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Video course · 15 chapters · 70 min · certificate

The Complete AI Product Management Guide: Build & Ship AI Products

The AI PM playbook: prompt engineering and prompt libraries, rapid prototyping, fine-tuning, RAG and vector databases, agents and multi-agent systems, evals and LLM judges, no-code SaaS, and handling edge cases and jailbreaks.

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What you'll learn

  • Use prompt engineering and build a prompt library
  • Prototype AI ideas quickly
  • Decide when to fine-tune versus use RAG
  • Explain vector databases and the RAG lifecycle
  • Understand agents and multi-agent systems
  • Evaluate AI with evals and LLM judges and handle edge cases

Chapters

15 chapters · 69:55
  1. 3:04 01Intro Members The AI product manager PMs are moving from intuition-driven to data-augmented, with AI as the engine.
  2. 5:12 02Prompting Members Prompt engineering and libraries Crafting effective prompts and building a reusable prompt library.
  3. 3:54 03Prototyping Members Rapid AI prototyping Making ideas tangible fast to get feedback and de-risk assumptions.
  4. 5:02 04Fine-tuning Members Fine-tuning models When, why and how to fine-tune, and measuring whether it moved the product metric.
  5. 3:12 05RAG Members Retrieval-augmented generation Adding your own knowledge to a model with RAG, compared with fine-tuning.
  6. 4:44 06Vectors Members Context engineering and vector databases Embeddings, vector databases and building a RAG chatbot.
  7. 2:13 07RAG Members The RAG query lifecycle RAG as a precise, multi-step process: query transformation, fast retrieval and more.
  8. 7:24 08Agents Members AI agents fundamentals The real pain is fragmented context across tools; agents bring it together.
  9. 6:23 09Multi-agent Members Multi-agent systems Blueprints for multi-agent systems that research, plan and execute.
  10. 4:47 10Teams Members AI assistants and teams Agents that work across many tools for teams.
  11. 2:25 11Evals Members AI evaluation methods Evals as unit tests for AI reasoning, tone and facts.
  12. 9:40 12Evals Members Scaling evals with LLM judges Human grading doesn't scale; LLM judges evaluate thousands of responses.
  13. 2:04 13SaaS Members Building scalable AI SaaS Considerations for scaling an AI product into SaaS.
  14. 4:44 14No-code Members No-code SaaS development One person with no technical background can now build a SaaS product.
  15. 5:07 15Safety Members Edge cases and safety Looking finished isn't being safe: attackers, bots and jailbreaks.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

Product ManagersChief Product Officers (CPOs)Product OwnersProduct AnalystsIT Project ManagersInnovation StrategistsProject ManagersCDOs (Chief Digital Officers)No-Code DevelopersSolutions ArchitectsTechnology ManagersAI Consultants