Don't Outsource the Final Judgement

The mistake of letting Claude make the call rather than inform it — shipping its output because it seems reasonable, without the review and judgement that the decision actually needs. The model is there to draft, analyse, and pressure-test; the decision and the accountability stay with you.

As output gets more fluent and more often right, the temptation is to rubber-stamp it, and the review that catches the occasional confident error quietly erodes. But Claude has no stake in the outcome, no view of the context outside the prompt, and no accountability when it's wrong — all of which are yours. Keeping the final judgement isn't distrust; it's recognising that 'usually right' still means someone has to own the times it isn't, and that someone is you.

Anything consequential or externally-facing — code that ships, content you publish, advice someone acts on, decisions that are hard to reverse. The higher the stakes, the more the judgement has to stay human.

Genuinely trivial, reversible, low-stakes tasks where a wrong output costs seconds to fix. You don't need to agonise over a first-draft Slack reply.

Give me your recommendation on <decision>, plus the two or three things I should check or weigh before I commit — the places your view could be wrong, the context you don't have, and what would change your answer. I'll make the final call; help me make it well.

Claude recommends a vendor and, prompted, notes it's assuming your team has the ops capacity to run it — which you know they don't. You use its analysis, override its conclusion, and own a better decision than either of you would have made alone.

Use Claude to strengthen your judgement rather than replace it: have it argue against your leaning, surface what you're missing, and stress-test the choice — then decide. The goal is a better-informed human decision, not an automated one you didn't really make.

• Rubber-stamping fluent output because reviewing feels redundant — until the one wrong call.
• Treating a recommendation as a decision and skipping the context only you have.
• Blaming 'the AI' for an outcome you shipped; the accountability was always yours.