Building an AI SaaS in 2026 requires answering hard questions that simple CRUD apps never faced. You must contend with inference latency, token cost volatility, hallucination liability, and platform risk from OpenAI, Google, and Anthropic.
The 15-Point Pre-Code Checklist
Pillar 1: Economic Viability
- [ ] 1. Does the customer save or make at least 5x what you charge per month?
- [ ] 2. Are your LLM token costs under 15% of your average customer monthly subscription?
- [ ] 3. Have you capped or metered heavy compute endpoints to prevent bad actors from draining your API key?
- [ ] 4. Can you charge at least $49/mo minimum to support customer acquisition?
Pillar 2: Technical Defensibility
- [ ] 5. Does the product do more than format a system prompt with user input?
- [ ] 6. Do you leverage proprietary datasets, specialized scraping, or customer private embeddings?
- [ ] 7. Does the application maintain persistent state and historical context across multiple sessions?
- [ ] 8. Would a clone built in 48 hours lack the business logic or integrations needed to function?
Pillar 3: Distribution & Retention
- [ ] 9. Do you know the exact search terms your ICP types when they need this solution?
- [ ] 10. Can users set it up in under 5 minutes without mandatory onboarding calls?
- [ ] 11. Does the product become more valuable the longer the customer uses it?
- [ ] 12. Have you pre-validated demand with at least 5 paying letters of intent?