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This paper introduces generative compilation, a method to obtain compiler feedback on partial programs during AI code generation, using a 'sealor' transformation that enables standard compilers to diagnose incomplete code. Evaluated on Rust coding tasks, it reduces non-compiling outputs and improves functional correctness by catching errors early.
A senior Google engineer released a 19-page PDF on 'Loop Engineering' for LLM and agentic systems, outlining an iterative feedback loop where the LLM proposes code transformations, observes compiler feedback, learns from it, and repeats until improvements stop.