Job Interview Prep
Build a bank of STAR stories from your real experience, mapped to the job's competencies, then drill them in a mock interview with feedback.
Prepare me for a job interview.
The job description:
"""
[PASTE THE FULL JD]
"""
My background (resume or a summary of my real experience):
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[PASTE RESUME OR WRITE THE HIGHLIGHTS: real projects, real numbers, real messes]
"""
Interview stage + format: [e.g. "first round with hiring manager" / "panel" / "final with VP"]
Work in three phases:
**Phase 1: Question forecast.** From the JD, extract the 5-7 competencies they'll probe (leadership, conflict, ambiguity, deadline pressure, failure, technical judgment...). For each, write the 2 most likely behavioral questions in the interviewer's voice.
**Phase 2: STAR story bank.** From MY background only, build 6-8 reusable stories. For each:
- Situation + Task in 2 sentences maximum: most candidates die here, spending 60% of the answer on setup.
- Action as the bulk (~50% of the answer): what I specifically did, decisions I made, in "I" not "we".
- Result with a number wherever my material has one; where it doesn't, mark [QUANTIFY: what metric would you estimate?] and ask me.
- A one-line "Reflection" tag: what I learned or changed after.
- Which forecast questions this story can answer (good stories cover 2-3).
If my background lacks a story for a key competency, say so and help me mine for one with 3 targeted questions about my experience. Do not invent anything.
**Phase 3: Mock interview.** Ask me the forecast questions ONE at a time. After each answer I type, give feedback on: length (60-120 seconds spoken is the target), setup-to-action ratio, whether the result landed with a number, and one sharper phrasing of my weakest sentence. Push with a follow-up probe ("what would you have done if X?") before moving on.
Also prep: my 90-second "tell me about yourself" (present → past → future, ending on why THIS role), and 3 questions for me to ask them that show judgment rather than Googleable curiosity.How to use
Interview prep is one of the highest-value personal AI use cases, and the story bank is the durable asset: 6-8 stories cover virtually any behavioral question, so drill the stories, not 200 questions. The phase-3 feedback loop is where improvement happens: answer out loud, transcribe or type what you said, and let it critique the real answer, not the answer you wish you'd given.
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