6 LIVE SESSIONS ON AI PRODUCT MANAGEMENT

SESSION 1 OF 6

What is AI Product Management (And how is it different from traditional product management)

Traditional PM builds logic. AI PM builds behaviors. You're no longer defining "if X then Y." You're designing how to get the best guess at Y, and what happens when that guess is wrong. In this session, you'll learn why AI products are fundamentally probabilistic (the same input can produce different outputs every time), why your competitive advantage shifts from code to data, and how the 4 Pillars and 7 Questions Framework give you a complete operating model for any AI product decision.

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SESSION 2 OF 6

Does This Really Need AI?

The most expensive AI mistake is building AI where plain software would have worked better. Teams do it because of FOMO, stakeholder pressure, and demos that create false confidence. In this session, you'll learn a 5-Gate Decision Framework you can use in your next product review to decide "AI or not AI" before anyone writes a line of code. You'll also see the AI Cost Iceberg: why 80% of AI costs are invisible until you're already committed.

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SESSION 3 OF 6

AI Product Sense: Why 70% of the Product Has Nothing to Do With the Model

Open Perplexity. You see search queries breaking down, 15 sources with clickable citations, comparison tables, follow-up suggestions. All of that is product logic. The model does roughly 30% of the work. In this session, you'll learn to see the invisible product decisions behind every AI product you use. You'll also see why every major AI product failure (Air Canada, Chevrolet, McDonald's, Google) maps to a specific system layer that a PM could have fixed.

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SESSION 4 OF 6

What Are AI Agents (What PMs Need to Know Before Building One)

Agents are the most hyped concept in AI right now. Most explanations are either too technical or too vague. In this session, you'll learn exactly how agents work: a brain (LLM) that reasons, tools (APIs) that act, and a loop that repeats until the goal is met. You'll see a real agent architecture end to end, understand when to use agents vs. RAG vs. simple prompts, and learn the specific product decisions that separate agents that work from agents that fail.

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SESSION 5 OF 6

From PRD to Product: How to Get Build-Ready With Claude Code

PMs who ship AI products spend 70% of their time on planning and 30% watching the AI code. The biggest mistake is opening a code editor with a 2-line prompt. In this session, you'll learn the 5-file prep system (PRD, Planning, Tasks, Knowledge, Decisions) that prevents the most common vibe coding disasters. You'll also learn why thin vertical slices work and why ChatGPT's "text box and nothing else" launch beat every AI product that tried to do 5 things at once.

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SESSION 6 OF 6

The Eval Problem: Why “It Looks Good” Is Not a Test

Evals are the single most important skill in AI product management. They're also the skill most AI courses skip entirely. "I look at the output and see if it's right" is not testing. It's vibes. In this session, you'll learn how to define "good," measure it with a structured rubric, and build test cases that tell you whether your AI product actually works before you ship it to real users.

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Taught by Sid Arora

Sid built AI products at Yelp, most recently the AI API that helps users find the best local businesses through conversation. He runs the AI PM Accelerator, an 8-week live cohort where PMs design, build, and ship real AI products. 70K+ PMs follow his work on LinkedIn. This series is built from the same course material that Cohort 1 students used to ship working AI products in 8 weeks.