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Career track · AI Product Manager

Become an AI product manager: decide what to build with AI, and prove that it works.

AI PMs prototype instead of writing long specs, and judge quality with evals instead of gut feel. Learn the new skills alongside the product fundamentals that still matter.

Or get your personal AI playbook now

What changes

Your work, re-mapped.

How AI is changing this work today, task by task. Your assessment maps it onto your own week.

Tasks AI can already do for you.

  • Long written specs for simple features
  • Manual synthesis of user feedback
  • First drafts of PRDs and roadmaps
  • Static mockups for every idea

The curriculum

Ten modules.
One path through them.

Your assessment orders these for your level and goals and skips what you already know. Open any module to see what it covers.

01What makes AI products different5 topics

Probabilistic products need a different way of managing.

  1. Deterministic vs probabilistic software
  2. Capability vs reliability
  3. The AI product lifecycle
  4. Roles in an AI team
  5. Common AI product failures
02Finding AI opportunities5 topics

Pick problems where AI creates real value.

  1. Jobs-to-be-done for AI
  2. Automation vs augmentation
  3. Feasibility checks
  4. Build vs buy vs wait
  5. Prioritising AI bets
03AI literacy for PMs5 topics

Enough technical depth to make good calls.

  1. How LLMs work
  2. RAG, fine-tuning and agents
  3. Latency and cost drivers
  4. Model selection trade-offs
  5. Talking with AI engineers
04Prototyping with AI5 topics

Make your spec the prototype.

  1. Prompt prototyping
  2. Text-to-app tools
  3. Testing with users quickly
  4. From prototype to plan
  5. Prototype pitfalls
05Evals: defining quality5 topics

The most important AI PM skill.

  1. Writing quality criteria
  2. Building your first eval set
  3. Human and LLM-as-judge grading
  4. Evals as acceptance criteria
  5. Tracking quality over time
06Data and feedback loops5 topics

Products that improve with use.

  1. Collecting feedback signals
  2. Labelling and review workflows
  3. Data flywheels
  4. Privacy and consent
  5. Measuring improvement
07Designing AI experiences5 topics

UX that earns trust.

  1. Setting expectations
  2. Showing sources and confidence
  3. Handling errors gracefully
  4. User control and undo
  5. Designing agents
08Business models for AI products5 topics

Make the numbers work.

  1. Unit economics with model costs
  2. Pricing models for AI
  3. Cost control levers
  4. Competitive moats
  5. Measuring ROI
09Responsible AI and risk5 topics

Launch without causing harm.

  1. Bias and fairness
  2. Safety and misuse
  3. AI regulation basics
  4. Red-teaming
  5. Launch reviews
10Launching and scaling AI features5 topics

Ship, measure and iterate.

  1. Staged rollouts
  2. Success metrics
  3. Monitoring quality after launch
  4. Iterating on feedback
  5. Your AI PM portfolio

Outcomes

By the end, you can.

  • 01Spot and prioritise AI opportunities with real value
  • 02Prototype an AI feature in a day and test it with users
  • 03Write eval sets that define quality for your team
  • 04Plan the economics and launch of an AI product

Tools and techniques you'll use

  • Lovable, v0 and Bolt
  • ChatGPT, Claude and Gemini
  • Braintrust
  • LangSmith
  • Arize Phoenix
  • Product analytics tools
  • Figma

Who it's forProduct managers, founders, business analysts and engineers moving into product.

The course is opening soon

Be first in.

Join the waitlist for the AI Product Manager course. One email when it opens, nothing else.

Questions

Good to know.

What skills does an AI product manager need?

On top of core product skills, AI PMs need to prototype with AI tools, define and run evals, understand AI cost and latency trade-offs, and design for uncertain model output. The course covers each of these.

Do AI product managers need to code?

Not in depth. Being able to build quick prototypes with AI tools and read a simple eval is increasingly expected, and the course teaches both without assuming programming experience.

When does the course open?

The full course is being built now and opens to the waitlist first. Join with your email and we'll tell you as soon as it's ready.

How is the course personalised?

Before the course, a five-minute assessment, by text or by voice with Iris, our AI guide, learns your role, daily work, skills and goals. Your personal playbook then orders these modules for your level and goals and skips what you already know.

What can I do while I wait?

Take the assessment now. You get your personal AI playbook straight away, with the tasks in your work AI can take over, the ones it speeds up, and your learning path.