From Prompt to Production: a One-Day Next.js SaaS Playbook
Shipping a revenue-ready AI SaaS in 24 hours is realistic when you constrain scope and automate ruthlessly. Here's how I build a Next.js app with auth, billing, and deploy pipelines in a single day-repeatable for teams, not just weekend hackers.
Hours 1-3: Scaffold the core
- Create Next.js 14 App Router project; add TypeScript, ESLint, and Turborepo if you plan services.
- Auth: use Auth.js or Clerk; model User, Team, Subscription tables with Prisma + Postgres (Neon works nicely).
- Domains: multi-tenant via middleware reading subdomain; lock down API routes with server-side checks.
- AI runtime: start with OpenAI or Anthropic; add a thin provider interface for swap-ability.
Hours 3-5: Charge money early
Drop in a Stripe checkout integration template and wire it end to end:
- Create Products/Prices in Stripe; store price IDs in env.
- Checkout session with customer portal links; success and cancel URLs per tenant.
- Webhook handler verifying signature; update Subscription on completed checkout, trial end, cancellation.
- Use idempotency keys and handle retries; add metered usage if you bill per tokens.
Hours 5-7: Market with AI, not guesswork
Spin up a landing page builder AI to generate copy, hero art prompts, and feature blocks.
- Feed it positioning constraints, ICP pain points, and brand voice; produce A/B variants.
- Track with PostHog; ship server-side experiments; cache with ISR and purge on edits.
- Auto-generate social cards and email drafts; keep a style guide in the prompt.
Hours 7-9: CI/CD that understands prompts
Your CI/CD setup for AI-generated projects should treat prompts as code.
- Store prompts and evaluation datasets; run regression tests measuring BLEU, factuality, latency, and cost.
- GitHub Actions: preview deploy per PR, run Prisma migrate, seed a demo org, and post eval benchmarks in comments.
- Secrets via OpenID Connect + cloud vault; no long-lived keys in runners.
Hours 9-12: Production hardening
- Observability: OpenTelemetry traces around model calls; correlate with user IDs and Stripe customer IDs.
- Feature flags for risky prompts; circuit-breaker to cached answers on provider outages.
- Data controls: PII redaction, regional data routing, and signed URL uploads.
Case study: doc-to-insight SaaS
We shipped a PDF insight service in 11 hours: ingestion to S3, parsing with Unstructured, embeddings in PGVector, RAG orchestration, and a minimal chat UI. Conversion jumped after replacing vague headlines with AI-tested variants focused on "audit readiness," validated by the landing page builder AI. CAC dropped 18% within a week.
Go-live checklist
- Stripe test -> live mode switch; taxes and invoices enabled; 3D Secure tested.
- SLA page, status page, and DPA links.
- Runbook: on-call, webhook replay steps, and rollback script.
Start small, prove value, then deepen automation. With focused prompts, a Stripe checkout integration template, and disciplined CI/CD, day one can ship.
