How I'd build HotelAI
I'd build the core on Next.js for the frontend, FastAPI for the backend, Postgres for the database, Stripe for billing, and Twilio for guest messaging. Auth would be JWT-based with refresh tokens stored in Redis for session management. Email goes through Resend, housekeeping coordination lives in a simple task queue backed by Celery and Redis. I'm looking at roughly 500 hours total to get to a production-ready MVP with at least three PMS connectors (Opera, Hotelogix, Hostaway). That's ten weeks at a comfortable pace, or we compress it to six if you want to accept more technical debt on the integration layer.
Day-by-day plan
- Day 1-2: Provision multi-tenant auth schema with JWT and refresh token rotation. Set up Postgres with row-level security. Wire Stripe API keys into the environment and seed three pricing tiers. Deploy a skeletal Next.js app to Vercel.
- Day 3: Build the customer onboarding flow end-to-end: property name, email, timezone, PMS selection dropdown. Store the choice in the tenant record. Wire Stripe checkout to create a subscription on signup.
- Day 4-5: Build the core guest messaging module. Integrate Twilio for SMS and WhatsApp inbound. Create a schema for message threads, guest profiles, and message history. Wire real Twilio webhooks to a FastAPI endpoint that parses inbound messages and stores them.
- Day 6-7: Build the AI review-response feature. Fetch reviews from your first PMS connector (Opera) via API. Use Claude API to draft responses. Store drafts and final responses in Postgres. Build a simple approval UI so the hotel owner can review before sending.
- Day 8: Build the housekeeping task coordinator. Simple form to create tasks, assign to staff, track status. Real-time updates via polling. Staff marks tasks complete and hotel owner gets a summary dashboard.
- Day 9-10: PMS connector number two (Hotelogix) and number three (Hostaway). This is where most of the risk lives. Build a plugin architecture so new connectors don't break the core.
- Day 11: Testing, logging, error handling. Set up Sentry for error tracking. Add structured logging to FastAPI.
- Day 12: Deploy to production. Set up Caddy reverse proxy, SSL, rate limiting. Create a runbook for ops.
What's hard about this build
The PMS integration layer is the technical and business killer. Fifty-plus property management systems exist, each with different authentication schemes, rate limits, and data shapes. Opera uses SOAP; Hotelogix uses REST with sketchy documentation; Hostaway changes their API quarterly. Building three connectors is feasible in two days each if the APIs are cooperative. Building a tenth connector at month six when the first nine variants have taught you edge cases you didn't anticipate takes three days. The real risk is committing to unlimited PMS support in your GTM, then discovering you can only reliably support the top five. You need a queuing mechanism with retry logic and exponential backoff so hotels know why their data is stale. Without this, support tickets eat your margins.
What's fast because of AI
Claude accelerates the scaffolding phase dramatically. I use it to generate the initial schema design, the FastAPI route structure, the Next.js component tree, and the Twilio webhook parser in one session. That saves three days of boilerplate. For testing, Claude writes eighty percent of the test cases for edge cases I wouldn't have thought of first: duplicate message deduplication, timezone handling across PMS systems, retry logic for failed Stripe webhooks. I use Claude to write the review-response prompts and iterate on them with real hotel feedback. On copywriting, Claude drafts the onboarding UI copy, the email templates, and the in-app guidance. That's normally a day of work; Claude compresses it to two hours of review and refinement. When Twilio webhooks fail silently, Claude helps me enumerate the possible failure modes and build instrumentation to narrow them down.
How I'd hand it off
I'd record a Loom walkthrough of the admin panel, the onboarding flow, and the Stripe billing setup. I'd write a runbook in Linear covering environment setup, deployment, secrets management, how to add a new PMS connector, and the status dashboard. I'd do a thirty-day pager rotation where you call me for critical issues: failed Stripe charges, broken PMS syncs, Twilio outages. All credentials get transferred to your account. I'd leave the codebase in a state where a junior engineer can pick up new PMS connectors. Deploy pipeline is automated via GitHub Actions.