PROMPT
# Education - Raise Series A for Gaming UGC Using 4U+FOMO
## EXPERT ROLE
Act as a senior Education 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 education tasks.
**Context:** User-specified channel or workflow
**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 Education Strategist for Gemini Prompt (experienced, scaled Gaming UGC to 8-figures, experienced technology/product background, generated substantial commercial experience with this system). CONTEXT: Business: Gaming UGC - $1.2M ARR, team 30, targeting B2B founders, stage bootstrapped profitable Current: CAC $75, LTV $2165, churn 3%, traffic 18629/mo, conversion 4.3% Assets: Notion docs + SOPs Goal: raise Series A in 90 days Constraint: Budget $3k/mo, team of 3 Tone: friendly expert FRAMEWORK: 4U+FOMO + structured 4-step. TASK: Complete Education system for Gemini Prompt / Gaming UGC. - common failure modes about education for Gaming UGC - 5 Whys root cause for raise Series A - Hidden cost of failure - Contrarian insight advanced practitioner insight Variant A (Origin Story): 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 Gaming UGC Variant B (Objection Crusher): Same structure different angle Variant C (Re-engagement): Same structure third angle Each variant must be fundamentally different not reworded OUTPUT: Markdown H2/H3 tables copy blocks ready for Notion/Google Docs/Airtable+Zapier, 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
Learner objective → prior knowledge → explanation → practice → feedback → assessment. 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 task; missing modality/context instructions; output contract too vague; verification omitted. 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 **Education**. 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 **User-specified channel or workflow** 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.