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Product · 8-week live cohort

AI and Product Management

Use AI inside a product system, not as a substitute for one.

Build a repeatable product-management workflow that combines discovery, requirements, prioritisation, experimentation, metrics and responsible AI delivery.

Next cohort

Next cohort details will be published when confirmed.

Register interest
See the programme journey
The programme standard

Understand it. Practise it. Produce evidence.

ClarityKnow the concepts and reasoning behind the work.
PracticeUse tools and methods in realistic tasks.
EvidenceLeave with practical outputs you can inspect and explain.
How the work fits together

The product decision loop

AI does not remove the need for product judgement. It makes the quality of that judgement more visible.

AI belongs inside a product system with clear problems, measurable outcomes and responsible boundaries.
01Discover

Use evidence to understand the user, problem and opportunity.

02Define

Turn learning into requirements, priorities and product guardrails.

03Test

Use prototypes and experiments to reduce uncertainty.

04Measure

Decide what success means and what evidence should change the direction.

Programme overview

AI and Product Management

Build a repeatable product-management workflow that combines discovery, requirements, prioritisation, experimentation, metrics and responsible AI delivery.

01
Discover before buildingUse customer evidence to frame problems and opportunities.
02
Write sharper product requirementsTurn learning into stories, acceptance criteria and guardrails.
03
Prioritise with explicit trade-offsBalance value, cost, risk and learning.
04
Evaluate AI use cases responsiblyConsider data, privacy, model behaviour and success thresholds.

What you will build

Practical work that makes progress visible.

01 · Output
Discovery report

Problem and Solution Tree grounded in evidence.

02 · Output
Product requirements document

User stories, acceptance criteria and AI guardrails.

03 · Output
Prioritised roadmap

Costs, risks and learning milestones.

04 · Output
Metrics plan

Activation, retention and growth measures.

05 · Output
Experiment backlog

Hypotheses and success thresholds.

06 · Output
Prototype and go-to-market one-pager

A practical capstone for communicating the product direction.

Programme journey

A clear progression through the work.

Start

Discovery and customer evidence

Frame real problems before choosing solutions.

Define

PRDs and roadmapping

Translate learning into requirements and priority.

Prototype

Experimentation and evaluation

Test assumptions and AI behaviour deliberately.

Measure

Metrics and learning

Define what success looks like and what needs to change.

Finish

Responsible AI delivery and capstone

Bring the product workflow together into a reusable system.

Who this is for

Built for people who need the capability in practice.

Aspiring and practising Product Managers
Business Analysts, Designers and Engineers moving into product
Founders and product operators
People shipping AI-enabled features responsibly

How you learn

A live learning rhythm built around practice.

The programme combines structured teaching, guided practice and regular review so the work develops alongside the knowledge.

01Three live sessions weekly
02Recordings available
03Weekly clinic and community support
04Templates, canvases and checklists
05Light weekly quizzes

Next step

Interested in this programme?

Check the current application status and register your interest. We do not publish cohort dates until they are confirmed.

Next cohort

Next cohort details will be published when confirmed.

Register interest