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ReCode proposes unifying planning and action in LLM agents

Published on December 13, 2025, the article presents ReCode, a paradigm using recursive code generation to let agents switch between strategic planning and detailed actions.

Published on December 13, 2025, the article presents ReCode, a paradigm for language-model agents that uses recursive code generation and lets them adjust the granularity of decisions. The proposal is to switch between strategic planning and detailed actions rather than rigidly separating high-level planning from low-level execution. The article argues that this separation limits agents; the supplied material does not report quantitative results.

To consult and verify the proposal, look up the article by title and publication date. Check how the method is defined and what evidence is presented, distinguishing the article’s argument from experimental results. If you use AI to study or apply the material, avoid entering confidential organizational data and follow your internal data-protection policy.

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