A step-by-step way to work
Bring a real experience
Give AI a genuine situation from your career, however roughly told.
Shape it into STAR
Ask it to structure the raw story into Situation, Task, Action, Result.
Catch the classic failures
Have it flag 'we' instead of 'I', too much Situation, and a missing or vague Result.
Quantify the Result
Ask it to prompt you for the numbers that would make the outcome concrete.
Rehearse for follow-ups
Have it ask the probing questions an interviewer would, so your real details are ready.
Real prompts, and what good output looks like
Critique this STAR answer: 'We had a launch that was slipping. We realised the scope was too big. We cut some features and we shipped on time.'
Problem 1 — all 'we', no 'I': an interviewer can't tell what YOU did. What was your specific action? Did you make the scope call, build the case, persuade someone?
Problem 2 — no real Result: 'shipped on time' is thin. On time by how much? What was the impact of shipping vs slipping? Any metric?
Problem 3 — Situation is vague: what was at stake if it slipped?
Reframe each as 'I' and add one concrete number to the Result — then it lands.
A prompt you can reuse
Fill in the highlighted parts and paste it into your AI tool of choice. Edit the output — it's a starting point, not a finished answer.
Help me build a STAR story from a real experience. Don't invent details — prompt me for the true ones. My rough story: [tell the experience loosely] The competency it should demonstrate: [e.g. leadership, dealing with ambiguity, conflict] Please: 1. Structure it as Situation – Task – Action – Result. 2. Flag every place I said 'we' where the interviewer needs 'I', and ask me what I specifically did. 3. Tell me where the Result is missing or vague, and ask me for the concrete number/outcome. 4. Then ask the 2–3 follow-up questions a sharp interviewer would, so I can prepare real answers.
What AI gets wrong here
Fabricated or embellished stories
An AI-invented or inflated story falls apart when the interviewer asks for specifics.
Hiding behind 'we'
Team framing obscures your individual contribution — exactly what's being assessed.
Weak, unquantified results
'It went well' isn't a result.
AI is a sharp editor for STAR — it reliably catches the 'we'-not-'I' problem and the missing result. But the story has to be your real experience, and the strength of a STAR answer is in true, specific detail AI can't supply and shouldn't fake. Prepare with it; don't outsource your story to it.