Verification Loops for AI Coding: Make the Model Test Before You Review

Verification Loops for AI Coding: Make the Model Test Before You Review One of the most expensive mistakes in AI-assisted coding is reviewing output too early. The model writes a patch. You skim it. It looks plausible. Then one of three things happens: the patch does not actually solve the bug it breaks an adjacent behavior it quietly ignores the constraint you cared about most At that point, the model did not really save you time. It just moved the debugging work into code review. That is why I like verification loops. A verification loop means the model does not stop at “here is the answer.” It has to check its own work against explicit criteria before handing it to a human. The basic idea Instead of a one-step prompt: Fix this bug. Use a three-step workflow: identify the likely cause propose the smallest reasonable fix verify the fix against tests, constraints, and edge cases The important part is that step 3 is not optional. Why this works LLMs are good at producing plausible code.