Become the Product Manager who can turn ideas into products, businesses and outcomes.
Master Product Management, AI, strategy, business, technology and execution — through one end-to-end learning system. From customer discovery to product strategy, PRDs, AI architecture, MVPs, pricing, GTM, launch and growth.
"Let's validate it before you build. Who is the user, and why would AI make this meaningfully better?"
Product Management has changed.
- — manage backlogs
- — write user stories
- — run stand-ups
- — create roadmaps
- — coordinate teams
The question isn't "Do you know Product Management frameworks?"
It's: can you make the right product decisions?
One programme. The complete Product Management journey.
Understand customers, problems and markets.
Turn problems into product opportunities.
Determine where and how to compete.
Create experiences people want to use.
Translate strategy into products and AI systems.
Take products to market.
Measure, experiment and scale.
Influence organisations and make strategic decisions.
Pick the career you're building. The work is real either way.
Stop taking requirements. Start owning the decision. You learn discovery, strategy, business models, AI product design and analytics — and you prove it by taking one product from a problem nobody has scoped to a launch plan you can defend in a room.
- + One AI product taken from problem to launch plan
- + A written portfolio case study hiring managers can read
- + A 10-minute executive pitch you can give in an interview
You already get things delivered. What you are missing is the half of the job that decides what should be delivered at all: the business case, the benefits, the trade-offs and the judgement to run AI work where 'done' is a quality threshold rather than a checklist.
- + A business case and benefits model for a real initiative
- + An AI delivery playbook: risks, evaluation and governance
- + A portfolio piece that shows leadership, not just coordination
Bring your own idea and find out early whether it survives contact with real customers and real numbers. You build the smallest thing that proves it, put it in front of users, and finish with a pitch and a model you can send to an investor without flinching.
- + A validated problem with evidence, not opinion
- + A working MVP in front of real users
- + A pitch deck and financial model you can send out
One skill stack. Read it through your own job.
Twelve pillars, the same for everyone — because the product system is the same. What changes is what each pillar asks of you and what you produce.
Know what you own, and say no to work that isn't yours.
- Product Management
- Product vs Project vs Programme
- PM/PO responsibilities
- Product operating models
- Product lifecycle
A one-page definition of the outcome you own
Use AI to map an operating model and spot where decisions actually get made.
Replace 'stakeholders asked for it' with evidence from real users.
- Voice of the customer
- Customer research
- Jobs to be Done
- Personas
- Journey mapping
- Problem discovery
- Problem validation
Interview findings and a validated problem statement
Synthesise interview transcripts into themes and quote evidence in minutes.
Argue your roadmap from market reality, not internal opinion.
- Market research
- TAM/SAM/SOM
- PESTLE
- Porter's Five Forces
- Competitive strategy
- AI-powered research
A sized market and competitive map
Run market and competitor research in hours instead of weeks.
Decide where to play and what to refuse — and write it down.
- Vision
- Mission
- Strategy
- Strategic choices
- Positioning
- OKRs
- Strategic alignment
A one-page product strategy with OKRs
Pressure-test strategic choices against competitor moves and scenarios.
Turn a problem into a scoped, defensible thing to build.
- Opportunity discovery
- Prioritisation
- MVP
- Hypotheses
- PRDs
- User stories
- Acceptance criteria
A PRD and a prioritised scope
Draft PRDs, acceptance criteria and edge cases from a problem statement.
Brief and critique design work without designing it yourself.
- Design thinking
- UX
- User journeys
- Information architecture
- Prototyping
- Usability testing
User flows and a tested prototype
Generate and iterate on prototypes fast enough to test the same week.
Specify an AI feature and know when it is good enough to ship.
- AI/ML fundamentals
- LLMs
- RAG
- Agents
- Prompt engineering
- AI UX
- Evaluation
- Guardrails
- Responsible AI
An AI capability spec and evaluation plan
This pillar is the AI accelerator — how AI products are specified and judged.
Hold your own in a technical trade-off conversation.
- APIs
- Data
- Cloud concepts
- AI architecture
- Integrations
- Security
- Privacy
- Scalability
A solution architecture diagram you can explain
Use AI to explain, diagram and interrogate an architecture you didn't write.
Build the business case that gets your work funded.
- Business models
- SaaS
- Platform models
- Pricing
- Unit economics
- Business cases
- ROI
- Financial modelling
A business model canvas with real numbers
Go from assumptions to financial projections without building a spreadsheet first.
Know whether what you shipped actually worked.
- Product analytics
- North Star metrics
- Funnels
- Retention
- Experiments
- A/B testing
- Growth loops
- Network effects
A measurement plan and dashboard
Interrogate product data in plain language and surface what moved.
Land the launch instead of handing it to marketing and hoping.
- Positioning
- Messaging
- Go-to-market
- Launch strategy
- Beta
- Rollout
- Adoption
A GTM plan with channels and messaging
Draft, test and sharpen positioning and messaging against real objections.
Get a decision made when you have no authority to make it.
- Stakeholder management
- Negotiation
- Executive communication
- Decision-making
- Influence
- Product leadership
A stakeholder and influence plan
Rehearse the hard conversation and stress-test your argument before the room.
You won't just learn Product Management. You'll develop the capability to operate across the entire product system.
AI isn't another module. AI changes how Product Managers work.
You learn to use AI across the entire product lifecycle — and to decide where it genuinely creates value and where it doesn't.
AI-powered market research
AI-assisted customer insight
Competitive intelligence
AI-assisted PRDs
AI prototyping
AI-assisted development
AI-powered product insights
AI agents for product workflows
Don't just learn. Build. Inside the AI Product Lab.
Every learner applies the programme to a real product, one stage at a time.
Not a certificate. Evidence of capability.
Learn through real product challenges.
Build an AI product for clinicians and patients.
Build an AI-native career platform.
Improve financial health and retention.
Build a collaboration and productivity product.
Personalised learning with an AI tutor.
Retention, unit economics and growth.
Design a safe, engaging consumer product.
Turn behaviour into measurable outcomes.
Search, RAG and enterprise workflow.
A full zero-to-one product journey.
Or bring your own problem — most people do, and the programme is built for it.
Learn. Analyse. Apply. Build. Defend.
Understand the concept.
Study a real-world case.
Use the framework on a product problem.
Create a product artefact.
Explain and justify your decision.
Nobody is rewarded for knowing what RICE is. They are rewarded for explaining why they chose one opportunity over another — so every module ends with you defending a decision.
A framework library you actually use, not a reading list.
- JTBD
- Personas
- Journey Maps
- VOC
- SWOT
- PESTLE
- Porter's Five Forces
- Blue Ocean
- Playing to Win
- Business Model Canvas
- Lean Canvas
- Value Proposition Canvas
- TAM/SAM/SOM
- Opportunity Solution Tree
- RICE
- MoSCoW
- Kano
- Prioritisation Matrix
- AI Product Canvas
- AI Risk Matrix
- AI Evaluation Framework
- RAG Decision Framework
- Agent Design Framework
- North Star
- AARRR
- Growth Loops
- Experiment Canvas
Each framework: Learn → Example → Template → AI assistant → Apply to your product.
From learner to practitioner to product leader.
You understand the system and the language.
You can run discovery and write a defensible PRD.
You own outcomes, not tickets.
You set strategy and make the hard trade-offs.
You design and govern AI-native products.
You influence the organisation, not just the roadmap.
Build the skills and portfolio needed to break into PM.
Move from delivery management to strategic product leadership.
Add the strategy and business half of the job to your delivery strength.
Turn an idea into a validated product and viable business.
Develop a product toolkit that increases your strategic value.
By the end, you can answer twelve questions.
A curriculum built around real Product Management capability.
Built for practitioners. Designed around real product work.
We don't publish student testimonials yet, because we would rather show you the work than invent a quote.
Built by someone who lives at the intersection of science, healthcare, technology and product.
The goal isn't to teach you another framework. It's to teach you how to think through product decisions.
More about the academy →The AI Product Coach
Bring an idea. The coach pushes back before you build — then evaluates your answers against the way real product decisions get made.
Let's validate it before you build it.
- → Who is the user?
- → What problem are they experiencing?
- → How frequently does it occur?
- → What are they doing today?
- → What alternatives exist?
- → Why would AI make this better?
Each framework: Learn → Example → Template → AI Assistant → Apply to your product.
- + All 18 modules, self-paced
- + Framework toolkit access
- + Case study library
- + Certificate of completion
- + Everything in Foundation
- + Live cohort and mentor reviews
- + The AI Product Lab build
- + AI Product Coach
- + Portfolio case study + pitch
- + Everything in Professional
- + Executive coaching sessions
- + AI transformation strategy work
- + Board-level communication
Is this suitable for beginners?+−
Yes. The programme starts at product foundations and builds up. What it assumes is that you will do the work — every module ends with something you produce.
Do I need technical knowledge or coding experience?+−
No coding. You will learn enough about data, APIs, models, retrieval and evaluation to lead the work and challenge engineers, without writing production code.
Is this only for AI Product Managers?+−
No. It is a complete Product Management programme. AI runs through it because AI now runs through the job, not because it is a niche.
How long does the programme take?+−
The cohort runs 16 weeks at around 5–7 hours a week. Foundation is self-paced and stays available afterwards.
Will I build a real product?+−
Yes. The AI Product Lab takes one product from problem definition to executive presentation — fifteen artefacts, reviewed at every stage.
Can I use my own product idea?+−
Yes, and most people do. If you would rather not, choose one of the capstone problems.
Will I receive a certificate?+−
Yes, but it is the least valuable thing you leave with. The portfolio and the pitch are what get you hired.
Is this suitable for career switchers?+−
It is built for them. Your existing domain knowledge is an advantage — the programme gives it a product language.
What tools will I learn?+−
Discovery and research tools, analytics, prototyping, AI assistants and no-code build tooling, plus the framework toolkit as working templates.
Which track should I choose?+−
Product if you want to decide what gets built, Project & Delivery if you already run delivery and want the strategic half, Entrepreneurship if you are building your own thing. The application asks, and we will say honestly if another track fits better.
Can my employer pay?+−
Yes. We provide invoices and a written business case you can send to your manager, and we run team cohorts for organisations.
Build something that proves
you can do it.
Don't just learn the theory. Ship a product that could change your career.