Phase 15 — Startup Playbook
The capstone: turning the entire curriculum into a real LLM startup. Where to play (opportunity map), what to build (discovery → market → AI-native design → MVP), how to make it a business (unit economics → moat), and how to win (sales → enterprise readiness → fundraising).
Why this phase matters
The curriculum's payoff isn't engineering for its own sake — it's building a startup-grade product on top of LLM infrastructure. This phase synthesizes Phases 5–14 into product strategy. The governing truths run through every doc: the foundation-model layer commoditizes whatever sits thinly above it (00), so don't wrap a model — own a workflow, the data, and the trust around it (03); defensibility never comes from the model but from data/integration/domain/distribution moats (06); every request costs money, so margins must be engineered (05); and the two questions that decide an AI company's fate — "can OpenAI build this?" and "do the unit economics work?" — must have structural answers. It builds directly on model selection (Phase 5), serving/cost (Phase 7), gateways/routing (Phase 8), RAG (Phase 9), agents (Phase 10), evaluation (Phase 12), fine-tuning (Phase 13), and security/governance (Phase 14).
Documents
| # | Document | What you'll be able to do |
|---|---|---|
| 00 | Startup Opportunity Map | Pick a layer/category; score candidates on ten dimensions; pass "can OpenAI build this?" |
| 01 | Product Discovery | Validate a painkiller (not a vitamin) via Mom-Test interviews; trust commitments over compliments |
| 02 | Market Selection | Choose a narrow beachhead with a sharp ICP; size bottom-up; nail "why now" |
| 03 | AI-Native Product Design | Don't wrap a model — own a workflow + system-of-record; evals/cost/approval/trust/routing |
| 04 | MVP Design | Scope the smallest core-workflow slice; ship embarrassingly simple; 30/90-day plan |
| 05 | Cost Model and Unit Economics | Model cost per resolved task; engineer 70–80% margin; price to margin/value |
| 06 | Moat and Defensibility | Build data/integration/domain/distribution moats; answer "can OpenAI build this?" structurally |
| 07 | Sales Engineering | Run POC→pilot→enterprise; demos that convert; handle "just a wrapper?"; champion vs buyer |
| 08 | Enterprise Readiness | Pass the gauntlet: SOC2/DPA/SSO/RBAC, deployment models, security questionnaires |
| 09 | Fundraising and Technical Demo | Pitch the business + moat + unit economics; flawless demo; survive technical diligence |
How to work through it
Read 00 first — the strategic frame (which layer/category, scored on ten dimensions, surviving the "can OpenAI build this?" filter). 01–02 are validation: discover a real painkiller (talk to users about past behavior, trust commitments) and select a narrow beachhead market. 03–04 are what you build: AI-native design (own the workflow, not a wrapper) and the MVP (smallest core slice, shipped fast). 05–06 make it a business: unit economics (engineer the margin) and the moat (defensibility beyond the model). 07–09 are how you win: sales engineering (POC→pilot→enterprise), enterprise readiness (the procurement gauntlet), and fundraising (the business story + the demo + diligence). Every doc opens with a from-zero plain-English primer and ends with a buildable lab; together they take a chosen idea from opportunity to funded company.
Phase 15 artifacts
- A one-page opportunity map (candidates × ten dimensions) + a chosen category (00).
- A discovery report (Mom-Test interviews, painkiller verdict, commitments, go/pivot/kill) (01).
- A market-selection brief (ICP, beachhead, bottom-up TAM/SAM/SOM, why-now, competition) (02).
- An AI-native product design (owned workflow + system-of-record, evals/cost/approval/trust/routing, wrapper check) (03).
- A twelve-piece MVP spec + a shipped week-1 version + a 30/90-day plan (04).
- A unit-economics model (cost per resolved task, margin, levers, pricing, break-even) (05).
- A moat strategy (compounding moat, system-of-record ownership, "can OpenAI build this?" answer) (06).
- A sales kit (converting demo, scoped POC/pilot, wrapper answer, champion/buyer map) (07).
- An enterprise-readiness kit (deal-blocker checklist, AI-data answers, deployment models, questionnaire bank) (08).
- A fundraising kit (narrative deck, two killer-question answers, metrics sheet, demo, diligence prep) (09).
Next
→ Curriculum complete. Return to the Hub, or revisit the technical foundations in Phases 5–14 that this playbook builds on.