PROMPT
# Code Review Demo Generation Strategy for Climate Tech
## EXPERT ROLE
Act as a senior Code Review specialist. Solve the exact task. Use supplied scenario details as inputs, separate facts from assumptions, and avoid generic advice.
## INTENT
**Job:** Improve the named business/performance outcome using a measurable, testable intervention.
**Audience:** Professionals or practitioners using AI for code review tasks.
**Context:** Development environment / repository
**Success:** define 2–4 observable criteria tied to the requested outcome.
## WORKING BRIEF
Treat this as the authoritative source brief. Preserve useful specifics; do not invent facts or turn scenario values into verified claims.
> Act as Senior Code Review Strategist for Coding (experienced, scaled Climate Tech to 8-figures, experienced technology/product background, generated substantial commercial experience with this system). CONTEXT: Business: Climate Tech - $2M ARR, team 10, targeting SMB owners, stage Seed Current: CAC $115, LTV $412, churn 7%, traffic 79177/mo, conversion 2.7% Assets: Next.js codebase + Stripe Goal: book 50 demos/week in 30 days Constraint: Budget $15k/mo, no-code only Tone: friendly expert FRAMEWORK: ICE + structured 4-step. TASK: Complete Code Review system for Coding / Climate Tech. - common failure modes about code review for Climate Tech - 5 Whys root cause for book 50 demos/week - Hidden cost of failure - Contrarian insight advanced practitioner insight Variant A (Us vs Them): Subject/headline 10 options with hypothesis, preview 3, body 250 words with {{FirstName}} tags PS PPS, visual brief, CTA, send logic delay trigger segment. Include placeholder [BRAND][AUDIENCE][DATA] + filled example for Climate Tech Variant B (Social Proof Avalanche): Same structure different angle Variant C (Referral Ask): Same structure third angle Each variant must be fundamentally different not reworded OUTPUT: Markdown H2/H3 tables copy blocks ready for Notion/Google Docs/Shopify Plus, both placeholder and filled side by side No generic advice, every sentence actionable, specific numbers, decision tree If [condition] then A else B, no buzzwords without definition
## EXECUTION
Problem → Requirements → Constraints → Architecture → Implementation → Tests → Failure Handling → Verification. Complete the task in the smallest complete workflow that solves it. Make inputs, decisions and deliverables explicit. Return the requested result, not a description of the workflow.
## FAILURE PREVENTION + QA
Watch for: ambiguous requirements; edge cases missed; security/reliability gaps; untested implementation. Apply only relevant prevention rules. Verify the result against intent, audience/context, constraints and output requirements.
## ITERATION
If weak, change the single highest-impact variable, preserve what works, revise, and rerun the relevant check.
## OUTPUT CONTRACT
Return a specific, immediately usable result. Include assumptions only when material; use concrete decisions and examples where useful; omit irrelevant boilerplate. Do not merely restate this prompt.
## SPECIALIST STANDARD
Judge the result using the professional standards of **Code Review**. Replace generic quality language with observable category-specific criteria.
## MODEL-NEUTRALITY
Keep core reasoning model-agnostic unless model-specific behavior materially changes the result. When a model is specified, adapt only the relevant syntax or capability.
## DELIVERY FIT
Optimize the final artifact for **Development environment / repository** only where platform behavior changes the format, attention pattern, constraints, or delivery.
## UNIQUENESS CHECK
Before finalizing, state why this prompt is materially different from nearby prompts: different intent, strategy, use case, audience, output, or decision—not merely different wording.