Take your idea from problem to launch
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.
- → Founders with an idea and no validation yet
- → Side-project builders who want a business, not a demo
- → Domain experts commercialising what they know
- + 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
Is this a real problem? Customer interviews and evidence
Business model, pricing, unit economics and market size
Build the MVP with AI and no-code tooling
Traction, go-to-market and an investor-ready pitch
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.
Understand the roles you are doing alone before you hire for them.
- Product Management
- Product vs Project vs Programme
- PM/PO responsibilities
- Product operating models
- Product lifecycle
A founder's split of product, delivery and commercial work
Use AI to map an operating model and spot where decisions actually get made.
Find out whether anyone actually has the problem you think they have.
- Voice of the customer
- Customer research
- Jobs to be Done
- Personas
- Journey mapping
- Problem discovery
- Problem validation
Ten customer interviews and a go/no-go call
Synthesise interview transcripts into themes and quote evidence in minutes.
Size the opportunity honestly before you spend a year on it.
- Market research
- TAM/SAM/SOM
- PESTLE
- Porter's Five Forces
- Competitive strategy
- AI-powered research
TAM/SAM/SOM with sources you can defend
Run market and competitor research in hours instead of weeks.
Pick the wedge you can win before you build the platform.
- Vision
- Mission
- Strategy
- Strategic choices
- Positioning
- OKRs
- Strategic alignment
A positioning statement and first-market choice
Pressure-test strategic choices against competitor moves and scenarios.
Define the smallest build that proves or kills the idea.
- Opportunity discovery
- Prioritisation
- MVP
- Hypotheses
- PRDs
- User stories
- Acceptance criteria
An MVP definition and hypothesis list
Draft PRDs, acceptance criteria and edge cases from a problem statement.
Get something in front of users before you pay for a build.
- Design thinking
- UX
- User journeys
- Information architecture
- Prototyping
- Usability testing
A clickable prototype tested with five people
Generate and iterate on prototypes fast enough to test the same week.
Decide where AI is your product and where it is just a tool.
- AI/ML fundamentals
- LLMs
- RAG
- Agents
- Prompt engineering
- AI UX
- Evaluation
- Guardrails
- Responsible AI
An AI product canvas with a risk view
This pillar is the AI accelerator — how AI products are specified and judged.
Make build-vs-buy calls without being sold to.
- APIs
- Data
- Cloud concepts
- AI architecture
- Integrations
- Security
- Privacy
- Scalability
A stack decision with cost and lock-in noted
Use AI to explain, diagram and interrogate an architecture you didn't write.
Price your product and know your unit economics cold.
- Business models
- SaaS
- Platform models
- Pricing
- Unit economics
- Business cases
- ROI
- Financial modelling
A pricing model and margin view
Go from assumptions to financial projections without building a spreadsheet first.
Find the loop that grows the business without more spend.
- Product analytics
- North Star metrics
- Funnels
- Retention
- Experiments
- A/B testing
- Growth loops
- Network effects
A growth loop and experiment backlog
Interrogate product data in plain language and surface what moved.
Get your first hundred users through a channel you can repeat.
- Positioning
- Messaging
- Go-to-market
- Launch strategy
- Beta
- Rollout
- Adoption
A GTM plan and first-traction experiment
Draft, test and sharpen positioning and messaging against real objections.
Pitch to investors, customers and your first hires.
- Stakeholder management
- Negotiation
- Executive communication
- Decision-making
- Influence
- Product leadership
A ten-minute pitch you can deliver cold
Rehearse the hard conversation and stress-test your argument before the room.
Shown through the Entrepreneurship track. The pillars are the same on every track — the work you produce is not.
18 modules. One complete
product, built to launch.
Same eighteen modules for everyone. What changes is how deep each one runs for you and why it matters to the job you are doing.
Separate the three jobs you are currently doing at once.
Find out fast whether anyone has the problem you think they have.
Size the prize honestly before you spend a year chasing it.
Pick the wedge you can win before you build a platform.
Choose the one opportunity worth your only year of runway.
Know how the business makes money before you build it.
Define the smallest build that proves or kills the idea.
Put something in front of users before you pay for a build.
Decide where AI is the product and where it is just a tool.
Make build-versus-buy calls without being sold to.
Ship something real without a founding engineer.
Watch the handful of numbers that say keep going or stop.
Price it so the business survives its own growth.
Find one channel that brings customers repeatedly.
Launch small, learn, then widen.
Pitch to investors, customers and your first hires.
Set a weekly rhythm before the company needs one.
Turn the work into the deck you send to investors.
The same situation. A different call, depending on your job.
Short decision exercises used through the curriculum. Read one and you can feel where the tracks separate.
A clinical documentation tool has strong sign-ups and almost no second week. Clinicians say they like it.
Do you improve what exists, or accept the tool solves the wrong moment in the day?
You decide whether this is a pivot or the end of the idea, and you decide this month.
Every order loses eighty pence. Growth is up thirty percent and the board is delighted.
Do you keep growing, raise prices, or cut the segment that loses the most?
You pick the niche where the economics already work and shrink to it deliberately.
An internal AI assistant answers confidently and is wrong roughly one time in eight.
Do you ship with a confidence warning, restrict scope, or hold until accuracy improves?
You narrow the product to the questions it answers reliably and sell only those.
A new onboarding flow lifts completion by twelve percent and drops ninety-day retention.
Do you keep the flow, roll it back, or split the difference?
You keep the users you can serve and stop paying to acquire the ones you cannot.
A sponsor demands a fixed date for an AI feature whose accuracy is still unproven.
Do you commit, refuse, or offer something else?
You say no to the customer and keep the relationship by offering a pilot.
A well-built product launches to silence. The team blames marketing; marketing blames positioning.
Do you relaunch, reposition, or change who you sell to?
You find one repeatable channel and stop doing everything else.
Illustrative teaching examples built from the capstone worlds, not accounts of named clients.
Learn through real product challenges.
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.
A full zero-to-one product journey.
Build an AI product for clinicians and patients.
Search, RAG and enterprise workflow.
Or bring your own problem — most people do, and the programme is built for it.