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Effective AI code suggestions: less is more
Learn how Qodo Merge boosted AI code suggestion acceptance by 50% by cutting distractions and focusing on critical issues.
In our quest to generate effective code suggestions with LLMs at Qodo Merge, an AI-powered tool for automated pull request analysis and feedback, we discovered that prioritization isn’t enough. (1) it eliminated the complexity of evaluating and prioritizing different types of suggestions, and (2) it prevented the model from being overwhelmed by the sheer volume of potential style improvements that could otherwise dilute its attention from critical issues. The success of this dual approach validated our strategy: developers trust and implement our critical bug suggestions because they know each one represents with high probability a genuine problem that needs fixing, while still having the flexibility to maintain their team’s coding standards through configurable best practices.
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