← All drillsShip and Monetize an AI Agent
What you'll be able to do- ✓Package a Python AI tool into a pip-installable distribution ready for PyPI
- ✓Design a free vs Pro entitlement model and gate features by tier
- ✓Mint, validate, and revoke license keys with an online validation service
- ✓Build a single FastAPI service that serves a landing page and the license API
- ✓Integrate Stripe Checkout in test mode and mint a key from a payment webhook
- ✓Persist licenses in Cloud Firestore and deploy the storefront to Google Cloud Run
- ✓Model value-based pricing with what-if scenarios and plan a B2C and B2B go-to-market
Take any AI tool you have built and turn it into a real product — installable, deployed, and paid — the way Cursor, Tabnine, and Sentry ship developer tools.
⌁ How developer-tool companies ship and monetize — package to PyPI, run a licensing backend serverlessly, and gate paid tiers behind a license-key checkout.
Start this internshipCreate an account to unlock the 11 sections, the workbench, and AskThili.
BeginSections
1. Ship and Monetize an AI Agent
🔒 locked2. Lesson 1 - Package It
🔒 locked3. Lesson 2 - Free vs Pro
🔒 locked4. Lesson 3 - The License Key
🔒 locked5. Lesson 4 - Activate
🔒 locked6. Lesson 5 - The Storefront
🔒 locked7. Lesson 6 - Payments
🔒 locked8. Lesson 7 - Persist the Keys
🔒 locked9. Lesson 8 - Containerize
🔒 locked10. Lesson 9 - Deploy to Cloud Run
🔒 locked11. Lesson 10 - Price It & Go to Market
🔒 lockedDig deeper
🔗thilishipagent — the reference implementation you build in this course
code🔗Stripe Checkout and webhooks — Stripe docs
article🔗Deploy a container to Cloud Run — Google Cloud docs
article🔗Packaging Python projects — Python Packaging User Guide
article🔗The Strategy and Tactics of Pricing (Nagle & Müller) — value-based pricing
articlePart of these learning paths
I want to become an ML engineer who ships and operates models in production
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