Interview preparation splits into five phases where AI is genuinely useful: company and role research, behavioral story drafting, technical question practice, question generation for the interviewer, and negotiation preparation. The prompts below cover all five. The key to getting useful output is specificity — paste the actual job description, use your real accomplishments, and name the company. Generic prompts produce generic preparation.
Paste the actual job description into prompts that reference it — generic prompts produce generic preparation
Use your real accomplishments and numbers in the STAR builder; AI cannot invent specifics that don't exist
Run the mock interview prompt in a fresh session and commit to answering fully before reading feedback
For salary negotiation, research market rate on Levels.fyi, LinkedIn Salary, or Glassdoor before running the script prompt
Practice your final answers out loud — AI-generated scripts that sound great to read often feel unnatural when spoken
The STAR prompt works best when you give rough notes, not polished prose — let the AI do the structuring
Ask the AI to 'steelman the interviewer' — what follow-up questions would a skeptic ask about your answer?
Generate a list of your top 5 achievements before starting, then map them to the JD competencies — this makes all behavioral prep faster
Interviewers remember the most specific answers, not the most polished; optimize for concrete details over smooth delivery
For senior roles, prepare a 30-60-90 day plan even if not asked — it signals genuine commitment and thinking
Negotiate every offer, even good ones. The 90-second negotiation script prompt is worth running before any final call
Start the company research prompt as soon as you get the interview confirmation — ideally 48 to 72 hours out. Behavioral story drafting takes two to three sessions, so begin that 3 to 5 days before. For technical roles, start technical practice a full week ahead. The night before, review your STAR stories and the smart questions prompt. Same-day cramming with AI is better than nothing, but the best preparation happens in layers over several days.
AI can draft STAR answer structures from your resume, but the output will be generic and obviously AI-written without your specific inputs. The STAR builder prompt works well when you give it rough notes about what actually happened — even a disorganized paragraph works better than a resume bullet. The AI structures; you supply the raw truth. Answers that sound rehearsed or AI-generated are a growing red flag for experienced interviewers.
Vague impact statements. Most candidates describe what they did without quantifying what changed because of what they did. The STAR prompt specifically asks for outcome with numbers, which forces you to supply them if you have them — or realize you need to find them. Running the mock interview with follow-up questions is the fastest way to identify where your answers go vague under pressure.
No — not because it's unethical, but because it does not work. AI-generated prose has a rhythm and phrasing that interviewers increasingly recognize. More importantly, if an interviewer pushes back on your answer, you cannot credibly defend something you did not write. Use AI to structure and improve your own answers, then rewrite in your own voice and practice until the content is genuinely internalized.
Yes, with limitations. The technical practice prompt works well for system design, product case questions, data analysis, and behavioral aspects of technical roles. For coding challenges, AI is a reasonable practice partner but you should also use dedicated platforms like LeetCode, HackerRank, or Interviewing.io for timed, realistic conditions. Claude and ChatGPT are good at explaining concepts and reviewing your approach; they are less good at simulating the pressure of a real timed coding round.
The salary negotiation prompt is most effective when you supply real market data first. Research the role on Levels.fyi for tech, LinkedIn Salary for other industries, or Glassdoor for smaller companies. Put specific numbers into the prompt — your target, your current comp, the offer you received. The AI produces a professional counter-offer email anchored to market data rather than personal need, which is the approach most likely to succeed without damaging the offer.