BeginnerProduct Managers

AI Product Management Fundamentals

Start here if you are new to AI product management. You will learn the core vocabulary, understand how AI products differ from traditional software, assess your organization's readiness, and start thinking about when AI is (and isn't) the right solution.

4 modules20 steps~4 hours
0% complete0/20 steps
Path Progress: 0% (0/20 steps)
Module 1: AI Vocabulary for PMs0/8
Module 2: How AI Products Are Different0/5
Module 3: Assess Your AI Readiness0/5
Module 4: When AI Is the Right Solution0/5

After completing this path, you will be able to:

  • Explain core AI/ML concepts (LLMs, RAG, hallucinations, prompt engineering) to stakeholders
  • Describe how the AI product lifecycle differs from traditional software
  • Assess whether your team and organization are ready for AI
  • Identify product problems where AI adds genuine value vs. hype

Learning Objectives

  • Define LLMs, RAG, hallucinations, and prompt engineering in plain language
  • Understand guardrails, RLHF, and chain-of-thought reasoning
  • Know the difference between agentic AI and traditional AI features
📖
Large Language Models (LLMs)
5m
📖
Hallucinations
5m
📖
Retrieval-Augmented Generation (RAG)
5m
📖
Prompt Engineering
5m
📖
Guardrails
5m
📖
Agentic AI
5m
✏️
15m
🏁
5m

Learning Objectives

  • Map the AI product lifecycle and compare it to traditional development
  • Identify the unique challenges: non-deterministic outputs, data dependencies, evaluation
  • Understand why AI products fail at higher rates and how to avoid common pitfalls
📖
AI Product Lifecycle Framework
12m
📖
Why AI Products Fail
10m
📖
How AI Is Changing Product Management
10m
✏️
8m
🏁
5m

Learning Objectives

  • Run an AI readiness assessment on your organization
  • Identify skill gaps and how to close them
  • Evaluate the AI risk profile of potential projects
🧮
AI Readiness Assessment
10m
🧮
AI PM Skills Gap Analyzer
10m
📖
AI Risk Assessment Framework
10m
✏️
10m
🏁
5m

Learning Objectives

  • Apply a decision framework for whether to use AI
  • Distinguish between LLM, ML, and rules-based approaches
  • Evaluate AI build vs. buy trade-offs
📖
When to Add AI to Your Product
10m
🧮
LLM vs ML vs Rules Tool
8m
📖
AI Build vs Buy Framework
10m
🧮
AI Build vs Buy Analyzer
7m
🏁
5m