Leverage an AI coding assistant like Claude Code to implement a Test-Driven Development (TDD) process. This workflow allows you to reproduce, fix, and verify bug fixes with incredible speed and accuracy.
Start with a specific bug, typically documented in a GitHub issue. This issue provides the necessary context for the AI.
Open your AI coding assistant and provide a detailed prompt. Reference the GitHub issue and explicitly ask the AI to follow a TDD process.
There's a customer issue that is outlined in this GitHub issue... Can you please read this issue and come up with a fix for the problem that's outlined here? I'd love for you to first write an eval that fails to show that you can reproduce this issue, then come up with a solution, and then prove that the solution works by showing that the eval now passes.The AI will first read the issue and write a failing evaluation (a test case) that successfully reproduces the bug, confirming its understanding of the problem.
Next, the AI will propose a solution (often a change to code or another prompt) and then automatically run the evaluation again to prove that the fix works by showing the test now passes.
This is a critical step. Carefully review the AI's proposed code change and test case. Use your expertise to ensure the fix is high-quality, correct, and doesn't introduce side effects.
Once you are satisfied with the AI's solution, instruct the AI to open a pull request for team review and merging.
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