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Aurelius · Work & Leadership
Knowledge + Guidance

How do I know when to trust an AI-suggested fix?

You pushed a fix the AI gave you. It broke something. Now you hesitate before every suggestion, unsure which ones are safe and which will bite you. This is not a failure of judgment. You simply have no habit yet for checking its work before it goes live. You've been treating the output like advice from a senior engineer who already tested it. It is not that. It is a guess — sometimes a sharp one — delivered with the same flat confidence whether it's right or wrong. The fix is not to trust the AI less, or more. It is to build one short, repeatable check you run every time, before anything ships. That check is within your power. The AI's reliability never was.

◆ How this problem reads on the two dials
GuidanceKnowledge
More coaching
Some to learn
1:1 with AureliusWith others (a Pod)
Mostly you & the coach
A little with peers
The core need is a repeatable verification habit, not more explanation — so coaching toward that habit outweighs teaching.
How the two dials adapt to you →
What’s really going on

You don't earn trust by feeling confident. You earn it by testing the fix the way you'd test code from a stranger — before it ships, not after. The AI is not your reviewer. You are its reviewer. That is the job now, whether you accepted it or not.

🔒 What you’ll build togetherUnlock by starting
A moveBefore running any AI-suggested fix, write one sentence on what breaks if it's wrong.
A moveTest the fix on the smallest case you can isolate, not the whole feature at once.
A moveRead the fix line by line as if a stranger wrote it and you must sign your name under it.
A moveKeep a short, running list of AI mistakes you've caught. Review it every week.
A moveNever merge a fix you have not personally run, no matter how reasonable it reads.

What changes unlock by starting

  • A quick, repeatable check you run before any AI suggestion ships.
  • Fewer surprises in production from fixes nobody verified.
  • A clearer sense of which fixes need more scrutiny and which don't.
  • Confidence built on verification, not on hope.

Related problems

One object, two jobs: a public answer to a real problem, and — the moment you start the chat — Aurelius’s live plan for your version of it.