How I'd build Webinar AI
I'd reach for Next.js with Postgres and Stripe as the spine, Claude API for the AI layer, Mux for video handling, and Resend for transactional emails. Deployment on Vercel with Railway for the database and background jobs. Rough estimate is 300-350 hours of development, which puts us at 4-5 weeks working full-time.
Day-by-day plan
- Days 1-2: Provision Postgres schema for tenants, users, subscriptions, and webinar artifacts. Set up NextAuth.js for email-based auth with role-based access control per tenant.
- Days 3-4: Integrate Stripe across the three pricing tiers. Build the subscription state machine (trial, active, churned, past-due). Wire up invoice webhooks for usage tracking.
- Days 5-6: Build the video upload form and S3 integration. Configure signed URLs for secure uploads and set up Mux for reliable video ingestion and thumbnail generation.
- Days 7-9: Integrate the Claude API to transcribe uploaded webinars, extract key moments, generate follow-up talking points, and surface recommended CTAs. Cache prompts where possible to reduce token spend.
- Days 10-12: Build the customer dashboard showing webinar performance metrics, conversion lift estimates, and a library of past analyses. Add CSV export for reporting.
- Days 13-14: Wire up Resend for welcome emails, billing receipts, and usage notifications. Add background job processing via pg_boss for async transcription work.
- Days 15-16: Write integration tests covering the subscription lifecycle, video upload flow, and API calls. Deploy to Vercel with environment-based configuration. Set up Sentry for error tracking.
- Days 17-18: Build the onboarding flow guiding customers through their first webinar upload, showing ROI methodology, and collecting feedback. Document the API for future integrations.
What's hard about this build
The trickiest part is getting the conversion-rate attribution right. Customers need to feel the AI actually moved the needle on post-webinar sign-ups, but webinar usage is spiky and contextual - a great product alone doesn't guarantee they'll see a measurable lift if their webinar strategy was already broken. That's a product trust problem, not a technical one, but it affects retention hard. Technically, video processing is IO-heavy and can bog down your backend if you're not careful about job queuing and timeouts. Mux handles some of this, but you'll still need to monitor for stuck jobs. Stripe webhook delivery is reliable but not instant, so there's a window where subscription state can diverge from the source of truth if you're not idempotent about it. Finally, multi-tenant isolation has to be bulletproof - a query bug that leaks one customer's webinar data to another tanks trust immediately.
What's fast because of AI
AI compresses the scaffold-to-working-API loop dramatically. Using Claude to scaffold the Postgres schema, generate initial NextAuth middleware, and produce a working Stripe webhook handler saves a week of boilerplate. Claude generates test cases I might have missed - edge cases like what happens when a video upload stalls mid-process or a customer hits their transcription quota mid-month. Copywriting for the dashboard, onboarding screens, and email templates gets drafted in minutes instead of days. Debugging is faster too: I can describe an error state to Claude, get back three hypotheses ranked by likelihood, and zero in on the real cause instead of spinning through hypotheticals. The biggest win is velocity on the initial build - what would have been a 6-week project alone becomes a 4-week one with focused review cycles.
How I'd hand it off
I'd record a 20-minute Loom walkthrough of the entire deploy pipeline, the Stripe test flow, and how to add a new customer manually if needed. You get a runbook documenting daily operational checks: Sentry alerts to watch, Stripe webhook logs to monitor, and the pg_boss job queue health. I'll set up a 30-day pager rotation if you want me on-call, or transition you to your own ops person with a week of overlapping shifts. All credentials go into your password manager, source code lives in GitHub with CI/CD configured, and we document any vendor API contracts so the next engineer can renew them. Final 90 minutes is a handoff call with your technical co-founder covering questions and edge cases I haven't documented.