The Debug-First AI Workflow: Why I Make My Assistant Break Things on Purpose
The author explains how they use AI assistants to break code first, rather than write it, to improve their coding workflow and reduce bugs.
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Why it matters
This approach demonstrates how AI can be used more effectively in the software development process by focusing on problem discovery rather than just code generation.
Key Points
- 1The default AI coding workflow leads to
- 2 where the code looks correct but has logic errors
- 3The debug-first approach involves: 1) Writing a spec, 2) Asking the AI to list failure scenarios, 3) Turning those into tests, 4) Writing the implementation, 5) Verifying against the tests
- 4This approach is better because it focuses the review on the tests rather than the code, and AI is better at finding problems than solving them
Details
The author argues that the typical AI coding workflow of describing what you want, having the AI write the code, and then reviewing it is flawed. This leads to
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