Product Managers

9:00 - 9:15 | Welcome & Orientation

• • Welcome & instructor introductions
• • Course overview & objectives
• • Logistics (breaks, lunch, bathrooms, WiFi)
• • Hybrid format expectations
• • In-person: Participation guidelines
• • Virtual: Camera on/off policy, chat usage
• • Icebreaker: Quick poll
• • What type of product do you manage? (B2B, B2C, Platform, Internal)
• • AI experience level (1-10)
• • One product decision you wish AI could help with

9:15 - 9:45 | What is AI?

• • What is AI, really? (demystified)
• • AI is not magic (it's pattern matching at scale)
• • AI vs ML vs LLM (hierarchy)
• • Three types of AI (overview)
• • Predictive
• • Generative
• • Agentic
• • Common misconceptions debunked
• • When AI helps your product vs. when it doesn't

9:45 - 10:15 | Predictive AI Deep Dive

• • Predictive AI explained (weather forecasting analogy)
• • How it works (simplified - no math!)
• • Real-world product examples:
• • Spotify recommendations (feature engagement)
• • Amazon "Customers also bought" (conversion optimization)
• • Stripe fraud detection (risk reduction)
• • **For YOUR work:**
• • Churn prediction (which users are about to leave?)
• • Feature adoption forecasting (will users adopt this feature?)
• • Customer segmentation (who should we target?)
• • Support ticket volume prediction (when will we need more capacity?)

10:15 - 10:45 | Generative AI Deep Dive

• • Generative AI explained (creative AI that produces new content)
• • How LLMs work (simplified)
• • Training on massive text
• • Pattern recognition
• • Next-word prediction
• • Real-world product examples:
• • Notion AI (writing and summarization)
• • Linear AI (auto-generated issue descriptions)
• • Intercom Fin (AI-powered support responses)

10:45 - 11:00 | Setup Verification & Break Prep

11:30 - 11:40 | Lab 1 Introduction

• • Lab 1 overview: "Your First AI Conversation"
• • Learning objectives:
• • Chat with an AI model
• • Write effective prompts for product work
• • Understand parameters
• • Recognize hallucinations
• • Demo: Instructor walkthrough (5 min)
• • Generate user stories from a feature brief
• • Show how prompt quality changes output quality
• • Q&A (3 min)
• • Get started!

11:40 - 12:10 | Lab 1: Your First AI Conversation

12:10 - 12:25 | Lab 1 Debrief & Discussion

12:25 - 12:55 | Agentic AI & Introduction to Agents

• • Agentic AI explained
• • Chatbot (passive) vs Agent (active)
• • Example: Search engine that gives links vs assistant that books your flight
• • Components of an agent:
• • Goal
• • Reasoning
• • Tools
• • Action
• • Result
• • Modern tooling: MCP (Model Context Protocol) for standardized tool integration

12:55 - 1:20 | Prompt Engineering Workshop

1:20 - 1:30 | Week 1 Wrap-Up & Homework

• • Recap: What we learned today
• • Three types of AI (through a product lens)
• • How to use Generative AI for PM tasks
• • Prompt engineering basics
• • Preview: Next Saturday (tease exciting content)
• • Build a product knowledge base with RAG
• • Create a feature request triage agent
• • AI-assisted sprint planning and cost analysis