How I'd build Threshold
I'd reach for Next.js on the frontend, FastAPI as the backend, Postgres for the database, and Claude API as the adaptive question engine. Stripe for billing, Resend for email delivery, Auth0 for user management. Roughly 320 hours of work, maybe 6 weeks at full-time velocity. That's the honest math here.
Day-by-day plan
Days 1-2: Multi-tenant database schema, user authentication flow, Stripe customer records tied to workspace accounts. Auth0 integration for sign-up and login.
Days 2-3: Stripe billing setup. Wire the three pricing tiers ($89/$129/$149) into the checkout flow. Subscription lifecycle management. Webhook handlers for upgrades and cancellations.
Days 3-4: Build the intake form builder. JSON schema for question templates. Client-side form rendering in Next.js with branching logic. Save draft responses to Postgres.
Days 4-5: Claude API integration. System prompt for the adaptive question generator. Call Claude after each answer to generate the next question based on what you've learned so far. Cache responses to reduce token spend.
Day 5-6: Build the brief generation pipeline. Parse the full intake conversation, feed it to Claude with a structured prompt, output a Markdown brief. Email the brief to the customer's account owner when complete.
Day 6-7: Admin dashboard. Customer list, intake submission history, revenue metrics, completion-rate tracking by question count. This is where you spot the death spiral early.
Day 7: Load test the intake form, set up observability (Sentry for errors, PostHog for funnels), deploy to Vercel and Railway. Security audit around Postgres encryption and API keys in .env.
What's hard about this build
The completion-rate death spiral is real. You'll need to instrument funnel analytics from day one to watch where people bail. Is it question three? Question seven? If drop-off spikes beyond five or six questions, your core promise collapses. You'll also need to guard against garbage-in, garbage-out: if the Claude prompt is weak, the generated questions feel generic and users abandon. Multi-tenant isolation in Postgres has to be airtight, especially when handling sensitive client intake data. And you're competing against entrenched platforms like Typeform and HoneyBook that have distribution and feature parity. The differentiation is the adaptive AI layer, but that's replicable in weeks once Typeform ships the same thing.
What's fast because of AI
I use Claude to scaffold the entire Next.js component structure for the intake form and dashboard. Instead of typing 200 lines of form boilerplate, I describe the schema and get 80% of the component in two minutes. Same with FastAPI route handlers. I generate test cases by feeding Claude the spec. The big one is the Claude system prompt itself: I iterate on five different approaches in parallel using Claude's API, test each against sample customer data, and converge on the one that produces the fewest abandoned intakes. Debugging integration issues gets faster too: I paste the error, the relevant code, and Claude suggests the fix before I'm done reading the stack trace. Documentation and runbook generation happen in a single pass instead of being an afterthought.
How I'd hand it off
I'd leave you a Loom walkthrough covering the admin dashboard, the intake flow, and the Stripe billing workflow. A runbook in Markdown: how to deploy, how to handle common errors, how to read the Postgres logs if something breaks. First-week 30-day pager rotation where you're on call and I'm available for questions. All credentials transferred: Stripe API keys, Claude API key rotation schedule, Auth0 tenant credentials. I'd leave the codebase documented with comments around the Claude integration and multi-tenant query patterns since those are the fiddly bits that always trip people up later.