AI Product Builders Course
Go from idea to launched AI product: scoping, picking models, evaluating quality, and managing cost.
25 lessons · about 6 hours of reading · Free
Start lesson 1Course syllabus25 Lessons
The AI Product-Building Loop: From Idea to Improvement
Learn the five stages of building a product with AI, what each stage is for, and how to make a first useful lap without building too much.
Define the Problem Before You Choose a Solution
Turn an app idea into a clear problem brief by naming the people, situation, task, evidence, and unanswered questions.
Check the Idea Before You Build
Plan a small round of user research, learn from recent behavior, review alternatives, and decide what evidence should change your next step.
App Anatomy for Non-Engineers: What Happens Behind a Screen
Follow a click through the browser, server, database, accounts, files, outside services, and hosting that make a digital product work.
Scope the First Version: Choose What to Build Now
Choose one user job, sort features into must, should, and later, and write a scope that is small enough to build and useful enough to learn from.
Choose a Tech Stack That Fits Your Constraints
Start with your team, users, data, time, and budget, then choose a stack you can build, operate, and change with confidence.
Choose a Prototype Tool for Your Product and Team
Compare visual design tools, AI app builders, and coding agents by the kind of prototype you need, your team’s control, and the handoff you expect.
Build a Clickable Prototype in One Focused Flow
Turn a scoped user job into three connected screens, use clearly fictional sample data, and stop when the prototype is ready to test.
Test a Prototype with Real People
Give people a task, watch how they use your prototype, and turn careful notes into a short list of problems to address.
Decide Whether to Keep, Change, or Stop
Turn prototype test findings into a clear next step without bending the evidence around the work you have already done.
Move from a Prototype to Real Code
Decide whether to stay in your builder, export the project, or rebuild from the product decisions you have already made.
Work with an AI Coding Tool on One Clear Task
Turn a product decision into a small coding task, give the agent useful project context, and review its work before moving on.
Learn the Web Basics Behind Your App
Recognize what HTML, CSS, JavaScript, React, and Node.js do, then use browser DevTools to gather clues when a screen behaves unexpectedly.
Connect a Database Without Losing Control of Your Data
Choose a simple data model, understand how an app connects to a database, and check access, secrets, and backups before real data is involved.
Tell a Small Fix from a Structural Change
Classify a change by its reach and risk, ask an AI tool to map its impact, and choose a review path that fits the work.
Run a Refinement Loop That Keeps the Product Useful
Turn user and product signals into one focused improvement, check what changed, and keep a useful record without polishing forever.
Make an AI-Built Product Easier to Use
Review a core user journey for clear wording, mobile layouts, keyboard access, readable contrast, helpful states, and common accessibility gaps.
Review and Check Changes Before They Reach the Team
Use branches, pull requests, human review, continuous integration, and a protected main branch to coordinate changes safely.
Test an AI-Built Product in Layers
Match unit, integration, end-to-end, and user tests to the risks in a product feature.
Work with a Team and Stakeholders
Keep product decisions, AI-assisted work, handoffs, and approvals clear across a small team.
Choose Where to Deploy Your Product
Compare cloud, serverless, and platform-as-a-service hosting by control, operating work, cost shape, region, and portability.
Go Live: A Launch Checklist for Your Product
Prepare the domain, secrets, data, recovery, and support before inviting people to use the product.
Measure and Improve Your Product After Launch
Choose a few useful measures, listen to users, understand operating costs, and turn evidence into the next product decision.
Add an AI Feature to Your Product Carefully
Decide whether a product problem needs AI, design a bounded first feature, evaluate it with realistic examples, and give people a clear fallback.
Capstone: Take a Product Idea to Launch
Bring the product cycle together in one practical lap, from a testable problem to a launch decision and a plan for what comes next.
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Frequently asked questions
Who is the AI Product Builders course for?
Founders, designers, product managers, analysts, students and developers who want to take an idea to a live product with AI tools.
What do I need before starting the AI Product Builders course?
None. Programming experience helps but is not required.
What will I learn in the AI Product Builders course?
You will take an idea from a problem worth solving through testing with real people to a launched product.
How long does the AI Product Builders course take?
It has 25 lessons and about 6 hours of reading, before you spend time on the practice tasks. Go at your own pace; the lessons are written to be done in order.
Is the AI Product Builders course free?
Yes. Every lesson is free to read, and you do not need to sign in.