ChatGPTGeminiClaude
Discovery call question list
Build a sharp set of questions that surface budget, pain, and decision process.
Example output
Warm-up
- "Walk me through how your team handles [process] today." → listening for: their words for the pain.
- "What made you take this call?" → listening for: the trigger event.
Pain & cost
- "Where does that process break down most often?" → the symptom they feel.
- "What happens downstream when it breaks?" → the real cost.
- "How are you working around it now?" → urgency and budget for a fix.
...
Decision
- "Besides you, who'd weigh in on a change like this?" → hidden stakeholders.
TipThe "what is it costing you" questions are what let you sell on ROI later — capture their exact numbers and quote them back in your proposal.
ChatGPTGeminiClaude
Demo prep brief from prospect research
Get a tailored demo plan so you show the right features to the right buyer.
Example output
Demo flow (map each beat to their pain):
1. Start at the new-rep view → "here's day one for a new hire." (pain: 6-week ramp)
2. Show a doc update auto-syncing → "answers never go stale." (pain: weekly doc changes)
3. Manager dashboard → resolution rate by rep. (pain: no visibility)
Wow moment: ask them for a real question their reps get, type it live, show the sourced answer.
Mid-demo questions:
- "Is this the kind of question that trips up new reps?"
- "Who on your side would live in this dashboard?"
TipSkipping features is as important as showing them — a demo that covers everything lands nothing. The live "type their real question" moment beats any scripted example.
ChatGPTGeminiClaude
Create interview questions for a role
Generate role-specific behavioral questions that predict performance.
Example output
**Stakeholder communication**
Q: Tell me about a time you had to deliver bad news to a client or executive who didn't want to hear it. What did you do?
Strong answer signals: gave early warning (not surprise), separated facts from opinions, had a proposed path forward.
Follow-up: What did they say, and how did it end?
**Execution under ambiguity**
Q: Describe a project where the requirements changed significantly mid-way. How did you handle it?
Strong answer signals: re-scoped rather than absorbed scope, renegotiated the deadline, communicated tradeoffs explicitly.
Follow-up: What would you do differently?
**Technical judgment**
Q: Tell me about a technical decision you made that you later regretted. What did you learn?
Strong answer signals: owns the decision rather than blaming constraints, describes what they'd change, shows updated mental model.
Follow-up: Did you change how you make that type of decision now?
TipWrite "what a strong answer sounds like" before you run the interview — interviewers who don't know what they're listening for get captured by confident delivery instead of actual signal. The follow-up probe is where you separate prepared storytellers from people who actually did the thing.
ChatGPTGeminiClaude
Run a structured candidate debrief
Turn interviewer notes into a clear hire / no-hire recommendation.
Example output
**Candidate: Jordan Lee — Senior Product Manager**
| Interviewer | Lean | Top strength | Top concern |
|---|---|---|---|
| Priya | Hire | Clear on tradeoffs | Thin on data fluency |
| Tom | No hire | Great communicator | Avoided specifics on past failures |
| Diego | Hire | Strong stakeholder instincts | no submission |
**Consensus strengths**
Stakeholder communication, clear prioritization logic.
**Consensus concerns**
Vague on failures and data-driven decisions — came up in both Priya's and Tom's debrief notes.
**Recommendation**
No hire. Stakeholder skills are real, but two interviewers independently flagged the same gap in analytical depth and self-awareness — too consistent to dismiss.
**Open questions for reference check**
- How does Jordan handle decisions when data is inconclusive?
- How did past managers describe their response to critical feedback?
TipRun this synthesis before the debrief meeting, not in it — when everyone sits down already having read a summary, you spend the meeting resolving real disagreements instead of retelling stories. The open questions for references are often more valuable than the hire/no-hire itself.
ChatGPTGeminiClaude
Prep for a difficult conversation
Plan and role-play a hard feedback conversation before you have it.
Example output
**Step 1 — Opening framing**
"I want to talk about the last three sprint reviews. In each one, the scope changed after we'd already committed — sprint 11 by two features, sprint 12 by one, sprint 13 by three. I'm not attributing intent; I want to understand what's happening and agree on how we handle scope changes going forward."
**Step 2 — Likely responses and replies**
- "The requests came from leadership, not me." → "I understand — and I need us to agree on a process so that when leadership asks, we have a way to respond that doesn't silently absorb the change."
- "I didn't think they were that significant." → "That's useful to know. Going forward, I'd like us to define what triggers a conversation before we say yes."
**Step 3 — Outcome I need**
Agreement that any mid-sprint scope addition requires a 10-minute trade-off conversation with me before it's accepted.
**Step 4 — Role-play**
"Honestly, I feel like I'm being blamed for trying to be helpful. Leadership asks for things and I'm supposed to just say no?"
TipWriting the opening statement before the conversation is the most underused prep step — most difficult conversations go sideways in the first 30 seconds because the manager led with emotion or hedged so much the other person didn't know what the conversation was about. Read your opening aloud; if it sounds like an accusation or a non-statement, revise before you sit down.
ChatGPTGeminiClaude
Interview questions tailored to a role
Generate skill- and behavior-based questions for a specific job.
Example output
Technical
1. "Walk me through how you've structured a sourcing funnel for a role with under 200 qualified candidates in the market." → Strong answer: a specific example with search strategy, outreach rate, and how they adapted.
Behavioral
2. "Tell me about a time a hiring manager wanted a candidate you thought was wrong for the role. What did you do?" → Strong answer: held a position with data, didn't just defer.
Thinking questions
3. "This role has a two-week time-to-fill target. What breaks first and how do you manage it?" → Strong answer: surfaces pipeline risk, sets expectations early, doesn't promise what they can't control.
TipAsk for "what a strong answer includes" in the same request — it forces the model to think about what you are actually trying to learn, not just generate questions that sound good.
ChatGPTGeminiClaude
Help a candidate prep for an interview
Create a prep guide so candidates show up ready and confident.
Example output
Prep guide for [Name] — [Role] interview at [Company], [Date]
Research before you go in:
- Their most recent product launch or press release (check their blog).
- Who's interviewing you — find them on LinkedIn, note anything you have in common.
- Their current job listings to understand where the team is growing.
Likely themes to prep:
- Cross-functional influence: they'll want to know how you work with Engineering without authority.
- Prioritization under ambiguity: they're a Series B company, resources are tight.
- Stakeholder communication: expect a "tell me about a time" on bad news delivery.
Questions to ask them:
- "What does success look like in the first 90 days?"
- "What's the biggest challenge the team is navigating right now?"
Day of: Log in five minutes early. Have your notes somewhere you can glance without reading off them.
TipPersonalize the "likely themes" using the job description — paste it in with the prompt and ask the model to extract what the interviewers actually care about, rather than writing generic advice.
ChatGPTGeminiClaude
Build an interview scorecard
Turn loose notes into a consistent scorecard for fair comparison.
Example output
Candidate: Priya Nair | Role: Senior Product Manager
| Criterion | Rating | Evidence |
|---|---|---|
| Strategic thinking | 4 | Mapped the competitive landscape unprompted and identified a positioning gap. |
| Cross-functional influence | 3 | Solid example with Engineering; less clear on how she handles Sales conflict. |
| Data fluency | 3 | Comfortable with funnel metrics; SQL depth not assessed. |
| Communication clarity | 4 | Explained a complex tradeoff in under two minutes without jargon. |
| Domain knowledge | 2 | Fintech background is thin; prior work is primarily e-commerce. |
| Leadership | Not assessed | No direct reports questions asked in this round. |
Overall: 3.2 | Signal: Advance — with a note to probe domain fit in the next round.
TipIncluding "not assessed" as a valid rating prevents the scorecard from looking more complete than the interview was — a gap in the data is useful information for the next interviewer.
ChatGPTGeminiClaude
Phone screen question list
Plan a 15-minute phone screen that filters fast without being cold.
Example output
Warm-up (keep both)
1. "How did you find out about this role?" — reveals whether they sought us out or got blasted.
2. "What does your week typically look like in your current job?" — gets them talking, helps you calibrate pace.
Quick filters (ask all three)
3. "This role requires [specific certification] — do you currently hold that?" — hard stop if no.
4. "The target comp range is [range] — does that work for you?" — covers comp mismatch early.
5. "We're planning a start date around [date] — any constraints on your end?" — surfaces notice period issues.
Motivation / culture
6. "What would need to be true about a new role for you to say it was the right move?" — cut this if short on time.
7. "What's one thing about your current setup you're hoping changes?" — honest answer tells you a lot.
Closing: "I'll follow up by [day] with next steps. Any questions for me before we wrap?"
TipPut comp and hard requirements in the first five minutes — discovering a mismatch at minute 12 wastes both your time. The warm-up questions are worth keeping because cold screens produce worse signal.
ChatGPTGeminiClaude
Prep talking points for a parent conference
Plan a balanced, specific set of talking points before the meeting.
Example output
Conference prep — Deshawn Harris, Grade 6
Strengths (open with these):
- Reading comprehension: consistently scores above grade level on cold reads; identified the author's irony in the Langston Hughes poem unprompted.
- Persistence: started the quarter needing three prompts to start a task; now self-starts on most assignments.
Growth areas:
- Written output: strong ideas verbally but written drafts average 40% of required length. Example: last persuasive essay had a solid argument but stopped at one paragraph.
- Organization: misses roughly 1 in 3 homework submissions, not due to comprehension.
Questions for parents:
- "Does Deshawn have a consistent homework routine at home?"
- "Is there anything going on this year that I should know about?"
Proposed next step: Daily written-output goal (minimum 3 sentences) tracked on a simple chart Deshawn keeps at his desk.
TipDrafting the questions you'll ask parents is as important as what you plan to say — a parent who feels heard shares information that can change your classroom approach for the rest of the year.
ChatGPTGeminiClaude
Prep for an internship interview
Build a prep plan with likely questions and strong answers.
Example output
Behavioral questions:
1. "Tell me about a time you worked under a tight deadline." Framework: Final project in Intro to Data Analysis — describe scope, constraint, your prioritization, what you shipped.
2. "Describe a situation where you had to learn something quickly." Framework: Self-taught Python for your stats lab over two weeks; what you used, what confused you, outcome.
Technical questions:
1. "Walk me through how you would clean a dataset with missing values."
2. "What is the difference between supervised and unsupervised learning?"
Smart questions to ask:
1. "What does a typical first-week project look like for interns here?"
2. "What's a skill past interns have said they wished they came in with?"
TipGiving your major, year, and one piece of real experience lets the model suggest frameworks grounded in your actual history — otherwise you get generic answers no interviewer believes.
ChatGPTGeminiClaude
Run a mock interview with AI
Practice a real interview with follow-ups and feedback.
Example output
"Thanks for coming in — can you tell me a little about yourself?"
[Student answers]
Coaching note: Your opening was clear and included a relevant project — good. The second half drifted into listing coursework without connecting it to the role. End with one sentence on why this specific internship, not internships in general.
Follow-up: "You mentioned the data project — what was your actual contribution versus the team's?"
[Continues for 5 rounds]
Overall debrief: Strong on specific examples. Pattern to fix: you front-load the context and rush the result — flip the ratio. Phrase you overused: "basically" (4 times). Replace it with a pause.
TipSet the company type to the actual company you are targeting, not a generic placeholder — the follow-up questions get sharper when the role context is real.
ChatGPTGeminiClaude
Nail "tell me about yourself"
Craft a tight, memorable answer to the opener everyone fumbles.
Example output
Right now I'm finishing my junior year in Economics at Ohio State, and most of my energy this semester has gone into a consulting project where my team analyzed pricing strategy for a regional grocery chain — we built a demand elasticity model that ended up influencing how they set promotions in two product categories.
Before that, I spent last summer as a research assistant tracking commodity prices for a professor's paper on inflation pass-through. That's where I got comfortable working with large, messy datasets — and realized I wanted to apply that kind of analysis in a faster-moving commercial environment.
That's what draws me to the strategy team here — I like the idea of working on questions where the data is complicated and the decision actually ships.
I'd love to hear more about the types of problems the team is working on this cycle.
TipThe present-past-future arc works because it is easy to follow and ends with forward momentum. The closing hook ("I would love to hear more about…") turns your answer into a conversation rather than a monologue.