How I'd build Church AI
I'd reach for Next.js on the frontend, FastAPI for the backend API, Postgres for the database, and Stripe for billing. On the communications side, Resend for email, Twilio for SMS reminders, and a document template engine built in-house using Handlebars. I'm estimating 70-80 hours total to get this to production, which puts the engineering cost around $5,250-6,000 at $75/hr.
Day-by-day plan
- Days 1-2: Provision multi-tenant auth schema and row-level security policies in Postgres. Set up NextAuth for SSO-ready login; establish church-as-tenant isolation boundaries.
- Day 3: Wire Stripe billing. Three tiers: Starter ($99/mo, 50 emails/month), Plus ($199/mo, 500 emails), Pro ($399/mo, unlimited). Implement webhook handlers for subscription state and usage tracking.
- Days 4-5: Build the customer onboarding flow. Church name, pastor email, member list import (CSV plus Planning Center API integration for direct data fetch). Validate email domain to prevent impersonation.
- Day 6: Scaffold the bulletin draft engine. Admin fills form with date, key announcements, giving goal, upcoming events. Claude API generates 2-3 draft bulletins in their church's voice. Export to PDF or send direct.
- Day 7: Build visitor follow-up automation. Simple rules: "If new email added, send welcome after 3 days, connect to volunteer mentor after 1 week." Resend handles delivery; Postgres cron jobs trigger at intervals.
- Day 8: Event announcement system. Admins create event, pick audience (all members, age group, giving history tier - voluntary and consent-based), schedule send time across time zones.
- Day 9: Admin dashboard. View sent communications, open rates via email provider webhooks, member list, template library, billing page. Role-based access for pastor vs. office manager.
- Day 10: Load test and security review. Multi-tenant isolation stress test, CCPA/GDPR consent audit, rate limit all API endpoints, Sentry error monitoring.
- Days 11-12: Polish UI bugs, add CSV export for member lists (auditable), finalize Loom docs, deploy to production.
What's hard about this build
The core technical risk is multi-tenant data isolation. A bug that leaks one church's member emails or giving history to another church is catastrophic and destroys trust instantly. Every query, permission check, and API endpoint must verify tenant ID. The second risk is congregation member data sensitivity. Pastors are understandably protective of their flock's contact information and giving behavior. I'd mitigate by offering optional data encryption at rest, explicit audit logs, and a no-sharing pledge in the ToS. The third gotcha is integration with existing church management systems. Planning Center, ChurchSoft, and Breeze all have different APIs. I'd start by supporting CSV import and Planning Center's API, then add others on demand. Finally, compliance. If you're processing US member data, CCPA applies in California; if international, GDPR kicks in. I'd build consent flags into the model from day one rather than bolting them on later.
What's fast because of AI
Claude accelerates the scaffolding of multi-tenant models and permission tests significantly. Instead of writing boilerplate auth middleware by hand, I'd generate templates, review them, then customize. For the bulletin-drafting engine, Claude itself is the product - LLM prompts trained on the church's past bulletins and tone. AI also speeds up copy generation for UI: form labels, error messages, empty states, and email templates. For edge cases, I'd use Claude to enumerate them (what happens when a church deletes its member list mid-send? What if someone changes their phone number?), then build tests around those scenarios. Finally, debugging. When a multi-tenant query returns the wrong data, Claude helps me reason through the permission logic and spot the bug in minutes instead of hours.
How I'd hand it off
I'd record a Loom walk-through of the entire admin interface and API, covering the most common flows: onboard a church, send a bulletin, view open rates. I'd leave a runbook in GitHub documenting the deployment pipeline, environment variables, Stripe test/live key rotation, and how to monitor Postgres row-level security violations. I'd stay on pager for 30 days post-launch, fixing any data isolation or billing bugs within 2 hours. All secrets, Stripe credentials, and GitHub credentials transfer to your AWS account before I hand off.