Claude Prompts That Make You Decide Faster

<task>Decide whether and how much to raise prices.</task> <context> - Current pricing: [describe tiers] - Last increase: [date + amount] - Customer feedback signals: [recent quotes if any] - Competitor pricing: [data] - Cost trajectory: [margin trend] </context> <output> 1. Justification check: what value increase justifies a price increase customer-side? 2. Three price-increase scenarios: 10%, 20%, 30% — projected churn at each, projected revenue at each. 3. Grandfather decision: keep existing customers at old price or migrate them? 4. Comms strategy: who hears first, what framing, what timing. 5. Risk: churn cliff, sales-cycle drag, public reaction. 6. Recommended increase + 90-day rollout plan. </output>

<task>Decide whether to lower prices.</task> <context> - Current price: [amount] - Conversion rate: [%] - Win/loss reasons in last 90 days: [list] - Margin: [current] - Competitor pricing: [comparable products] </context> <output> 1. Is price the actual blocker (per win/loss data) or are we projecting? 2. Demand elasticity estimate: at -20% price, conversion lift needed to break even. 3. Brand/perception risk of lowering price. 4. Alternative: keep price, add value vs cut price (which moves the needle more?). 5. Annual margin impact at each scenario. 6. Recommendation with the strongest counter-argument. </output>

<task>Restructure pricing tiers.</task> <current> - Tier 1: [name, price, features] - Tier 2: [name, price, features] - Tier 3: [name, price, features] - Distribution: [% customers in each] - Top requested features: [list] </current> <output> 1. Tier-by-tier diagnosis: who's in each, why, where they upgrade/downgrade. 2. Feature gating analysis: what gates work (drive upgrades) vs what gates annoy (drive churn). 3. New tier proposal: 3 tiers with prices, features, target persona for each. 4. Migration path for existing customers (grandfather, opt-in, force-migrate). 5. Pricing-page narrative: what message each tier sends. 6. Risks + the test we'd run before full rollout. </output>

<task>Decide our discount strategy.</task> <context> - Current discount practice: [describe] - Most common discount request: [%] - Win rate with vs without discount: [data] - Avg ACV impact: [data] - Sales rep autonomy: [current rules] </context> <output> 1. Strategic position on discounts: never / rarely / situationally / always negotiate. 2. Approved discount ladder: % bands tied to commitment (annual prepay, multi-year, etc.). 3. Sales rep authority: when to escalate, when to walk. 4. Discount-killer alternatives: trials, extra seats, services, deferred start. 5. Margin impact of each scenario at current win rate. 6. Recommendation + the 90-day measurement plan. </output>

<task>Decide whether to add, kill, or modify our free tier.</task> <context> - Current state: [free tier exists / doesn't] - Free → paid conversion: [%] - Free user support cost: [hours/month] - Free tier strategic role: [acquisition / awareness / data] - Competitor free tiers: [describe] </context> <output> 1. Free tier ROI: cost to serve vs paid conversions generated. 2. Strategic role check: is it actually driving the role we claim? 3. Three options: kill free / shrink free / keep free / expand free — projected impact each. 4. Top-of-funnel alternative if we kill free (trial, freemium-of-features, demo). 5. Migration plan if we modify or kill. 6. Recommendation with 90-day signal we'd measure. </output>

<task>Decide pricing for [specific enterprise deal].</task> <deal> - Prospect: [company] - Stated budget: [if shared] - Use case: [describe] - Stakeholders: [count] - Competition: [other vendors] - Strategic logo value: [yes/no/why] </deal> <output> 1. Anchor price: what we'd charge a typical company this size. 2. Strategic adjustments: logo discount, multi-year discount, expansion-bet discount. 3. Walk-away price: minimum we'd take. 4. Above-anchor scenarios: what'd justify pricing above the anchor. 5. Negotiation moves: what we give if they push (deeper discount vs more value). 6. Recommended opening price + the three concession ladder. </output>

<task>Decide how aggressively to push annual contracts vs monthly.</task> <context> - Current annual %: [%] - Annual discount currently offered: [%] - Cash position: [months runway] - Churn rate monthly vs annual: [data] - Sales cycle implications: [annual slower?] </context> <output> 1. LTV impact: monthly vs annual customer lifetime value (with churn factored). 2. Cash impact: annual prepay vs monthly streaming at current growth. 3. Sales-cycle drag of pushing annual (objections, longer close). 4. Discount calibration: discount % that maximizes annual conversion without margin loss. 5. Comms / packaging: how the offer is shown on pricing page. 6. Recommendation: hard push annual / nudge / customer choice. </output>

<task>Decide whether and how to introduce geographic pricing.</task> <context> - Current pricing: [single global] - Geographic mix: [% by region] - Purchasing-power differences in target markets: [data] - Risk of arbitrage (people gaming via VPN): [low / med / high for our product] - Competitor practice: [describe] </context> <output> 1. Markets where current price is a meaningful blocker (be specific). 2. PPP-adjusted pricing proposal for top 3 underpenetrated markets. 3. Arbitrage protection: payment-method gating, address verification, etc. 4. Existing-customer policy if they relocate. 5. Revenue impact: new sales vs cannibalization. 6. Recommended rollout: which markets first, what timeline. </output>

<task>Decide which add-ons to introduce.</task> <context> - Current product: [describe] - Top customer requests not in core: [list] - Top reasons for churn or downgrade: [list] - Team capacity to build: [hours] </context> <output> 1. Add-on candidate list ranked by: revenue potential × adoption likelihood × build cost. 2. Bundle vs separate decision per candidate. 3. Adoption funnel: how customers discover and try the add-on. 4. Margin: which add-ons are high-margin (digital, automated) vs low (services). 5. Risk: do any add-ons signal core product gaps that should be fixed instead? 6. Recommendation: top 2 to ship next quarter, top 1 to kill before starting. </output>

<task>Decide how to sunset [old pricing plan] while keeping legacy customers.</task> <plan> - Plan name: [describe] - Customers on it: [count + % of total] - Revenue from it: [amount] - Why it's being sunset: [strategic reason] </plan> <output> 1. Migration paths: nearest new plan, custom landing, or grandfather forever. 2. Communication timing: notice period, framing, who gets what message. 3. Special-case handling: high-value legacy accounts, multi-year prepays. 4. Sales / support enablement: scripts, FAQ, escalation criteria. 5. Revenue scenarios: best case, expected, worst case under each migration path. 6. Recommended approach + the 90-day execution plan. </output>

<task>Decide whether to offer founding-member pricing.</task> <context> - Stage: [pre-launch / early / scaling] - Current pricing plan: [if any] - Distribution channel for founding members: [waitlist, network, social] - Desired commitment from them: [feedback, case studies, testimonials] </context> <output> 1. Strategic role of founding-member pricing (loyalty, social proof, feedback, cash). 2. Pricing options: lifetime discount, locked-in price, free year, lump-sum lifetime. 3. Cap: how many founding members and why that number. 4. Obligation: what we commit to vs what they commit to (feedback cadence, case studies). 5. Cost over time: revenue we forgo vs value we capture. 6. Recommendation + exact offer language. </output>

<task>Decide whether to grandfather existing customers at old pricing or migrate them.</task> <context> - Old price: [amount] - New price: [amount + when introduced] - Active customers on old price: [count + revenue] - Goodwill considerations: [recent issues if any] - Cash impact of migrating: [estimate] </context> <output> 1. Grandfather-forever vs migrate-with-notice vs hybrid (partial increase) — financial impact each. 2. Customer reaction modeling: who'd churn vs accept under each path. 3. Loyalty / fairness narrative: how each path lands with the customer base. 4. Operational cost: maintaining old pricing infrastructure forever. 5. Sales-side implication: do current discounts to new prospects undermine the grandfather? 6. Recommendation + the comms wording. </output>

<task>Decide whether to bundle or unbundle [product / set of features].</task> <context> - Current packaging: [bundled / unbundled / hybrid] - Customer purchase patterns: [data] - Stage of market: [early adopter / mainstream / mature] - Competitor packaging: [describe] </context> <output> 1. Bundle case: simpler buying, higher ACV, harder to compare. 2. Unbundle case: lower entry price, easier expansion, modular adoption. 3. Market-stage match: early markets often bundle; mature markets often unbundle (or rebundle). 4. Pricing power: which path captures more value at our stage? 5. Comms / positioning shift required for the new packaging. 6. Recommendation + the 90-day test plan. </output>

<task>Decide whether to switch to usage-based pricing.</task> <context> - Current model: [flat / per seat / hybrid] - Variable cost per unit (compute, API, etc): [data] - Customer usage distribution: [P50, P90, P99] - Customer feedback on current model: [signals] - Cash predictability requirement: [investor expectations] </context> <output> 1. Margin variability under usage-based vs flat — model scenarios. 2. Customer-acquisition impact: easier entry vs harder forecasting for them. 3. Predictability hit: revenue forecastability decreases — quantify. 4. Hybrid models: base + usage, credits, committed-spend with overage. 5. Migration plan for existing customers (forced vs optional). 6. Recommendation with the riskiest assumption flagged. </output>

<task>Decide whether to offer a lifetime deal.</task> <context> - Product type: [recurring / one-time-ish] - Current MRR per customer: [average] - Cash runway: [months] - Distribution channel for LTD: [AppSumo, own audience, partnership] - Strategic stage: [need cash now / building long-term LTV] </context> <output> 1. Cash now vs revenue forever — break-even months calculation. 2. Customer-base composition risk: LTD buyers behave differently than recurring (more support, less loyal). 3. Pricing: LTD price that's break-even at year 2 vs year 3 vs year 5. 4. Cap: limited slots, sunset date, tiered. 5. Brand / positioning risk of being "the LTD product." 6. Recommendation: yes/no + structure if yes. </output>

<task>Set negotiation floor and ceiling for [type of deal].</task> <context> - Typical deal size: [data] - Margin profile: [data] - Strategic value of close rate vs price: [describe] - Authority structure: [who can approve what] </context> <output> 1. List price (anchor). 2. Standard discount band: 0-15% (rep authority). 3. Manager escalation band: 15-25% (with justification). 4. Exec escalation band: 25-35% (rare, strategic only). 5. Walk-away floor: below this, decline the deal. 6. What we ask for in return at each discount level (commitment, term, expansion). </output>

<task>Decide our refund policy.</task> <context> - Current policy: [describe] - Refund rate: [%] - Top refund reasons: [list] - Customer service load from refunds: [hours/week] - Competitor policies: [describe] </context> <output> 1. Liberal vs strict refund — what each says about brand confidence. 2. 30-day money-back vs no-questions-asked vs case-by-case — abuse risk each. 3. Refund vs credit vs alternative compensation analysis. 4. Trial-first alternative: would a longer free trial reduce refund volume? 5. Annual revenue impact at each policy. 6. Recommendation + the exact policy language. </output>

<task>Decide cancellation win-back offer.</task> <context> - Cancellation rate: [%] - Top cancellation reasons: [list] - Customer LTV vs CAC ratio: [data] - Current win-back attempts: [describe] </context> <output> 1. Win-back offer ladder: discount, pause, downgrade, custom — when to use each. 2. Triggers: which cancellation reasons get which offer. 3. Cost / benefit per offer: revenue retained vs concession given. 4. Brand risk: aggressive win-back can feel desperate. 5. Limit: cap on win-back attempts per customer per year. 6. Recommendation + scripts for the top 3 cancellation reasons. </output>

<task>Decide whether to run a Black Friday / seasonal promo.</task> <context> - Past promo performance: [if any] - Brand positioning: [premium / accessible / discount-friendly] - Customer expectations: [trained to wait for promos?] - Margin headroom: [%] - Team capacity for promo execution: [hours] </context> <output> 1. Strategic role of the promo: new acquisition / win-back / cash injection / cultural moment. 2. Promo structure options: % off, BOGO, gift, free trial extension, bundle. 3. Risk of training customers to wait: quantify if past data exists. 4. Margin impact: gross profit per new customer acquired through promo. 5. Comms plan: pre-launch tease, launch, last-call. 6. Recommendation + the kill criteria if performance is weak by day 2. </output>

<task>Decide how to react to [competitor] changing their pricing.</task> <context> - Competitor: [name] - Change: [their new pricing vs old] - Their positioning shift implied: [describe] - Our overlap: [shared customers / similar product] - Customer feedback on the change: [if any] </context> <output> 1. Did they raise (validates market) or lower (creates pressure)? 2. Match / hold / counter-position — three reaction options analyzed. 3. Customer-side: who'll defect either direction and why. 4. Sales enablement update: talking points for prospects asking about it. 5. Public response: silent vs subtle vs direct counter. 6. Recommendation + the 30-day measurement plan. </output>

<task>Decide whether to hire FTE or contract out [function].</task> <context> - Function: [describe] - Estimated hours/week needed: [number] - Specialized vs commodity skill: [describe] - Current team capacity: [if any] - Cash position: [runway] - 12-month forecast for the work: [growing / stable / one-time] </context> <output> 1. Total cost: FTE fully-loaded vs contractor (don't forget hidden FTE costs). 2. Output quality / consistency under each model. 3. IP / continuity risk of contractor. 4. Speed-to-productive: how fast each can deliver. 5. Reversibility: easier to end a contractor relationship than fire an FTE. 6. Recommendation + the 6-month review trigger to revisit. </output>

<task>Design the first hire for [function] we don't have yet.</task> <context> - Function: [marketing / sales / product / etc.] - Current state: [founder-led / contractor / nothing] - 12-month goal for the function: [describe] - Team they'd work with: [list] - Reporting line: [direct to founder?] </context> <output> 1. Generalist vs specialist for the first hire — why. 2. Seniority decision: someone who can build alone vs someone who needs scaffolding. 3. Top 3 must-have skills + top 2 nice-to-haves. 4. Compensation band benchmark (with location adjustment if remote). 5. 90-day expected output to validate fit. 6. Red flags to screen for in interviews (function-specific). </output>

<task>Decide whether to hire senior or junior for [role].</task> <context> - Role: [describe] - Existing team structure: [who they'd work with] - Mentorship capacity available: [hours/week] - Budget: [comp range] - Urgency: [need them productive in X weeks] </context> <output> 1. Senior pros: speed to productive, lower management overhead, hiring brand signal. 2. Junior pros: lower cost, longer tenure, growth path, culture-shaping. 3. Mentorship reality check: is there actually capacity to develop a junior? 4. Org-shape consequence: too many seniors = no growth path; too many juniors = bottlenecked seniors. 5. Recommendation + the alternative scenario (what changes if budget shifts). </output>

<task>Set compensation band for [role].</task> <context> - Role: [title + level] - Location flexibility: [remote / hub-based] - Top 2 competitors for this talent: [companies they'd consider] - Internal equity reference points: [comp of comparable role] - Cash vs equity philosophy: [our stance] </context> <output> 1. Market data: 25th, 50th, 75th percentile from public sources (Levels, Pave, Glassdoor estimates). 2. Internal equity check: where does this sit vs other roles at same level? 3. Floor: minimum we'd offer + why. 4. Anchor: opening offer. 5. Ceiling: above this, requires founder approval. 6. Equity grant + vesting if applicable. </output>

<task>Decide whether [team member] is salvageable or should be let go.</task> <context> - Person: [role, tenure] - Specific performance issues: [list with examples] - Their strengths: [be specific] - Manager feedback / coaching given: [history] - Team impact: [morale, output, blocking others] </context> <output> 1. Skill issue vs will issue vs fit issue — diagnose. 2. PIP viability: are the gaps coachable in 60-90 days? 3. Cost of keeping (their salary + team drag + manager time). 4. Cost of replacing (recruit, ramp, severance). 5. Team-side honesty: what would the team think if we kept them / let them go? 6. Recommendation + the conversation plan. </output>

<task>Decide whether to promote [team member] to [next level].</task> <context> - Person: [role, tenure] - Performance against current level: [reviews / wins / metrics] - Evidence of next-level operation: [specific examples] - Comparable peers at the next level: [for calibration] - Team-impact of promotion (positive / negative): [describe] </context> <output> 1. Operating at next level NOW (not "potential") — yes / partial / no, with evidence. 2. Promotion gaps that need closing first — list with timelines. 3. Comp adjustment required at next level. 4. Team-side reaction: who'd be upset, who'd be inspired. 5. Risk of NOT promoting (flight risk, motivation, signal to team). 6. Recommendation + comms plan. </output>

<task>Reorganize [team / org] structure.</task> <context> - Current structure: [describe] - Pain points: [decision speed, accountability, communication] - Strategic priorities for next 12 months: [list] - Team size: [current + planned hires] </context> <output> 1. Diagnosis of structural pain: who's blocked by what? 2. 2-3 alternative structures with pros/cons each. 3. Reporting line changes required. 4. Title / role changes (any demotions disguised as moves?). 5. Comms sequence: who hears first, what gets shared when. 6. Recommended structure + the 30-60-90 day rollout. </output>

<task>Decide remote vs in-office for [role].</task> <context> - Role: [describe] - Team's current distribution: [remote / hybrid / in-office] - Role-specific collaboration needs: [describe] - Talent pool size at each option: [local vs national vs global] - Comp differential by geography: [estimate] </context> <output> 1. Talent pool size: local vs national vs global — order of magnitude. 2. Role's collaboration profile: lone-wolf / pair / heavy meeting. 3. Comp implications under each model. 4. Onboarding considerations: remote ramps slower without structure. 5. Manager-side capacity to manage remote. 6. Recommendation + the dealbreaker that'd flip it. </output>

<task>Decide whether to fill [role] internally or externally.</task> <context> - Role: [describe] - Internal candidates: [list with current roles] - External market: [easy / hard to recruit] - Role's strategic newness: [continuity vs change?] </context> <output> 1. Internal candidate readiness: are they at level now, or 6 months away? 2. External hire upside: fresh perspective, broader experience. 3. Internal hire upside: continuity, retention signal, culture fit. 4. Risk of passing over an internal candidate (motivation, attrition). 5. Hybrid: external hire with internal stretch role created. 6. Recommendation + comms plan. </output>

<task>Decide equity grant for [hire / promotion].</task> <context> - Role: [level + function] - Stage of company: [seed / Series A / B / later] - Cash comp offered: [amount] - Internal equity reference points: [comparable existing grants] - Their previous equity expectations: [if known] </context> <output> 1. Stage-adjusted equity range for this level (e.g., seed eng level 3: 0.1-0.3%). 2. Internal equity check: where does this sit vs peers? 3. Cliff / vest schedule (standard 4-year, 1-year cliff vs alternatives). 4. Refresh schedule: when next grant comes. 5. Cash-vs-equity trade: are they more cash-motivated or upside-motivated? 6. Recommendation + offer language. </output>

<task>Decide whether to counter-offer [departing team member].</task> <context> - Person: [role, tenure, performance] - Their stated reason for leaving: [if known] - Their new offer: [amount + role + company if known] - Strategic value to us: [be honest] - Counter-offer history at our company: [any precedent?] </context> <output> 1. Is the actual motivator money or something else? (Money usually masks the real reason.) 2. Counter math: cost of counter vs cost of replacement and ramp. 3. Counter-offers fail 70% of the time within 12 months — apply to this case. 4. Precedent risk: counter-offering one teaches others to fish. 5. Goodwill exit alternative: structured handoff, recommendations, alumni network. 6. Recommendation + the conversation. </output>

<task>Decide whether to hire a manager for [team].</task> <context> - Team size: [count] - Current manager: [founder-led / IC-leading / nobody] - Team's pain points: [communication, prioritization, growth] - Strategic priorities the team owns: [list] </context> <output> 1. Team size threshold check: typically managers needed at 5-7 direct reports. 2. Founder bandwidth check: hours/week currently spent managing this team. 3. IC-promotion alternative: can someone on the team grow into the role? 4. External manager hire vs internal promotion — pros/cons each. 5. Risk: bad managers do more damage than no manager. Hiring bar. 6. Recommendation + the 90-day fit milestones. </output>

<task>Decide whether to replace [departing role] or restructure work.</task> <context> - Departing role: [describe] - Their actual outputs in last 6 months: [list] - Team capacity if work redistributed: [estimate] - Strategic importance of the function: [be honest] </context> <output> 1. Output audit: which outputs were valuable, which were vestigial? 2. Redistribution map: who could absorb what (with capacity check). 3. Replacement option: same role / different role / not refilled. 4. Cost: hire cost + manager time vs redistribution overhead. 5. Risk: under-resourcing creates burnout 90 days later. 6. Recommendation + the 60-day re-evaluation criteria. </output>

<task>Define layoff selection criteria for [headcount reduction].</task> <context> - Cut size: [number / %] - Strategic priorities post-cut: [what must keep functioning] - Team distribution: [function and seniority breakdown] - Tenure / performance data: [available] - Legal jurisdiction: [WARN Act, etc.] </context> <output> 1. Strategic-need filter: which functions / roles must remain intact. 2. Performance filter: where lower-quartile performers exist. 3. Redundancy filter: where role overlap exists. 4. Criteria documented: explicit, defensible, applied consistently. 5. Legal review checklist: protected classes, WARN Act, severance norms. 6. Final selection framework + the executive sign-off process. </output>

<task>Decide severance package for [layoff / single termination].</task> <context> - Type: [layoff / performance / mutual] - Person / group: [describe] - Tenure: [data] - Geographic / legal jurisdiction: [list] - Budget for severance: [if any] </context> <output> 1. Statutory minimum by jurisdiction. 2. Industry / stage norms (e.g., early-stage SaaS: 2-4 weeks per year tenure). 3. Goodwill premium: extra weeks for layoff vs performance. 4. Benefits continuation: COBRA, equipment, references, alumni. 5. Release / non-disparagement: scope and risks. 6. Recommended package + total cost. </output>

<task>Decide founding-team equity split.</task> <context> - Founders: [list with roles] - Idea origin: [who] - Capital contributed: [if any] - Time commitment so far: [full-time / part-time per founder] - Future time commitment: [planned] </context> <output> 1. Equal split vs role-weighted vs contribution-weighted — pros/cons each. 2. Vesting: standard 4-year cliff vs alternatives (especially with prior work). 3. Reverse vesting / leaver provisions: bad-leaver, good-leaver scope. 4. Pre-formation work credit (idea, IP, prototype). 5. Future-dilution expectations: who's OK with which dilution path. 6. Recommended split + the conversation to have before signing. </output>

<task>Help me decide how to resolve [co-founder conflict].</task> <context> - Conflict: [describe] - History: [recurring vs one-off] - Stakes: [low / company-existential] - Each founder's stated position: [list] - Each founder's underlying interest (often different from position): [if known] </context> <output> 1. Position vs interest analysis: what does each side actually want? 2. Decision rights: whose call is this by function / by stake? 3. Options menu: 4-5 ways to resolve, ranked by mutual acceptability. 4. The conversation: how to start it without it spiraling. 5. Worst-case planning: if this isn't resolvable, what does separation look like? 6. Recommended next step (sometimes that's a 3rd-party mediator, not an answer). </output>

<task>Allocate performance review tiers across the team.</task> <context> - Team: [count + roles] - Performance signals: [outputs, peer feedback, manager feedback] - Last cycle's distribution: [if any] - Compensation budget for raises: [%] - Calibration goals: [forced ranking, no-forced-ranking, hybrid] </context> <output> 1. Tier definitions: top-performer, strong, meets, below — what each looks like. 2. Distribution: forced curve vs natural distribution — pros / cons. 3. Calibration: cross-team comparison to prevent inflation. 4. Edge cases: new hires, parental leave returners, role-change mid-cycle. 5. Raise / bonus / equity refresh implications per tier. 6. Recommended distribution + manager conversation guide. </output>

<task>Refine job description for [role] by deciding which requirements are must-have vs nice-to-have.</task> <context> - Role: [title] - Initial JD: [paste] - Talent pool reality: how rare each requirement is in the market. - Strategic must-do outputs: [what they actually need to deliver] </context> <output> 1. Must-haves (3-5 max): non-negotiable, would fail without. 2. Nice-to-haves: helpful but not required. 3. Disqualifiers: filters in screening. 4. The "kitchen sink" items in the original JD that probably aren't needed. 5. Diversity-of-pool check: does the JD as written exclude qualified candidates? 6. Rewritten JD + the candidate persona. </output>

<task>Stress-test my Q[X] plan and surface the assumptions it depends on.</task> <plan> - Goals: [list] - Key initiatives: [list] - Resources committed: [hours, headcount, dollars] - Success criteria: [how we'll know] </plan> <output> 1. The 4-5 assumptions this plan depends on (often unstated). 2. Each assumption ranked by fragility (most likely to break first). 3. Leading indicators that'd tell us an assumption is breaking — 60 days before it's obvious. 4. Pre-mortem: imagine this plan failed. What's the most likely failure path? 5. Top 3 things to validate in the first 30 days. 6. The hardest part of the plan nobody's talking about. </output>

<task>Help me decide whether to pivot [direction].</task> <context> - Current product / market: [describe] - Pivot proposal: [where we'd go] - Evidence for pivot: [what's not working in current state] - Evidence against pivot: [what is working] - Pivot cost: [time, money, team, reputation] </context> <output> 1. What's actually broken in current state — is it product, market, distribution, timing? 2. Is the pivot solving the actual problem or projecting hope onto something new? 3. Pivot specificity: pivot WHAT — product, customer, business model, channel? 4. Reversibility: how much of current state we'd lose vs preserve. 5. 90-day pivot validation milestones. 6. Recommendation + the strongest counter-argument. </output>

<task>Help me decide which one bet to focus on.</task> <context> - Options on the table: [list] - Evidence for each: [what we know] - Resources we have: [time, headcount, cash] - Win conditions: [what success looks like for each] </context> <output> 1. Each option scored on: market size, conviction, time-to-evidence, fit with team. 2. Mutually exclusive vs sequencable: can we do A then B, or is it really either/or? 3. The cost of NOT picking each one (regret cost). 4. The cost of picking each one (commitment cost). 5. The bet that maximizes information vs the bet that maximizes outcome. 6. Recommendation + the kill criteria for the chosen bet. </output>

<task>Sequence roadmap items for the next 6 months.</task> <context> - Items on the table: [list with rough effort] - Strategic priorities: [list] - Customer commitments: [if any] - Team capacity: [data] - Compounding items vs one-off items: [if categorized] </context> <output> 1. Dependencies: which items unblock or accelerate others? 2. Risk-adjusted value per item. 3. Compounding sequence vs one-off sequence — which order builds momentum? 4. Customer-commitment fixed dates (can't reschedule). 5. Capacity allocation: % of team time per item. 6. Recommended 6-month sequence + 30/60/90 day milestones. </output>

<task>Decide whether to build or buy [capability].</task> <context> - Capability: [describe] - Build cost estimate: [time + dollars] - Available products to buy: [list with pricing] - Strategic differentiation: is this core or context? - Team's interest in building: [be honest] </context> <output> 1. Core vs context check: is this in our differentiation, or just necessary plumbing? 2. Total cost of ownership: build (with maintenance) vs buy (with subscription compounding). 3. Time-to-value: when does each option produce. 4. Vendor risk: lock-in, pricing power, ecosystem health. 5. Reversibility: easier to buy then build than build then buy. 6. Recommendation with the 18-month review point. </output>

<task>Decide whether to build [capability] or partner with someone who has it.</task> <context> - Capability: [describe] - Potential partners: [list] - Build cost: [estimate] - Strategic value of owning it: [describe] - Customer adoption needs: [describe] </context> <output> 1. What customers need vs what we need: do customers care WHO delivers? 2. Margin / unit economics under each path. 3. Partnership lock-in risk: what happens if partner changes strategy. 4. Time-to-market under each path. 5. Capability staying current: who's better at keeping it competitive — us or them? 6. Recommendation + partnership terms or build sequence. </output>

<task>Decide whether to expand to [geography].</task> <context> - Current geo: [primary market] - Target geo: [describe] - Why now: [signal that triggered the question] - Local capability needs: [language, support, payments, legal] - Investment required: [estimate] </context> <output> 1. Demand evidence in target geo (organic signal vs hope). 2. Local capability gaps: language, payments, support, legal, sales motion. 3. Light vs full expansion: try-it-with-existing-product vs localized-product. 4. Investment + 18-month financial outlook. 5. Distraction cost: focus pulled from core geo. 6. Recommendation + the 90-day validation experiment. </output>

<task>Decide whether to expand vertically or horizontally.</task> <context> - Current product: [describe] - Current customer: [describe ICP] - Vertical expansion option: deeper for current ICP — [describe] - Horizontal expansion option: same product, new ICP — [describe] - Evidence pulling each direction: [list] </context> <output> 1. Pull strength: which direction is the market asking for, with evidence? 2. Capability fit: which direction matches what we already know? 3. Compounding: which direction creates lock-in or expansion revenue? 4. Risk: which direction breaks our current customer story? 5. Sequencing: can we do one then the other? 6. Recommendation + the leading indicator we'd watch for 90 days. </output>

<task>Decide whether to open-source [component / product].</task> <context> - What's being considered: [describe] - Strategic role: [acquisition / community / standard-setting / hiring] - Business model implications: [how we monetize if open-sourced] - Competitive risk: [who'd benefit] - Team capacity to maintain open-source community: [hours/week] </context> <output> 1. Strategic role: is open source actually serving what we claim it serves? 2. Business model fit: open core, dual-license, services, sponsored development — which? 3. Competitive risk: who benefits more from open source — us or competitors? 4. Maintenance reality: open source isn't free — community management cost. 5. License choice: MIT / Apache / GPL / source-available — implications. 6. Recommendation + the success metric for year 1. </output>

<task>Decide whether [feature] should be free or paid.</task> <context> - Feature: [describe] - Cost to build/maintain: [data] - Customer value: [how much pain it solves] - Strategic role: acquisition vs expansion vs retention - Current free/paid split philosophy: [describe] </context> <output> 1. Feature's strategic role: hook (free) / value (paid) / retention (free). 2. WTP signal: would customers pay separately? 3. Adoption ceiling: does paid gating prevent the network effects we need? 4. Pricing tier fit: which existing tier should it be in? 5. Cannibalization risk: does it weaken anything paid we already offer? 6. Recommendation + the rollout test. </output>

<task>Sequence the launch of [feature / product / campaign].</task> <context> - Launch elements: [product, marketing, sales, PR, partnerships] - Strategic goals: [awareness, signups, revenue, narrative] - Dependencies: [what must happen before what] - Risk tolerance: [bold launch vs phased] </context> <output> 1. Risk-adjusted launch model: stealth → soft → public, vs big-bang. 2. Pre-launch sequence: alpha, beta, waitlist, design partners. 3. Launch day: PR, social, email, sales enablement, customer comms. 4. Post-launch: 7-day, 30-day, 90-day milestones. 5. Kill criteria: what'd make us pull / pause the launch. 6. Recommended sequence + the single biggest risk in it. </output>

<task>Decide whether to launch [thing] now or wait.</task> <context> - Thing: [describe] - Readiness: [where it is vs ideal] - Market signals: [what's happening externally] - Competitor activity: [imminent or quiet] - Cost of waiting: [opportunity, runway, momentum] - Cost of launching now: [unfinished, missing features] </context> <output> 1. Market window: is it opening or closing? Evidence. 2. Readiness threshold: what'd be unacceptable to launch without? 3. First-mover vs fast-follower trade-offs. 4. Internal momentum: launch-now energy vs polish-more morale. 5. Reversibility: can we launch now and fix later, or is this one-shot? 6. Recommendation + the 30-day go/no-go criteria. </output>

<task>Decide whether to niche down further or broaden out.</task> <context> - Current positioning: [describe ICP] - Wins / losses by segment: [data] - Distribution channel fit by segment: [data] - Competitive density by segment: [data] - Strategic ambition: [niche dominance vs broad reach] </context> <output> 1. Niche-down case: deeper differentiation, lower CAC, faster reference building. 2. Broaden case: bigger TAM, more dependencies, harder positioning. 3. Where wins are coming from now: signal of where to lean. 4. Where losses are coming from: signal of where you're not yet winning. 5. The unbreakable promise you'd make to the niche (or broad market). 6. Recommendation + 12-month leading indicator to watch. </output>

<task>Decide whether to reposition the brand.</task> <context> - Current positioning: [describe] - Why it's being questioned: [signals] - Proposed positioning: [if any] - Brand equity built: [years, customer recognition, search volume] - Switching cost: [internal effort + external relearning] </context> <output> 1. Is the current positioning broken, or is the messaging just stale? 2. What customers think we are vs what we think we are — gap analysis. 3. Repositioning options: tweak / refresh / hard reset. 4. Risk: alienating existing customers vs being invisible to new ones. 5. Transition plan: rename, redesign, relaunch — sequencing. 6. Recommendation + 90-day measurement plan. </output>

<task>Decide a name for [product / feature / company].</task> <context> - What it is: [describe] - Audience: [describe] - Brand context: [parent brand if any] - Constraints: [domain availability, trademark, search competition] - 3-5 candidate names: [list] </context> <output> 1. Each candidate scored on: pronounceability, memorability, distinctiveness, scaleability. 2. Trademark / domain availability check. 3. Search competition: who else owns this term in SEO. 4. International concerns: meaning in other languages. 5. 10-year scalability: does the name limit what the product can become? 6. Recommendation + a fallback if first choice has issues. </output>

<task>Decide whether to buy [premium domain] for [amount].</task> <context> - Domain: [name] - Asking price: [amount] - Alternative domains we own / could use: [list] - Strategic value: [SEO, brand, defensive] - Current usage by seller: [parked, monetized, used] </context> <output> 1. Domain value categories: brand match, SEO authority, defensive, vanity. 2. Comparable sales for similar domains in this category. 3. ROI math: how much revenue / brand value over 5 years justifies the spend? 4. Alternatives: settle for .co / .ai / different name at much lower cost. 5. Negotiation: ceiling, opening offer, walk-away. 6. Recommendation: buy / negotiate down / pass. </output>

<task>Decide between public launch and continued stealth.</task> <context> - Where we are: [stage, traction] - Public launch upside: [PR, hiring, fundraising, customers] - Stealth upside: [no competitor pressure, slow learning, no PR exposure] - Team's energy / public-readiness: [be honest] - Competitive risk if visible: [low / high] </context> <output> 1. What does going public BUY us right now — be specific. 2. What does going public COST us — competitor attention, hiring expectations, PR drag. 3. Halfway: tier-1 customers know, public doesn't (semi-stealth). 4. The forcing function: what'd make us go public regardless (fundraise, hiring, customer demand). 5. Comms plan if public, stealth-preservation if not. 6. Recommendation + the trigger event. </output>

<task>Decide founder's title and role as the company scales.</task> <context> - Current title: [CEO / co-founder / etc.] - Current scope: [what they actually do] - Company stage: [seed / Series A / B / later] - Team composition: [executive team in place?] - Founder's strengths / weaknesses: [be honest] </context> <output> 1. CEO vs CPO vs CTO vs Chairman — what each title means at this stage. 2. Role narrowing: which areas should the founder hand off and to whom. 3. Energy match: where founder produces 10x value vs 1x value. 4. Title signaling: external vs internal implications of each option. 5. Successor / second-in-command: who covers what. 6. Recommendation + the 90-day handoff plan. </output>

<task>Help me decide whether to quit [strategy / approach].</task> <context> - Strategy: [describe] - Time committed: [months / years] - Results vs goals: [data] - What we'd lose by quitting: [list] - What we'd gain by quitting: [list] </context> <output> 1. Quitting is hard because it codes as failure — separate quitting from failure. 2. Stage of strategy: should it have worked by now? What's the typical timeline? 3. Doubling-down alternative: what'd it take to actually make this work — is it within reach? 4. The 80% test: if you'd told yourself at the start "this would happen," would you have started? 5. Quit-cost: pride, reputation, sunk effort. 6. Recommendation + the language for explaining the quit. </output>

<task>Decide whether to re-org [team / company].</task> <context> - Current state: [structural pains] - Proposed re-org: [if any] - Reasons floated for re-org: [list] - Last re-org: [when, what changed, what worked / didn't] </context> <output> 1. Is the actual problem structural, or are we using re-org to avoid people decisions? 2. Re-org cost: 3-6 months of disruption, attrition risk, lost context. 3. Alternative: fix process, fix manager, fix one role — without org redesign. 4. Re-org payoff: what does the new structure unlock that current doesn't. 5. Comms / sequence / 90-day stability metric. 6. Recommendation + the rules for what NOT to also change while re-orging. </output>

<task>Decide whether to enter [partnership].</task> <partnership> - Partner: [name] - Type: [referral / co-marketing / integration / reseller / strategic] - Proposed structure: [describe] - Their expected value to us: [describe] - Our expected value to them: [describe] </partnership> <output> 1. Strategic fit: does this advance our north star or distract? 2. Asymmetric value: are we getting equal value or are we doing more? 3. Lock-in / exclusivity terms: dangerous or fine? 4. Operating cost: hours/month to actually deliver our side. 5. Reversibility / off-ramp: can we exit cleanly if it underperforms? 6. Recommendation + the 90-day milestone to evaluate. </output>

<task>Decide which [type of] integration partner to prioritize building with.</task> <options>[list candidates with: user overlap, technical fit, strategic alignment, partnership program quality]</options> <output> 1. Each option scored on: user overlap, partnership program leverage, technical effort, strategic alignment. 2. Distribution leverage: which partner's marketing actually moves the needle for us? 3. Engineering cost: which integration is reasonable vs swamping us? 4. Mutual incentive: which partner cares about us, vs which we'd be one of 100 to? 5. Sequencing: 1 deep, 3 shallow — or 1 deep first? 6. Recommendation + the success criteria for the first integration. </output>

<task>Decide whether to set up a reseller / channel partner program.</task> <context> - Current sales motion: [direct, hybrid] - Margin structure: [room for partner cut?] - Strategic geo / vertical fit for partners: [describe] - Team capacity for partner management: [hours] </context> <output> 1. Strategic fit: are channels the natural distribution for our product? 2. Margin math: what % can we give partners and still make it work? 3. Channel conflict: where direct sales and channel collide on accounts. 4. Partner enablement requirements: training, certification, support. 5. Pilot model: 2-3 partners first vs full open program. 6. Recommendation + the 6-month go/no-go criteria. </output>

<task>Evaluate [acquisition offer] for our company.</task> <offer> - Acquirer: [company] - Offer: [structure: cash, stock, earnout] - Total enterprise value: [amount] - Strategic rationale (theirs): [describe] - Timeline / urgency: [their pacing] </offer> <output> 1. Value comparison: offer vs realistic 3-year independent value. 2. Strategic fit: do we believe their thesis for us under the new umbrella? 3. Lock-up / earnout / retention risk: how much of the value depends on staying. 4. Team-side: who'd thrive vs who'd leave post-acquisition. 5. Negotiation leverage: what we can push on (price, structure, autonomy). 6. Recommendation + the 4 alternative outcomes (counter, walk, accept, multi-bid). </output>

<task>Decide whether to accept [acquihire offer] vs continue independent.</task> <context> - Stage: [pre-revenue / early revenue / etc.] - Runway: [months] - Team morale / energy: [be honest] - Offer: [team retention + small premium typically] - Independent path: realistic chance of bigger outcome </context> <output> 1. Independent-path probability honestly assessed. 2. Acquihire outcome for: founders, team, investors. 3. Team future: do they get good roles or get shelved at the acquirer? 4. Personal: founder reputation, network, future-fundraise implications. 5. Walk-away option viability. 6. Recommendation + the negotiating points if proceeding. </output>

<task>Decide which investor / term sheet to take.</task> <options>[list term sheets with: valuation, partner, fund stage, value-add reputation, terms]</options> <output> 1. Each option scored on: valuation, partner quality, fund stage, follow-on capacity, network value, terms cleanliness. 2. The 10-year-relationship view: which partner do we want on this cap table for a decade. 3. Term gotchas: liquidation preference, anti-dilution, board composition, info rights. 4. Speed-to-close: which can move fastest if speed matters. 5. Reference checks: what 3 founders they've backed say about working with them. 6. Recommendation + the negotiation moves before signing. </output>

<task>Decide whether to fundraise or bootstrap from here.</task> <context> - Current state: [revenue, growth, runway] - Capital needs: [what we'd actually use money for] - Path-without-capital: [what we can build from cash flow] - Founder ownership preference: [how much dilution acceptable] - Market opportunity: [winner-take-most vs fragmented] </context> <output> 1. Use of funds: what exactly capital would buy that bootstrap can't. 2. Bootstrap path: realistic ramp at current capital efficiency. 3. Market dynamics: does this market reward fast-and-funded or slow-and-profitable? 4. Dilution math: % given vs % we'd retain in either path at year 5. 5. Founder energy: fundraise mode is expensive in attention. 6. Recommendation + the trigger that'd flip the answer. </output>

<task>Decide whether to raise the next round now or wait.</task> <context> - Current runway: [months] - Current traction: [data] - Traction we'd have in 6 months: [forecast] - Market sentiment for our category: [hot / cooling / cold] - Founder appetite for fundraising right now: [be honest] </context> <output> 1. Runway buffer: never raise with less than 9 months left. 2. Traction inflection: what number we'd hit in 6 months that changes our raise narrative. 3. Market timing: macro / category sentiment in 6 months — better or worse. 4. Opportunity cost: 3-4 months of founder time on fundraise vs on traction. 5. Valuation: where would we land now vs in 6 months at projected metrics. 6. Recommendation + the milestone that changes the answer. </output>

<task>Decide whether to take a down round vs alternatives.</task> <context> - Last round: [valuation] - This round options: [down round terms] - Alternatives: [bridge, convertible, structured, no raise] - Runway: [months] - Cap table sensitivity: [employee / common shareholder impact] </context> <output> 1. Down round structure: clean (just lower valuation) vs structured (with preferences). 2. Cap table impact: employee dilution, common-stock impact, ratchets. 3. Bridge alternative: convertible note with discount, no valuation set today. 4. No-raise path: cut burn, extend runway. 5. Signal: down rounds are loud but survivable; structured rounds are quieter and worse. 6. Recommendation + the comms plan. </output>

<task>Evaluate [target company] as an acquisition.</task> <target> - Company: [name] - What they do: [describe] - Strategic rationale: [why we'd buy] - Estimated cost: [range] - Integration complexity: [low / med / high] </target> <output> 1. Build-vs-buy comparison: what would this cost us to build instead? 2. Strategic fit: revenue accretion vs capability addition vs talent addition. 3. Integration plan: tech stack, team, customer base, brand. 4. Risk: integration failure rate by acquisition type. 5. Cultural fit honesty check. 6. Recommendation + the diligence priorities before LOI. </output>

<task>Decide whether to keep or drop [problem account].</task> <account> - Customer: [name + size] - Issue history: [list] - Revenue: [annual] - Support load: [hours/month] - Strategic value: [logo, reference, expansion potential] </account> <output> 1. Margin reality: revenue minus support load minus management time. 2. Strategic value: is the logo worth the headache? 3. Behavior trend: are issues escalating or resolving? 4. Internal team morale: who's impacted, and how badly? 5. Fire path: terms of disengagement, transition support, comms. 6. Recommendation + the conversation if firing. </output>

<task>Decide whether to make a public statement on [issue / controversy].</task> <context> - Issue: [describe] - Our actual position: [be honest] - Stakeholders: [who'd see it — customers, team, investors] - Risk of staying silent: [list] - Risk of speaking: [list] </context> <output> 1. Our actual stake in the issue: relevant / adjacent / opportunistic. 2. Stakeholder mapping: who needs us to speak vs who'd be alienated. 3. Statement options: silent / brief / detailed / activist. 4. Internal alignment check: would our team feel represented? 5. Long-term consistency: if we speak now, does that commit us to speaking on similar future issues? 6. Recommendation + draft statement if proceeding. </output>

<task>Decide how to respond to [press inquiry / story / coverage].</task> <situation> - Outlet: [name] - Topic: [their angle] - Their deadline: [time] - Our exposure: [reputation, customer, competitive] - Past relationship with this outlet: [if any] </situation> <output> 1. The story will run with or without us — what comment matters? 2. On-record vs background vs no-comment — pros / cons each. 3. Talking points: 3 things we want in the story. 4. Hostile-question prep: what we won't say. 5. Crisis vs opportunity: this can amplify or contain. 6. Recommendation + statement / on-record quote if proceeding. </output>

<task>Decide whether to escalate [legal dispute] vs settle.</task> <situation> - Issue: [describe] - Counterparty: [who, with what resources] - Our position: [strong / mixed / weak] - Settlement on table: [if any] - Strategic cost of fight: [time, distraction, public exposure] </situation> <output> 1. Legal merit: how strong is our case, honestly? 2. Cost / time of full litigation vs settlement. 3. Reputation / precedent: does settling teach others to try this? 4. Counterparty's resolve: are they bluffing or committed? 5. Settlement structure that protects us most. 6. Recommendation + the term they'd never accept (so we know we're starting realistically). </output>

<task>Decide whether to file patent / protect IP on [innovation].</task> <context> - Innovation: [describe] - Patentability assessment: [from counsel if available] - Strategic role: defensive vs offensive - Cost of patent: [filing + prosecution + maintenance] - Competitive density: [how fast could this be replicated?] </context> <output> 1. Trade secret vs patent: is this better kept private or registered? 2. Patent's defensive value: blocking competitors. 3. Patent's offensive value: licensing or litigation revenue. 4. Cost over 20 years: filing + prosecution + maintenance globally. 5. Disclosure cost: patents publish — does that help competitors? 6. Recommendation + the territory strategy. </output>

<task>Decide whether to sponsor [conference / event].</task> <event> - Event: [name] - Audience: [size + persona match] - Cost: [sponsorship + travel + opportunity] - Past sponsorships' ROI: [if any data] - Strategic alternatives: [own event, content marketing, ads] </event> <output> 1. ICP match: how many actual buyers will be there? 2. Activation: what we'd do beyond the logo (talk, dinner, demos). 3. Pipeline math: opportunities needed to break even. 4. Brand / awareness lift if direct pipeline isn't the goal. 5. Opportunity cost: same dollars in other channels. 6. Recommendation + the activation plan if proceeding. </output>

<task>Decide whether to accept [endorsement / partnership opportunity] from a brand-risk perspective.</task> <partner> - Partner: [who] - Reach: [audience size, demographics] - Past controversies / brand baggage: [list] - Audience overlap with our ICP: [%] - Value being offered (or asked): [describe] </partner> <output> 1. Brand alignment audit: do their values match what we publicly stand for? 2. Risk register: 3-5 things that could go sideways from this association. 3. Reversibility: can we unwind if their next controversy is bad? 4. Audience reaction modeling: who'd love it, who'd be offended. 5. Contract protections: morality clause, termination rights. 6. Recommendation + the kill criteria. </output>

<task>Evaluate [co-marketing deal] with [partner].</task> <deal> - Partner: [name] - Activity: [webinar / report / event / content] - Audience overlap: [%] - Effort each side: [estimated hours] - Distribution promises: [their commitment] </deal> <output> 1. Audience match: is their audience actually our ICP, or just a big number? 2. Effort symmetry: are we doing 50% or 80% of the work? 3. Distribution discipline: will they actually push to their list? 4. Output value: what we keep after the co-marketing ends (content, leads, brand). 5. Reputational fit: do we want our brand near theirs? 6. Recommendation + the leverage we should ask for. </output>

<task>Decide whether to take [distribution deal] on offered terms.</task> <deal> - Distributor: [who] - Volume promise: [estimated] - Margin to distributor: [%] - Exclusivity terms: [any] - Term length: [years] </deal> <output> 1. Volume realism: is the promise based on data or hope? 2. Margin math: can we afford their cut and still grow? 3. Exclusivity damage: what other channels does this lock out? 4. Term length: how long are we committing? 5. Channel conflict with direct sales: where does it bite? 6. Recommendation + the negotiation moves. </output>

<task>Decide whether to start an exit process now.</task> <context> - Current state: [revenue, growth, market position] - Market for exits in our category: [hot / cool] - Founder readiness: [be honest] - Investor pressure: [if any] - Best case independent path: [3-year forecast] </context> <output> 1. Market timing: are buyers paying premium multiples for our category now? 2. Independent path: what'd we be worth in 3 years if we stayed. 3. Founder energy: do you have another 3 years of this in you? 4. Investor / cap table alignment: what does the cap table need. 5. Process: who'd lead it, what'd timeline look like. 6. Recommendation + the trigger event that'd flip the answer. </output>