A hands-on AI product course for beginners

Do more than assemble screens with AI.
Build and ship a complete product.

All 27 chapters build the same service-booking mini program. Start with screens and forms, then add APIs, a database, authentication, permissions, payments, files, servers, and monitoring. Every chapter ends with a concrete task, product deliverable, and acceptance checklist.

View the roadmap ↗ See the project
One project across 27 chapters From interface to backend Launch and ongoing maintenance included
Based on the current 27-chapter curriculum

Now learning: connect the booking flow to the backend

Chapter 7 of 27
CHAPTER 07 Load a real API from the page Replace the static service list with API data
CHAPTER 08 Save bookings to the database Design the data model and create a real order
CHAPTER 09 Login and user identity Ensure users can see only their own bookings
CHAPTER 10 Manage bookings in the back office Accept, reschedule, complete, and cancel
CHAPTER 11 Errors and edge cases Network failures, duplicate submissions, and no availability
CHAPTER 12 Run one complete acceptance pass Verify the end-to-end flow through the real user journey

Generating code with AI is not the same as building a product. The real skill is knowing what to solve, what changed, and how to prove it works.

You do not memorize programming before you begin. Each concept appears inside the product task that needs it. AI speeds up implementation, while you remain responsible for requirements, boundaries, and acceptance—and gradually build sound engineering judgment.

01 · One real project from interface to production

One service booking must connect
the interface, data, and back office.

The course project is a service-booking mini program. A customer chooses a service and time and submits a booking; the backend validates availability and saves the data; an administrator accepts, reschedules, completes, or cancels it.

Course project

For every new screen, know which API it uses and which data it stores.

The interface is only the outer layer. The course continues through API contracts, data tables, user identity, business states, and error paths so a booking truly moves from the customer side to the admin side.

Service-booking mini program Customer app → API → Database → Admin
Available this week Choose a service
Appliance cleaning
About 90 minutes
Home repair
About 60 minutes
Home cleaning
About 120 minutes
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Booking time Saturday 14:00 2 slots remaining
Confirm booking
Mini-program screens Services, dates and times, booking form, my orders User action
Business API Check availability, submit, cancel, and reschedule Rule validation
Database Users, services, time slots, bookings, and status history Persistent data
Admin console Accept, schedule, complete, refund, and handle exceptions Complete workflow
Course basis: Current booking screens, API, database, and admin workflow used across the course. Services and times are examples.
02 · 27 chapters, not 27 disconnected demos

Each stage extends the product
with another production capability.

The first six chapters build working screens and a mini program. Next come APIs, the database, and login, followed by permissions, concurrency, payments, and files. The final stages cover domains, servers, monitoring, release, and iteration.

CH 00—06

Build the product first

Learn how to work with AI and build screen structure, interaction states, forms, and mini-program foundations.

Deliverable: working booking interface
CH 07—12

Connect real data

APIs, backend, database, login, and one end-to-end acceptance pass.

Deliverable: persistent booking flow
CH 13—18

Handle business boundaries

Roles, permissions, security, concurrency, payments, refunds, and file uploads.

Deliverable: transaction-ready business system
CH 19—25

Launch and operate

Analytics, domains, servers, deployment, monitoring, releases, and iteration.

Deliverable: accessible production product
CH 26

Keep the project maintainable

Preserve decisions with Git, project documentation, and context management so future work can continue safely.

Deliverable: maintainable project assets
Every chapter ships a change

The course does not stop at explanation. Every chapter leaves a product change you can verify.

In chapter 7, the task is not merely to understand an API definition. You replace local mock services with a real endpoint and verify loading, empty, error, and retry states.

Chapter 7 · Load a real API Task, concepts, and deliverable
TASK Connect the service list to the backend Concepts: HTTP requests, JSON, async state, API contracts, and error handling. Product deliverable: show database services and handle load failures.

Acceptance checklist

1 Call the real endpoint No static service array remains in the page script.
2 Handle the three states Loading, success, and request failure each have clear feedback.
3 Compare with API data Name, price, and duration match the server response.
4 Run regression checks Service selection and the next step still work.
Course basis: Current curriculum tasks, core concepts, product deliverables, AI collaboration skills, and acceptance checklists.
03 · AI accelerates implementation; people own direction and acceptance

Give AI context and boundaries,
then assign one clear change.

The course repeatedly trains one collaboration loop: explain the current product state, goal, allowed scope, and acceptance criteria; let AI understand the code before implementation; then refine the result from actual runtime evidence.

AI collaboration task Provide context before editing

Information I give AI

Current state The service list still uses a static in-page array.
Goal Call GET /api/services and show bookable services.
Allowed scope Change only the service-list page and request module.
Acceptance criteria Loading, success, empty, failure, and retry are all verifiable.

AI's work does not end at “code generated”

01Read the existing page, request wrapper, and response shape
02State which files and UI states will change
03Implement the smallest change and run focused checks
04Diagnose real errors instead of replacing evidence with guesses
05Have a person confirm the business rule and final experience
Method basis: The task, context, boundary, implementation, and acceptance loop used throughout the course; this example comes from chapter 7.
Working with AI

AI can write quickly, but it should never have to guess what “done” means.

You learn to verify the user journey, business rules, and data boundaries. When something fails, inspect logs and actual state, then give AI better evidence instead of trying random prompt variations.

Start with one complete product and learn how to build with AI for real.

Across 27 chapters, requirements, screens, backend, data, security, payments, and launch become one practical product journey.

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