𝗧𝗵𝗲 𝟰-𝗦𝘁𝗲𝗽 𝗥𝗶𝘁𝘂𝗮𝗹 𝗧𝗼 𝗧𝗿𝘂𝘀𝘁 𝗔𝗜 𝗖𝗼𝗱𝗲
I built my whole product using an AI coding agent.
The biggest risk is not bugs. The biggest risk is a test suite that passes for the wrong reason. A green checkmark can lie to you.
I use these four steps to stay in control.
Freeze your success criteria Write your pass or fail rules in git before you see any AI results. If you define success after the AI finishes, you will pick a definition that favors the AI output. I once lost a project because a test passed by measuring the wrong thing. Write the bar down first.
Run baseline tests Commit your criteria and run tests on your current code. You need a known good starting point. You must know if a test passed today or if it was already green before the AI touched it.
Demand a plan before code Ask the AI for a plan. Do not ask for code. Most people ruin their codebase because they approve 400 lines of code without reading them. You can review a plan in two minutes. This stops the AI from deleting difficult test cases to make the numbers look good.
Manual approval only Review the plan. Push back if it looks wrong. Only then approve the work. The AI never writes code I have not already read in a plan. Auto-approval leads to systems that are confidently wrong.
Optional learning community: https://t.me/GyaanSetuAi