AI Product Management
The complete playbook for AI Product Managers in 2026: from foundational LLM concepts, RAG, prompting, and evals to AI roadmapping, AI customer intelligence, agent architectures, and the new craft of vibe coding & vibe experimentation. Everything you need whether you're transitioning into AI PM or scaling an AI product from prototype to production.
- ✓Speak the language: LLMs, RAG, fine-tuning, agents, MCP, evals, prompting — and know which to reach for
- ✓Build an AI roadmap that ships value, not demos — with the right metrics and observability
- ✓Run the AI PM craft: prompt design, eval suites, LLM judges, vibe coding prototypes, agent monitoring
- ✓Land a $300K+ AI PM role — resume, portfolio, and interview prep tuned to 2026 hiring
- Skim the full concept list below — it's a curated progression, not a random pile.
- Pick any concept that's relevant to what you're working on right now and read it end-to-end (5-15 min each).
- Don't skip the interview questions at the bottom — they double as the best self-test.
- Follow the related concepts links to build the mental graph.
Curriculum (20)
🧠Everything You Need to Know about AI (for PMs)
The foundational vocabulary and mental model. If you can speak fluently about LLMs, RAG, agents, evals, and the cost stack, you're already ahead of 80% of PMs.
🚪How to Become an AI PM
From regular PM (or no PM experience) to AI PM. The fastest growing PM specialization of the 2020s.
🎯Your AI Product Strategy
How to think about adding AI to your product without falling into the 'AI feature graveyard' trap.
🗺️How to Create an AI Product Roadmap
AI roadmaps are different. The model layer changes monthly; the user expectations shift quarterly. Plan for compounding.
🎚️RAG vs Fine-tuning vs Prompt Engineering
Three ways to inject knowledge into an LLM. Picking the right one saves months of wasted infrastructure.
📝Prompt Engineering in 2026
The patterns that work with current frontier models. Less about clever tricks, more about clear instructions and good examples.
📊Evals — The FAQ Every AI PM Needs
Evals are how you know if your AI product actually works. The single most-skipped discipline by junior AI teams.
⚖️Why LLM Judges Fail (and How to Fix Them)
LLM-as-judge is now the default eval method. Most implementations are unreliable. Here's why and what to do about it.
🤖AI Agents for PMs
Agents are the dominant AI UX of 2025-26. PMs who can design and ship agentic products have a defensible career skill.
🔬AI Customer Intelligence
Using LLMs to synthesize 10,000 customer signals at the scale and speed humans can't. The new craft of customer-listening.
📝Writing PRDs in the AI Era
Modern PRDs include prompts, evals, model choices, and failure modes — alongside the classic user problem and success metric.
⚡Vibe Coding for PM Portfolios
Build a real working AI product in a weekend. Use it as your portfolio. Recruiters in 2026 stop scrolling.
🧪Vibe Experimentation
Using AI to run product experiments faster — from hypothesis generation to results synthesis.
🎯AI PM Job Search — The 9-Step System
From 'I want to be an AI PM' to landing a $300K+ role. A structured 90-day playbook.
📄The AI PM Resume
Lead with the AI artifact. Reframe every bullet through the AI lens. The resume that gets the interview is structurally different.
🎤The AI PM Interview
The format that's emerging at AI-native companies. Technical AI depth, scenario design, and increasingly a live vibe-coding round.
📡AI Observability
How you know if your AI feature is working in production. The single most-underbuilt layer in AI products in 2026.
🪒21 Harsh Truths about Product Management in AI
What practicing AI PMs wish someone had told them. The uncomfortable patterns nobody publishes.
🪄Using Claude for PM Work
The day-to-day Claude workflows that compound a PM's leverage. From PRDs to user research synthesis to roadmap analysis.
↗️Case Study: Cursor's Growth
From VS Code fork to $9B valuation in 2 years. The fastest-growing dev tool in history, by some measures.