Build AI features people use —
and products people pay for.
The practical course on building with LLMs. Add chat, search, extraction, and vision to real apps, make them accurate, fast, and affordable, and ship them as products.
Save $70 · One-time payment · Lifetime access · 30-day money-back guarantee
- 132
- lessons
- 15
- modules
- ~23h
- of reading
- 6
- capstone builds
Hands-on with the stack builders use
- Anthropic API
- OpenAI API
- Gemini API
- Vercel AI SDK
- Next.js
- Postgres + pgvector
- Ollama
- Stripe
Why this course
Most AI tutorials stop at the demo. This one goes to production.
A complete, ordered path that covers the parts most courses skip: AI UX, evals, unit economics, safety, operations, and pricing.
Understand the models you build on
Tokens, context, reasoning, failure modes, and how the major APIs differ — explained so you can predict what a model will do inside your product.
Build the features users expect
Streaming chat, summaries, extraction, classification, semantic search, RAG with citations, vision, and voice — with real TypeScript you can ship.
Ship products that last
Evals, cost and latency control, safety and privacy, deployment, pricing, and billing — the parts that turn a demo into a business.
Curriculum
15 modules. 132 lessons. One complete path.
Start at the beginning or jump to the module you need — every lesson stands on its own.
Start Here
Your on-ramp to building with AI
- Welcome: What You'll Build in This Course
- What Makes Something an AI Product?
- The AI Builder Stack in 2026
- + 3 more
LLM Fundamentals for Builders
What you need to know about models to build on them
- How LLMs Generate Text: A Builder's Mental Model
- Tokens, Context Windows, and What They Cost
- Anatomy of a Model API Call
- + 5 more
Prompting & Context for Apps
Prompts that hold up in production, not just in a chat window
- Prompts Are Product Code
- Writing System Prompts for Product Features
- Few-Shot Examples: Showing Instead of Telling
- + 6 more
Building Core AI Features
The everyday features users expect from modern software
- Building a Streaming Chat Feature
- Streaming End to End
- Summarization Features Users Trust
- + 7 more
Structured Outputs & Tool Use
Getting typed data out and letting models call your code
- Structured Outputs in Practice
- Designing Output Schemas with Zod and Pydantic
- Validation, Retries, and Repair
- + 5 more
Embeddings, Search & RAG
Grounding answers in your own data
- Embeddings in Practice
- Choosing a Vector Store
- Building Semantic Search into Your App
- + 9 more
Choosing, Routing & Running Models
The right model for each job — hosted, open, or local
- The Model Landscape for Builders
- Choosing a Model per Feature
- Model Routing and Cascades
- + 6 more
Multimodal AI: Vision, Audio & Images
Features that see, hear, speak, and draw
- Adding Vision to Your App
- Document Understanding: Receipts, Forms, and PDFs
- Image Generation and Editing in Products
- + 6 more
AI UX & Product Design
Interfaces people understand, trust, and keep using
- Principles of AI UX
- Beyond the Chat Box: Choosing the Right Interface
- Designing for Uncertainty and Errors
- + 6 more
Evals & Quality for AI Features
Knowing — not hoping — that your feature works
- What Quality Means for an AI Feature
- Error Analysis: Read Your Outputs First
- Building a Golden Dataset from Real Usage
- + 6 more
Cost, Latency & Scale
AI features that are fast and pay for themselves
- Understanding Your AI Bill
- Unit Economics of AI Features
- Prompt Caching in Practice
- + 6 more
Safety, Privacy & Responsible AI
Shipping AI features you can stand behind
- Risk Assessment for AI Features
- Prompt Injection in Apps: RAG, Uploads, and User Content
- Input and Output Moderation
- + 6 more
Deploying, Operating & Selling AI Products
From working feature to a product people pay for
- Architecture for AI-Powered Apps
- Deploying AI Features: Serverless, Containers, and Timeouts
- Long-Running AI Workflows
- + 7 more
No-Code & Low-Code AI Building
Build useful AI tools without writing an app
- The No-Code AI Builder Landscape
- Shareable Assistants: ChatGPT Plugins, Gems, and Claude Projects
- Prompt-to-App Builders
- + 5 more
Capstone Projects
Build complete AI products end to end
- Capstone 1: An AI Feature for a SaaS App
- Capstone 2: A RAG Knowledge Base App
- Capstone 3: A Multimodal Expense App
- + 4 more
Inside every lesson
Designed to be used, not just read.
Focused, 10-minute lessons with worked examples, before-and-after comparisons, and prompts and code you can reuse.
- Copy-ready code and prompts
- Real files and prompt templates you can copy in one click and adapt to your app.
- Code that compiles
- TypeScript first (Python where it fits), type-checked against current SDKs.
- Exercises, every time
- Apply each idea to your own work in under 30 minutes.
- Search in a keystroke
- Press ⌘K for any lesson, section, or 98-term glossary entry.
Who it's for
A path for wherever you're starting.
Developers
Add AI features to the apps you already build — and know they work before your users find out they don't.
Recommended modules
Founders & product people
Decide what to build, design AI UX people trust, and price an AI product with real margins.
Recommended modules
No-code builders
Ship useful AI tools with assistants, app builders, and automations — and know when to graduate to code.
Recommended modules
Try it free
8 complete lessons. No signup.
Read all of Module 0, the first lesson of Module 1, and the streaming chat build from Module 3 — and ship your first AI feature today.
- 0.1Welcome: What You'll Build in This CourseHow the course is organized, the two tracks (code and no-code), the running example app, and the six capstone products you'll be able to build by the end.9 min
- 0.2What Makes Something an AI Product?Where language models genuinely add value inside software — and where they don't. A practical test for spotting AI features worth building.10 min
- 0.3The AI Builder Stack in 2026A map of the layers every AI app is made of — models, provider APIs, SDKs, retrieval, evals, observability, and hosting — and the sensible default at each layer.9 min
- 0.4Your Builder Setup: Node, TypeScript, and API KeysSet up Node.js 22+, a TypeScript project, provider API keys stored safely, and a scratch playground you'll use to try every idea in the course.9 min
- 0.5Your First AI Feature in 20 MinutesHands-on: build a working "summarize this" endpoint with a real model call, test it on messy input, and see the core loop of AI feature development.9 min
- 0.6Thinking Like an AI BuilderBuilding on a probabilistic component changes how you design, test, and ship. The habits that separate AI products that work from impressive demos that don't.8 min
- 1.1How LLMs Generate Text: A Builder's Mental ModelTokens, next-token prediction, training, and instruction tuning — explained through the lens of what it means for the features you build.10 min
- 3.1Building a Streaming Chat FeatureBuild an in-app AI chat from scratch: a streaming route handler, a React client, conversation storage, and the details that make it feel polished.11 min
Launch offer · 47% off
The complete course for $79 — for the first 100 students.
Normally $149. When the 100 launch seats are gone, the price goes back up. No subscription, tiers, or upsells.
- Instant access after checkout
- Sign in anywhere with a one-click email link
- Team licenses available on request
- Secure checkout with Stripe
Complete course
Lifetime accessYou save $70. Launch price for the first 100 students only.
- All 132 lessons across 15 modules
- Hundreds of type-checked code examples
- A hands-on exercise in every lesson
- 6 complete capstone builds with code
- Progress tracking across devices
- Every future update, included
30-day money-back guarantee. If it's not for you, email us for a full refund.
Do I need to know how to code?
For most of the course, yes — basic JavaScript or TypeScript. Code is TypeScript-first, with Python where it fits. If you don't code, the Start Here module, the LLM fundamentals, the AI UX and product modules, and the entire No-Code & Low-Code module (plus a no-code capstone) are written for you, and the rest will still teach you how AI products work and what to ask of your developers.
What exactly do I get?
Lifetime access to all 132 lessons across 15 modules (about 23 hours of focused reading), type-checked TypeScript examples, reusable prompts, hands-on exercises, 6 complete capstone builds, progress tracking, and every future update to the course.
Is this a subscription?
No. It's a single one-time payment with lifetime access. No recurring charges, ever.
Is the launch price really limited?
Yes. The $79 launch price applies only to the first 100 students. The seat counter on the site is live and counts real purchases. When the seats are gone, the price goes back to $149 automatically.
Can I try it before buying?
Yes. 8 lessons are completely free, including the entire Start Here module, how LLMs generate text, and building a streaming chat feature. No account required.
Which models and tools does the course use?
Code examples default to the Anthropic API (Claude 5 models) with TypeScript, and the course also covers the OpenAI and Gemini APIs, the Vercel AI SDK, Next.js, Postgres with pgvector, open-weight models via Ollama and vLLM, and Stripe for billing. Lessons focus on principles that transfer, and show where providers differ.
Will I need to pay for AI tools too?
You'll want a small amount of API credit with at least one model provider. Most exercises use small, inexpensive calls — a few dollars covers the build exercises if you follow the cost tips we teach — and several lessons show how to run open models locally for free.
How is this different from the Agent Builder Course?
They're sister courses with no overlapping lessons. The Agent Builder Course teaches you to use and build AI agents — coding agents, the agent loop, MCP servers, multi-agent systems. The AI Builder Course teaches you to build AI features and products: chat, search, RAG, extraction, multimodal, AI UX, evals, cost, and selling what you build. Where this course touches agents, it links to the other one.
Built the way it teaches
This site and its 132 lessons were planned, written, reviewed, and shipped with AI — directed by one person who decided what to build and checked the results. Every code sample was type-checked against current SDKs.
Sister course
Want to go deep on AI agents?
This course is about building AI features and products. Our companion, the Agent Builder Course, covers coding agents, the agent loop, MCP servers, and multi-agent systems in depth.
Launch offer · 47% off · 100 seats left
Get the whole course for $79.
The launch price is only for the first 100 students. After that it goes back to $149.