Agentic AI and MCP for Product Managers

What 'Agentic' Actually Means

The Autonomy Ladder

Why Most Things Called Agents Aren't

What This Course Covers

The Loop

Tools Are the Interesting Part

What the Agent Remembers

Stopping Conditions

Copy This Prompt - Mapping Your Agent's Loop

Exercise - Trace Your Own Agent

The Problem MCP Solves

Servers and Clients

The Three Things a Server Offers

What MCP Gives You and What It Doesn't

Copy This Prompt: Working Out What You'd Connect To

Exercise: Map Your Connections

Why Tool Design Is Product Design

Names and Descriptions

Granularity

What a Tool Returns When It Fails

Copy This Prompt - Designing Your Tool Inventory

Exercise - Write Your Tool Inventory

Three Categories, Not Five

Where the Approval Goes

Approval Fatigue

Designing the Approval Moment

Copy This Prompt - Designing Your Permission Model

Exercise - Build Your Permission Model

Why the Final Answer Isn't Enough

Trajectory Evaluation, Plainly

A Test Set of Tasks, Not Questions

The Four Things to Measure

Copy This Prompt - Building an Agent Test Set

Exercise - Build and Run an Agent Eval

Why Cost Per Task Has a Long Tail

Where the Seconds Go

Loops, Retries and Runaways

Budgets and What Happens at the Limit

Copy This Prompt - Modelling Agent Cost

Exercise - Model Your Costs and Set Your Caps

The Waiting Problem

Showing Work Without Showing Everything

Interruption, Correction and Undo

Building Trust One Delegation at a Time

Copy This Prompt - Designing the Agent Experience

Exercise - Design the Experience

The Blast Radius Question

Prompt Injection When the Agent Can Act

Compounding Errors

Rehearse the Incident

Exercise - Work Out Your Blast Radius

Five Situations Where a Workflow Wins

Agent, Workflow, or Just a Button

What Agents Structurally Struggle With

Reducing Autonomy Instead of Adding Capability

Copy This Prompt - Checking Whether You Need an Agent

Exercise - Check Your Own Choice

Lesson FP.1: What You're Producing

Prompt Library: Understanding the Task

Prompt Library: Designing Tools

Prompt Library: Permissions

Prompt Library: Evaluating

Prompt Library: Cost and Caps

Prompt Library: Experience and Risk

Prompt Library: Checking Yourself

Words Explained: Glossary

Lesson 7

Prompt Library: Checking Yourself

Do You Actually Need an Agent?

Help me work out whether an agent is right, or whether something simpler is better. THE TASK:

[description]. HOW A HUMAN DOES IT TODAY: [walk through]. DOES THE PATH VARY: [how much].

ACTIONS INVOLVED: [read, write, irreversible]. CONSEQUENCE OF A WRONG ACTION: [honestly]. CAN

WE CAPTURE FULL TRACES: [yes/no/don't know]. Tell me directly: is this a button, a workflow,

or an agent, pick one, don't hedge. If an agent, what's the lowest autonomy level that still

delivers most of the value? Is there a version where a workflow handles 80% of cases and an

agent only the awkward ones? What would have to be true for an agent to be clearly right, and

is it true here? And if we built it and it underperformed, what's the most likely reason?

Don't be encouraging.

Agentic AI and MCP for Product Managers

Module 1What 'Agentic' Actually Means

Module 2How an Agent Actually Works

Module 3MCP: What It Is and Why You Should Care

Module 4Designing the Tool Layer

Module 5Permissions and the Human in the Loop

Module 6Evaluating Agents

Module 7Cost, Latency and Unpredictability

Module 8Designing What the User Sees

Module 9Risk and Blast Radius

Module 10When an Agent Is the Wrong Answer

Module 11Final Project: Design One Real Agent End to End

Module 12Appendix: The Prompt Library

Prompt Library: Checking Yourself