Developer Builds Autonomous AI Coding Agent That Refines Code Using Test Feedback

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A developer has built an autonomous coding agent designed to tackle challenging programming tasks in competitive settings. Instead of producing code in a single LLM pass, the system follows a full workflow of repository analysis, planning, implementation, execution, testing, and refinement. Its key feature is an iterative feedback loop in which failed tests are diagnosed, the code is updated, and the relevant tests are rerun before submission. The author plans to compare performance with and without this loop using success rate, tests passed, completion time, and compute cost, though the article presents these metrics only as placeholders. Further optimizations include model selection, prompt design, tool usage, and failure recovery.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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