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Local LLM agent falsely reports bug fix success due to flawed Git application

A developer running an autonomous coding agent locally encountered a significant bug where the system falsely reported success on fixing a GitHub bounty. The agent, utilizing the Qwen3 27B model via llama.cpp, produced an empty diff that `git apply` rejected as corrupt. However, the pipeline incorrectly registered a passing test suite on the original, unmodified code as a success. This led to the creation of a system that manufactured "green checkmarks" from non-existent code changes. The developer implemented fixes by adding checks for actual file modifications after patch application and by setting a line limit for generated patches to prevent excessive rewrites. AI

IMPACT Highlights critical engineering challenges in building reliable autonomous coding agents, particularly concerning verification and patch application.

RANK_REASON The item describes a specific bug and its fix in a custom-built autonomous coding agent, not a release from a frontier lab or a major industry event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Local LLM agent falsely reports bug fix success due to flawed Git application

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The item describes a specific bug and its fix in a custom-built autonomous coding agent, not a release from a frontier lab or a major industry event.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · prodbymarcu ·

    My local LLM fixed a bug overnight. The "success" was the bug.

    <p>I run a small autonomous coding agent on a secondhand RTX 3090 in my apartment. Last week I pointed it at paid GitHub bounties and let it run unsupervised, thinking I'd wake up to pull requests. I did wake up to pull requests. One of them was a lie, and it taught me more about…