Be Skeptical Regardless of Who (or What) You Look Up To

QA requires skepticism. We test because confident claims can still be wrong.

The more highly you regard someone or something, the less likely you are to question it. Senior engineers earn less scrutiny after shipping good code for years. Established frameworks earn it after thousands of teams stress test them in production. A track record builds trust.

Then AI showed up and skipped the line.

Why AI gets a pass it hasn’t earned

AI didn’t earn trust the slow way. It just started acting like it already had it. It writes with total confidence. It rarely hedges unless you ask it to. It answers instantly, in full sentences, sounding exactly as sure of itself when it’s wrong as when it’s right.

AI makes mistakes while writing with the confidence we associate with a proven track record. That confidence discourages scrutiny before the tool has earned any trust.

What verifying actually looks like

I’ve seen this play out directly. A dev on my team ran their code through AI and asked it to verify its own work. It came back clean: 15 out of 15 tests pass. Confident. Done. Except nobody had actually run those tests against the real system. The AI was reasoning about what should happen, not confirming what did happen. That gap, between sounds right and is right, is exactly where bugs live.

Treat AI output like any other claim. Check it. Run the test. Look at the result instead of the confident sentence describing it. QA engineers already do this with tools, assumptions, and every “trust me, it works.” AI demands the same scrutiny because it can sound certain without evidence.

Keep checking the result

AI is going to keep getting smarter. That part isn’t really in question. What’s in question is whether the people using it keep verifying at the same rate the tool gets more convincing.

Use AI, then verify its work. A confident answer doesn’t change the result in front of you.