and the harness never checks whether an implementation still matches the interface the team agreed on. They introduce AECP, a protocol that requires agents to communicate only through structured artifacts, and the harness acts on them. It supplies recorded findings when an agent opens relevant code, screens implementations against interface commitments, and makes affected agents revisit an agreement when it changes. Results hold across Doc2Repo, NL2Repo, and CodeProjectEval with models including Opus-4.8 and DeepSeek-V4-Flash. There is a security benefit too. Malicious instructions relayed between agents reach another agent 0% of the time instead of 95%, and get acted on 0% of the time instead of 40%. Paper: https://academy.dair.ai/papers/aecp-artifact-exclusive-communication-protocol-for-multi-agent-code-generation-2610.06481
Related
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Source: DAIR.AI (X) | 2026-10-07