# Better Tools Made Copilot Code Review Worse - Here's How We Fixed It Optimizing workflows led to 20% performance improvement - **Source:** [The GitHub Blog](https://brifing.si/source/9783c41a-41dd-45e0-8c71-c0930937342d) - **Published:** 2026-07-10 - **Topic:** [Data & AI](https://brifing.si/c/data-ai) - **Original article:** - **On Brifing:** https://brifing.si/s/b70b0e28-0843-4b4a-ac6f-ac2e04c91d7d ## Better Tools, Unexpected Results GitHub team integrated CLI tools to enhance Copilot's code review performance. However, this change increased review costs while reducing detected issues. Expected improvement turned into performance degradation. ## Problem Was in Approach, Not Tools Analysis revealed the issue wasn't the new tools themselves, but how they were being used. The workflow and instructions followed a general-purpose approach unsuitable for code reviews. ## Modeling Developer Behavior In real code reviews, developers start from the diff and ask targeted questions. The team designed a new workflow reflecting this natural behavior pattern. ## Focused Approach Over Broad Searches While previous methods performed wide code scans, the new approach focused only on relevant code sections. This eliminated unnecessary context burden. ## Tool Usage Efficiency New instructions enabled Copilot to use tools like grep and glob more efficiently. Each tool call became more targeted and purposeful. ## Context Window Optimization The old method carried excessive code context, increasing token costs. The new system maintains only necessary minimum context, reducing expenses. ## Results: 20% Cost Reduction The approach change reduced average review costs by 20% while maintaining the same quality level. Performance improvement exceeded expectations. ## Multi-Product Integration The new workflow was made compatible with other products like Copilot CLI and cloud agent, spreading improvements across a wide usage spectrum. ## Right Instructions for AI This experience showed that AI tool performance depends not just on technical capabilities but also on how they're directed. Proper instructions can fundamentally change outcomes. ## Continuous Improvement Culture This case reflects GitHub's culture of constant testing and optimization. Even performance regressions can become significant improvement opportunities when properly analyzed. ## Sources covering this story - https://github.blog/ai-and-ml/github-copilot/better-tools-made-copilot-code-review-worse-heres-how-we-actually-improved-it/ — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._