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What to do when an AI project fails: a 20-minute review

Write a failure review that produces one smaller, testable next attempt.

About 20 minutesBeginnerRead free · No sign-up

Before you start

A disappointing AI result and the prompt that produced it. No failure handy? Ask any chat or image tool for “a poster for our bake sale” with no other details, and review that.

Why this lesson exists

The archived posts behind “Three Missing Teeth and the Difference Between a Loss and a Curriculum” treat difficult attempts as feedback. This exercise keeps that idea concrete and avoids turning a technical failure into a judgment about yourself.

The idea this guide practices: AI does the work faster. Judging it is still your job · How to debug with AI: give it evidence, not guesses.

Do the exercise

  1. Name the intended result

    Write what you expected to happen and the evidence that it did not. Keep observation separate from your explanation of the cause.

  2. Classify the gap

    Ask whether the problem lies in the brief, input, tool capability, implementation or evaluation. More than one cause may be possible; list uncertainty.

  3. Learn one missing fundamental

    A fundamental is a basic principle of the craft. Name the smallest one that would have prevented the problem, in plain words: text you can read from across a room, information that survives closing the page, a source you can trust, or the facts the tool needed. Ask for one short exercise on just that principle.

  4. Repeat a smaller test

    Change one thing and rerun. Keep the failed version and the result. Decide what evidence would justify moving back to the larger project.

A prompt to adapt

Replace the bracketed parts with your own details.

Help me review this failed attempt without generic encouragement. Intended result: [goal]. Observed result: [evidence]. Original instructions: [prompt]. Separate facts from hypotheses, identify one missing fundamental, and propose a small next experiment with a pass/fail check.

More prompts to adapt ↗

What this looks like

A bake-sale poster with no date, place or price has a brief problem: add those three facts, change nothing else and rerun. If the facts are there but nobody can read them from across the room, the missing fundamental is text size and contrast, and a newer image model will not fix it. A game character that moves faster on a faster computer needs a lesson on frame timing (often called delta time) before new artwork.

Check your result

Use evidence from your output. A confident explanation from the AI is not enough.

If it isn’t working

If the review becomes a long roadmap, reduce it to one uncertainty. Keep the practice project low stakes so experimentation stays reversible.

Where this came from

Adapted from the archived LinkedIn theme “Three Missing Teeth and the Difference Between a Loss and a Curriculum.” See the post coverage and editorial method. One of the original LinkedIn posts ↗

Prepared September 2026. Tools and interfaces change; use current official setup instructions. Session lengths are estimates.

THE IDEA BEHIND THIS GUIDE

Read the story, then keep practicing

KEEP GOING

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