A generative AI developer shipping a SaaS MVP needs a checklist more than a research paper. GenAI features fail from weak constraints and missing review, not from lack of model novelty.
MVP GenAI checklist
- One user job (draft, summarize, rewrite), not ten
- System prompt with brand and policy constraints
- Structured output when fields must feed the product
- Human review before publish/send
- 20 to 50 golden examples before coding polish
- Token budget and model tier chosen on purpose
- Feature flag and rollback plan
- Logging that avoids secret and PII leakage
What to skip in v1
Multi-agent swarms. Fine-tuning. Custom vector infrastructure if five documents can live in Postgres. Perfect brand voice automation without human taste checks.
Success metrics
Acceptance rate of drafts, edit distance, time saved, cost per successful action, and support tickets caused by bad AI output.
Summary
GenAI MVPs win with constraints, review, and measurement. Clever prompts alone are not a product.
Related: Generative AI Development, AI MVP Development, Hire AI Developer.
Prakash Tank
Full-Stack Architect & Tech Enthusiast. Passionate about building scalable applications and sharing knowledge with the community.
