LEARNING PATH · AI Engineering

AI for Product Managers

For PMs shipping AI features who want to reason about them without writing code.

Beginner ~5h12 lessons14 steps

A concept-first path for product managers: the AI stack, the build decisions (RAG vs fine-tuning, big vs small model), the cost and quality levers, and the risk surface — paired with interactive calculators so you can pressure-test a plan in a meeting, not just nod along.

  • Speak the AI stack credibly with your engineers
  • Make the build calls: RAG vs fine-tuning, big vs small model
  • Estimate inference cost and reason about the quality bar
  • Understand the risk surface — injection, leaks, and the EU AI Act
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  1. HandbookNext up

    AI for Product Managers

    The PM’s map of the AI stack.

  2. Handbook

    The Prompting Handbook

    What actually makes model output reliable.

  3. Handbook

    LLM vs SLM

    Big model vs small model — when each one wins.

  4. Handbook

    RAG vs Fine-Tuning

    The build decision you’ll be in every week.

  5. AI System Design

    Design ChatGPT

    What sits under a chat product, at a glance.

  6. AI System Design

    Design a RAG Pipeline

    How grounding on your own docs actually works.

  7. ToolTool · optional

    LLM Pricing Comparator

    Compare model prices side by side.

  8. Handbook

    The AI Cost Engineering Handbook

    Where the inference bill actually comes from.

  9. ToolTool · optional

    Context Budget & Cost Planner

    Feel how context length drives cost and latency.

  10. Handbook

    The Agent Evaluations Handbook

    How to know whether the AI is actually good.

  11. Handbook

    The Guardrails Engineering Handbook

    Keep the model on-policy and safe.

  12. Handbook

    The AI Security Handbook

    The new attack surface: prompt injection, data leaks.

  13. Handbook

    The EU AI Act Handbook

    The regulation that will shape your roadmap.

  14. AI System Design

    Design an AI Agent System

    When a feature grows up into an agent.

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