AGENTIC AI FOR PRODUCT MANAGERS

Make better
decisions about
AI agents.

Learn how agents work, test their quality, estimate their costs, and plan a product that uses them.

18 self-paced modules · No coding required · No course fee

AN AGENT, MADE VISIBLEIllustrative example
01 / REQUEST

“Prepare a customer refund.”

02 / MODEL DECISION

Check the order and refund policy.

Order lookupPolicy lookup
03 / HUMAN CHECK

A person approves before money moves.

A checkpoint adds time and gives a person the final decision.

Same request. A different product decision.

FROM CURIOSITY TO PRODUCT JUDGEMENT

Go beyond the demo.

01

Find the right opportunity

Decide where an agent helps, where a simpler workflow fits, and what success means.

02

Test what actually works

Inspect failures, build an evaluation plan, and choose evidence over a convincing answer.

03

Make trade-offs visible

Estimate total cost, choose safeguards, and explain your product decisions.

04

Build a portfolio

Turn each module into a practical brief, test plan, policy, or product specification.

A REAL TASTE OF THE COURSE

Start anywhere.
See how you learn.

Three selected lessons. No account needed.
Watch, read, and explore at your own pace.

THE COMPLETE PATH

Build understanding.
Then build your case.

Follow the sequence, revisit a difficult idea, or practise what you need. Your free account keeps your place.

Explore the full course ↗
STARTChoose Your Course Project

See how the course works, then choose a product to practise on.

01Language Models, Tokens & Prompts

See how a language model uses small pieces of text called tokens to answer your instructions.

02APIs, JSON & Workflows

Read the messages and steps that let software systems work together.

03AI Agents & Multi-Step Reliability

Understand agents that choose actions and why errors add up across steps.

04Context Limits & Model Sampling

Understand what a model can use at once and how it chooses between possible answers.

05Retrieval-Augmented Generation (RAG)

Find relevant information and give it to the model before it answers.

06The Agent Loop

Follow the cycle of choosing an action, using a tool, checking the result, and stopping.

07Tools, Context Engineering & MCP

Describe tools and connect them through Model Context Protocol, a shared connection format.

08Multi-Agent Coordination

Decide when several agents should work together and how to divide their work.

09Agent Memory & State

Decide what an agent should remember and how to track unfinished work.

10Agent Evaluation

Build tests that show whether an agent does the job well enough.

11Agent User Experience & Trust

Design what people see, approve, and control when an agent acts.

12Agent Reliability & Security

Find failures, limit damage, and protect tools and information.

13Agent Costs & Model Selection

Estimate the cost of a completed task and choose models that fit the job.

14Agent Product Requirements

Write the goals, limits, and evidence needed to build your agent product.

15Agent Pricing & Go-to-Market

Choose who the product serves, how to charge, and how to reach customers.

16Agent Development & Team Roles

Plan how a product team builds, tests, releases, and maintains an agent.

17Building & Testing Your Agent

Build one bounded workflow, measure its results, and improve one important failure.

18Agent Readiness & Portfolio

Review your evidence, decide what is ready, and keep a useful record of your work.

ON YOUR TERMS

A course that fits around your work.

01

Try it

Explore the public samples before joining.

02

Join free

Create an account to access the entire course.

03

Learn and practise

Read or watch, make predictions, and try the simulations.

04

Keep your place

Save progress across devices and revisit due review cards.

YOUR COURSE AUTHOR

Created by
Vaibhav Saraf.

A practical course for product managers who want to understand, evaluate, and plan products built with AI agents. No coding background required.

BEFORE YOU BEGIN

A few useful answers.

Is the course really free?

Yes. There is no course fee. Some optional external tools may have their own charges; you can decide whether to use them.

Do I need to know how to code?

No. The course uses explanations, browser simulations, practical decisions, and workflow tools.

How long do I have to complete it?

It is self-paced. The 18 modules describe the learning sequence, not a deadline.

Why create an account?

An account unlocks the full course and saves your learning progress across devices. The three public samples work without one.

Are the videos private?

The videos are Unlisted on YouTube. Anyone who receives a video link can play it. Your account protects the course pages and your saved progress.

YOUR NEXT PRODUCT DECISION STARTS HERE

Understand the agent.
Own the decision.

Join the course free ↗

No course fee. No coding required.