How I'd build Music Production AI
I'd reach for Next.js with Postgres, Stripe for billing, and Resend for transactional email. The backend would be a lightweight Node server handling webhooks and scheduled jobs via bull-mq. I'm estimating 250-300 hours for a launch-ready MVP, which puts us at around $18,000-22,500 in labor alone plus about $200-300 in infrastructure and third-party fees for the first month.
Day-by-day plan
Day 1: Provision Postgres schema for multi-tenant architecture, including accounts, users, roles, and workspaces. Auth via NextAuth with OAuth fallback to email magic links.
Day 2: Wire Stripe integration: create product SKUs for three tiers, webhook handlers for subscription events, and idempotent billing logic that handles downgrade mid-cycle.
Day 3-4: Build customer onboarding flow, including workspace setup, team member invites, and integration handshakes with Calendly (OAuth) and Stripe Connect for indie payment processing.
Day 5: Implement the studio dashboard: session logging, revenue tracking by client and project, and a read-only calendar view synced from Calendly.
Day 6-7: Smart scheduling engine. I'd use a rules-based conflict checker (producers care about overlapping session times, gear conflicts, and engineer availability) and a basic scheduling recommendation layer based on historical booking patterns.
Day 8: Auto-invoicing: template system, PDF generation via Puppeteer, Resend email delivery, and archive versioning.
Day 9-10: Testing, performance profiling, and Sentry integration for error tracking in production.
What's hard about this build
The hardest part is the Calendly sync. Their API returns events but doesn't expose granular permissions around shared calendars, so detecting when two producers are double-booked requires polling and soft-conflict detection rather than atomic truth. We'd need to handle rate limits and stale data gracefully. Second, music producer income is seasonal and highly irregular, which means churn spikes during slow months. I'd need to instrument retention metrics early and be ready to add dunning or downgrade-to-free flows within the first month. Third, the AI angle is thin without a real value prop. Smart scheduling alone isn't enough. We'd need to measure actual time saved and bake that into onboarding messaging from day one, or risk producers dismissing it as a feature, not a product. Finally, producer communities are skeptical of SaaS. We'd need to validate product-market fit via Beta with 10-15 real studios before paid launch, which could extend timeline by 2-3 weeks.
What's fast because of AI
AI compresses scaffold generation and test writing. I'd use Claude to generate Zod schemas from Stripe webhook payloads and to write integration tests for the billing system, which usually takes a week of careful thinking. Copywriting for onboarding flows and email templates runs 10x faster with Claude iterating on tone. Edge-case enumeration for the scheduling conflict detector is something I'd heavily lean on Claude for: what happens if a client books twice, if a session extends past midnight, if a producer cancels and re-books the same slot. Debugging production errors is faster too. Claude can read Sentry stack traces and suggest root causes alongside code fixes. The real win is time-to-insight on observability. Instead of spending two days building dashboards, Claude can suggest key metrics and help scaffold the instrumentation upfront.
How I'd hand it off
I'd record a 10-minute Loom walking through the codebase structure, the Stripe webhook flow, and how to add a new feature. I'd write a runbook covering deployment, emergency rollback, and how to handle common producer-support escalations. For 30 days post-launch, I'd do a Monday oncall rotation via Slack, responding to production incidents and helping the team interpret metrics. I'd transfer all third-party credentials (Stripe, Calendly, Postgres, etc.) to a shared vault and document the deploy process for both backend and frontend. Most important: I'd leave behind a test suite that covers the critical path (signup, subscribe, create session, invoice) so the next operator can iterate safely.