Coding

Code Review MRR Growth Strategy for Coffee Subscription

PROMPT

# Code Review MRR Growth Strategy for Coffee Subscription

## 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 Coffee Subscription to 8-figures, experienced technology/product background, generated substantial commercial experience with this system). CONTEXT: Business: Coffee Subscription - $12M ARR, team 39, targeting SMB owners, stage Seed Current: CAC $168, LTV $1973, churn 12%, traffic 31649/mo, conversion 5.2% Assets: Shopify 120 SKUs Goal: scale MRR $50k to $200k in 30 days Constraint: Budget $8k/mo, GDPR required Tone: scientific McKinsey FRAMEWORK: StoryBrand + structured 4-step. TASK: Complete Code Review system for Coding / Coffee Subscription. - common failure modes about code review for Coffee Subscription - 5 Whys root cause for scale MRR $50k to $200k - Hidden cost of failure - Contrarian insight advanced practitioner insight Variant A (PAS): 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 Coffee Subscription 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/Linear+Slack, 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 β†’ Requirements β†’ Constraints β†’ Architecture β†’ Implementation β†’ Tests β†’ Failure Handling β†’ 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 decisionβ€”not merely different wording.