You are a seasoned operator who has written dozens of strategy memos for founders. Draft a one-page strategy memo for the following situation.
Company: [COMPANY NAME]
Stage: [PRE-SEED / SEED / SERIES A / GROWTH]
Team size: [NUMBER OF PEOPLE]
The strategic question: [THE EXACT DECISION WE NEED TO MAKE]
Key constraints: [BUDGET, TIMELINE, HEADCOUNT, OR OTHER LIMITS]
What we already know: [2-3 RELEVANT FACTS, METRICS, OR PRIOR ATTEMPTS]
Structure the memo with these sections:
1. TL;DR (3 sentences max)
2. The decision and why it matters now
3. Two or three real options, each with pros and cons
4. Your recommendation, with reasoning
5. Risks and how we'd mitigate them
6. What we'd commit to in the next 30 days
Write it like a smart 28-year-old chief of staff. No buzzwords. Short paragraphs. Use plain English a board member could follow.
Why this works
It pins down the role (seasoned operator) and forces a fixed memo structure, so the AI can't drift into generic "strategy" filler. The "no buzzwords" instruction strips out the consultant-speak most models default to.
Act as a head of talent who has hired and calibrated dozens of [ROLE TITLE]. Build a hiring scorecard I can use to evaluate candidates fairly.
Role context:
- Role: [JOB TITLE]
- Level: [JUNIOR / MID / SENIOR / STAFF / DIRECTOR]
- Team they'll join: [WHICH TEAM AND WHY THE ROLE EXISTS]
- Top outcomes for the first 6 months: [2-3 OUTCOMES]
- Non-negotiables: [HARD REQUIREMENTS]
Output the scorecard as a table with these columns: Competency, Why it matters, Strong evidence, Weak evidence, Interview question to test it. Include 6-8 competencies, mixing hard skills and behaviors.
Then add a short rubric (1-4 scale) for each competency and a final hiring decision section with three outcomes: Strong yes, Lean yes, No. Keep language concrete. Avoid words like "rockstar," "ninja," or "passionate."
Why this works
Asking for a table with named columns forces the AI into a structured artifact you can paste straight into Notion or Greenhouse. The banned-words list quietly removes the generic startup-speak that makes scorecards useless.
You are a senior product researcher who specializes in finding patterns across messy qualitative data. I will paste raw notes from [NUMBER] customer interviews below. Synthesize them into a structured insight report.
Context:
- Product: [WHAT YOU SELL]
- Who we interviewed: [TYPE OF CUSTOMER]
- The question we were trying to answer: [YOUR RESEARCH QUESTION]
Produce the following:
1. The 5 most-repeated quotes or phrases (verbatim where possible)
2. 3 themes that came up across multiple interviews, each with which interviewees mentioned it
3. The single biggest unmet need
4. The strongest objection or piece of friction
5. Two surprising findings that contradict our assumptions
6. A short list of follow-up questions we should ask in the next round
Do not invent quotes. If something only one person said, mark it as "single source." Keep the report under 600 words.
INTERVIEW NOTES:
[PASTE YOUR RAW NOTES HERE]
Why this works
The "do not invent quotes" instruction is the key — it tells the model to stay grounded in your text instead of hallucinating customer voices. Asking for "single source" tagging makes the output honest about how strong each finding actually is.
Act as a Chief of Staff who has rolled out OKRs at three different companies. Help me draft quarterly OKRs.
Company context:
- Company: [COMPANY NAME]
- Quarter: [Q1 / Q2 / Q3 / Q4 + YEAR]
- Team size: [NUMBER OF EMPLOYEES]
- Top company priorities: [2-3 PRIORITIES IN PLAIN WORDS]
- Biggest current challenge: [ONE-SENTENCE DESCRIPTION]
- Last quarter's miss or learning: [WHAT DIDN'T GO TO PLAN]
Generate exactly 3 Objectives. Under each, list 3 Key Results.
Each Key Result must include:
- A specific metric and target number
- A baseline placeholder: [CURRENT: ___]
- An owning role (not a person)
- A confidence level: low / medium / high
Format the output as a clean table. Make objectives ambitious but reachable. No vanity metrics — every Key Result must have a clear yes/no or numerical answer at the end of the quarter.
Why this works
Locking the count to "exactly 3 Objectives, 3 Key Results each" stops the AI from over-generating. Asking for confidence levels forces the model to think like a real operator who has to commit, not a consultant listing aspirations.
You are a pricing strategist who has helped B2B and B2C companies repackage their offers. Walk me through a pricing analysis for the following product.
Product context:
- What we sell: [PRODUCT OR SERVICE]
- Who buys it: [BUYER PERSONA AND USE CASE]
- Current price: [PRICE OR "NO PRICE YET"]
- Direct competitors and their prices: [LIST 2-4]
- Our cost to deliver: [APPROX COST PER UNIT OR PER MONTH]
- Goal of this exercise: [INCREASE REVENUE / IMPROVE MARGIN / SIMPLIFY PACKAGING / OTHER]
Produce:
1. A summary of which pricing model best fits this product (subscription, usage, tiered, one-time, hybrid) with reasoning
2. Three pricing options in a comparison table: name, price, what's included, target buyer, expected trade-off
3. Two specific A/B tests we could run in the next 60 days
4. The single biggest risk of getting pricing wrong, and how we'd detect it early
Keep it concrete. No "value-based pricing" platitudes — explain the logic in dollars.
Why this works
Pricing is where AI tools love to deliver vague theory. Forcing three concrete options in a table — plus two testable experiments — drags the answer out of the textbook and into the real numbers your business actually moves.
Act as a competitive intelligence analyst. I'm going to paste public information about a competitor below. Produce a teardown that helps my team understand them, not flatter or panic about them.
Our company: [YOUR COMPANY + ONE-LINE DESCRIPTION]
Our positioning: [HOW YOU DIFFERENTIATE TODAY]
Competitor: [COMPETITOR NAME]
Source material: [PASTE PRICING PAGE, ABOUT PAGE, RECENT BLOG POSTS, REVIEWS, OR WHATEVER YOU HAVE]
Produce:
1. Their likely ideal customer profile (be specific about company size, role, budget)
2. Their core value proposition in one sentence
3. Pricing model and what it tells us about their unit economics
4. Three things they appear to do better than us
5. Three things we appear to do better than them
6. Two moves they're likely to make in the next 6-12 months
7. Two ways we could sharpen our positioning starting this week
Be honest, not motivational. If we're losing on something, say so plainly.
Why this works
"Be honest, not motivational" is doing a lot of work here. Without it, the model defaults to a flattering teardown that makes you feel good. Pasting your own source material also keeps the AI grounded instead of inventing competitor facts.
You are a CEO coach who has reviewed hundreds of monthly investor updates. Draft a clean, honest update I can send today.
Company: [COMPANY NAME]
Period: [MONTH AND YEAR]
Key metrics this month: [REVENUE, GROWTH RATE, BURN, RUNWAY, KEY USAGE NUMBERS]
What went well: [2-3 WINS]
What didn't: [2-3 STRUGGLES]
Asks from investors: [INTROS, FEEDBACK, HIRING HELP]
Structure the update as: TL;DR, Highlights, Lowlights, Metrics table, Asks, What's next. The voice should sound like the founder, not a press release. Be specific about numbers...
Act as a senior operator who has written decision docs at high-trust companies. Build a structured decision document for the question below.
The decision: [WHAT WE NEED TO DECIDE]
Decision owner: [ROLE]
Reversibility: [ONE-WAY / TWO-WAY DOOR]
Deadline: [DATE]
Stakeholders: [WHO NEEDS TO REVIEW]
Produce a doc with: Context, Options considered, Selection criteria, Recommendation, Trade-offs accepted, Decision log entry...
You are a blameless post-mortem facilitator. Help me run a structured retro on the following incident or project miss.
What happened: [ONE-PARAGRAPH SUMMARY]
Impact: [CUSTOMER, REVENUE, OR TEAM IMPACT]
Timeline: [KEY EVENTS WITH ROUGH TIMES]
People involved: [ROLES, NOT NAMES]
Produce: a clean timeline, contributing factors split into people/process/tooling, three corrective actions ranked by leverage...
Act as the COO of a fast-moving company. I'll paste this week's metrics, key events, and team updates below. Produce a concise operations review I can share with my leadership team.
Required sections: top 3 wins, top 3 risks, metric movements with commentary, decisions needed this week, what we're watching next week...