Start Here
Your on-ramp to building with AI
Get oriented: what makes something an AI product, the tools builders actually use in 2026, a working setup, and your first AI feature shipped in under half an hour.
- Lessons
- 6
- Reading time
- 54 min
- Level
- Beginner
- Free lessons
- 6
Lessons in this module
- 0.19 minFree
Welcome: What You'll Build in This Course
How 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.
- 0.210 minFree
What 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.
- 0.39 minFree
The AI Builder Stack in 2026
A 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.
- 0.49 minFree
Your Builder Setup: Node, TypeScript, and API Keys
Set 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.
- 0.59 minFree
Your First AI Feature in 20 Minutes
Hands-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.
- 0.68 minFree
Thinking Like an AI Builder
Building 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.
About this module
Building an AI app in 2026 means putting a language model inside real software: a summary above a long support thread, fields pulled out of a messy email, a search box that understands meaning, a drafted reply a person can edit before sending. Getting a model to answer a prompt takes an afternoon. Getting it to behave well on inputs you've never seen, at a cost that makes sense, inside an interface people trust, is the actual work of an AI builder.
This free module is the starting point for AI Builder Course. It's written for developers who know JavaScript or TypeScript but haven't shipped an AI feature yet, and for technical founders and product people who need to know what's possible, what it costs, and where it breaks. There's also a no-code track later in the course for people who want to build without writing an app.
You'll start by learning what a language model genuinely adds to software and where it doesn't belong, with a five-question test for judging any AI feature idea. Then you'll get a map of the AI builder stack, covering models, provider APIs, SDKs, retrieval, tools, evals, observability, and hosting, with a sensible default at every layer so you don't drown in tool choices.
Next you'll set up Node.js and a strict TypeScript project, store API keys safely, and build a playground for testing prompts. Then you'll build a working summarize endpoint, test it on deliberately messy input, and write a tiny eval. The module closes with the habits that separate AI products that work from impressive demos that don't.
Questions about Start Here
How do I start building AI apps?
Start with one narrow feature, such as summarizing text or classifying support tickets, and build it with a provider SDK and a single model call. Test it on realistic, messy inputs and read the outputs before adding more features. Frameworks and extra infrastructure can wait until you feel the problem they solve.
Do I need machine learning experience to build AI apps?
No. Most AI product work treats the model as a component you call through an API, so the core skills are software engineering, prompt and context design, testing, and product judgment. You won't need to train models or read research papers to build useful AI features.
What programming language is best for building AI apps?
TypeScript and Python are both well supported by the major model providers' official SDKs. TypeScript is a natural fit if you're building web products, especially with Next.js, while Python is common for data work and fine-tuning. This course uses TypeScript first and Python where it's the natural choice.
What is an AI product?
An AI product is software where a model handles work that's hard to write as rules, such as understanding unstructured text, making judgment calls on fuzzy categories, or generating language. The best AI products pair the model with code that handles facts, math, and business rules, plus a design that makes mistakes easy to catch.
How much does it cost to experiment with AI APIs?
Model APIs charge per token of input and output, so small experiments on short texts usually cost very little, especially on smaller, cheaper model tiers. Set a monthly spend limit in your provider's console before you start, so a bug in a loop produces an error instead of a large bill.