Two-Day TrainingProgramme

Two Days, Hour by Hour

Fourteen working sessions across two days. Click any session to see what happens inside it and what your team walks away with.

09:00 to 17:00 both days · teams of 3 to 5 · one real challenge

2 Days

09:00 to 17:00

8 to 24

Participants

Teams of 3 to 5

Working mode

Shared Canvas + AI

Working environment

Your Own Challenge

Worked across both days

12 Artefacts

A complete system

From Problem to Installed Practice

Six moves across two days, with AI woven through every one of them.

01

Why a New Operating System

Where innovation gets stuck, and where AI creates leverage.

02

The Right Customer Problem

Align the team on the problem worth solving, backed by evidence.

03

Value Proposition

Design what you could offer, then let AI attack it.

04

Business Model and Market

Create, deliver and capture value, then reach the customer.

05

Assumptions and Evidence

Find what would break the idea and design the tests.

06

Install It

A 90-day plan that turns the method into how you work.

Session by session

What Happens, and When

Timings are indicative. The facilitator adapts the rhythm to the room and to the challenge in front of it.

Day 1

Find the Right Value

By the end of Day 1 you know WHO you are creating value for, WHAT problem matters and WHAT value you could create.

09:00 – 09:30 1.Welcome: The Case for a New Operating System

The challenge is not a lack of ideas or technology. It is that the way organisations work has not kept pace with technology. The result: slower decisions, stalled projects, siloed teams and a widening gap between insight and impact.

Activity: Collaboration Friction Map

  • Where do we lose momentum?
  • Where do decisions slow down?
  • Where are the silos?
  • Where are assumptions invisible?
  • Where do meetings replace learning?
  • Where could AI create leverage?
Deliverable Our Collaboration Friction Map: current reality, friction, opportunity
09:30 – 10:30 2.Human + AI: The Augmented Collaboration Mindset

Humans contribute creativity, empathy, context, relationships, judgement and decision-making. AI contributes speed, scale, synthesis, pattern recognition, alternatives and challenge. The opportunity is to integrate AI into the team process as a collaborator rather than bolt it on as a separate tool.

Activity: Collaboration Challenge

  • Round 1: human only
  • Round 2: AI only
  • Round 3: Human + AI
  • Compare speed and insight
  • Compare quality and diversity of thinking
  • Compare blind spots and decision quality
Deliverable Our Human + AI Collaboration Principles: AI generates, humans judge. AI challenges, teams decide.
10:30 – 10:45 Break
10:45 – 12:00 3.Find the Right Customer Problem

Do not start with an idea. Start with the Customer Problem. Teams work the Customer Problem Canvas: Customer, Context, Job, Struggle, Pain, Desired Outcome, Evidence, Assumptions.

AI activity: Problem Challenger

  • What are you assuming?
  • What evidence is missing?
  • What alternative explanation exists?
  • Is this a symptom or the real problem?
  • Who experiences this problem most strongly?
Deliverable Prioritised Customer Problem: a team-aligned statement of the problem worth solving
12:00 – 12:30 4.Map the Customer Workflow

A Customer Problem lives inside a workflow. Before designing a proposition, understand how the customer currently gets the job done: Trigger, Discover, Explore, Decide, Buy, Use, Get Value, Repeat.

AI activity

  • Identify missing steps
  • Generate alternative workflows
  • Challenge assumptions
  • Surface hidden stakeholders
  • Find potential moments of value
Deliverable Customer Workflow Map plus the top 3 to 5 Value Opportunities
12:30 – 13:15 Lunch
13:15 – 14:45 5.Create Value: From Opportunity to Value Proposition

The central design module of Day 1. Teams prioritise the opportunity on customer importance, severity of pain, frequency, strategic fit, differentiation and business value, then design the Value Proposition against jobs, pains and gains.

Four AI roles

  • AI Customer: reacts to the proposition
  • AI Challenger: identifies the weaknesses
  • AI Competitor: suggests the alternatives
  • AI Synthesiser: sharpens the proposition
Deliverable Testable Value Proposition: our current hypothesis about how we create meaningful value
14:45 – 15:00 Break
15:00 – 16:00 6.Value Creation Sprint

Connect the individual templates into one blueprint: Customer, Customer Problem, Customer Workflow, Value Opportunity, Value Proposition. The focus is the logic: can we clearly explain how understanding this problem led us to this proposition?

Peer Challenge: the other team may only ask

  • Why this customer?
  • Why is this really a problem?
  • Why is this opportunity important?
  • Why will this create value?
  • What evidence do you have?
Deliverable Day 1 Value Creation Blueprint
16:00 – 16:45 7.The Human + AI Collaboration Workflow

Step back from the customer challenge and ask a different question: how did we actually work today? Teams map, activity by activity, what the human brought, what AI brought and what the two produced together.

Mapped across the day

  • Problem discovery: empathy, synthesis, challenge
  • Customer research: context, patterns, insights
  • Workflow mapping: experience, alternatives, design
  • Opportunity selection: judgement, analysis, decision
  • Value Proposition: creativity, variations, creation
Deliverable Human + AI Collaboration Workflow v1: how this team wants to work
16:45 – 17:00 Day 1 Reflection and Preview

Three questions: what did we learn, what surprised us, and what is our biggest assumption? Day 1 closes on a single line: we have a hypothesis about the value we can create. Tomorrow we make it real.

Deliverable A clear handover into Day 2
Day 2

Make Value Happen

A good Value Proposition is not enough. By the end of Day 2 you know HOW to test, learn, execute and install the system.

09:00 – 09:30 8.Reconnect: From Value to Action

A gallery walk across every Day 1 output: Customer Problem, Customer Workflow, Value Opportunities, Value Proposition and Human + AI Workflow.

Each team receives three kinds of feedback

  • KEEP: what is strong?
  • CHALLENGE: what needs questioning?
  • TEST: what do we need evidence for?
Deliverable Updated Value Creation Blueprint
09:30 – 10:45 9.Design the Business Model

How do we create, deliver and capture the value? Move from the proposition to the system around it: customer segments, value proposition, channels, relationships, revenue, resources, activities, partners and costs.

AI activities

  • Generate business model alternatives
  • Challenge dependencies
  • Identify missing partners
  • Model scenarios
  • Surface risks
Deliverable Business Model Hypothesis: how this value becomes a viable business
10:45 – 11:00 Break
11:00 – 12:15 10.Design the Go-to-Market Workflow

How does the value actually reach the customer? Teams work the Go-to-Market Canvas across target customer, beachhead market, value proposition, awareness, acquisition, conversion, activation, retention, channels and economics.

Activity: map the route

  • TARGET: who do we start with?
  • REACH: how do we find them?
  • ENGAGE: why should they care?
  • CONVERT: what makes them decide?
  • ACTIVATE: when do they feel the value?
  • GROW: why do they stay and expand?
Deliverable Go-to-Market Hypothesis
12:15 – 13:00 Lunch
13:00 – 14:15 11.Find the Assumptions That Matter

Now the whole system goes under pressure: Customer Problem, Customer Workflow, Value Proposition, Business Model, Go-to-Market. At every stage, one question: what needs to be true?

Activity: Assumption Mapping

  • DESIRABILITY: do customers have this problem, and is it important?
  • FEASIBILITY: can we actually deliver this?
  • VIABILITY: can we make the economics work?
  • ADOPTION: can we reach and convert customers?
  • High impact plus high uncertainty means test it first
Deliverable Prioritised Assumption Map
14:15 – 15:15 12.Experiment: Turn Assumptions into Evidence

Stop debating assumptions. Start testing them. Teams work the Experiment Canvas from belief to hypothesis to experiment to evidence to success criteria to decision.

For every assumption

  • What do we believe?
  • What specifically should happen?
  • How can we test it?
  • What data do we need?
  • What would validate or invalidate it?
  • Persevere, pivot or kill?
Deliverable Experiment Backlog: 3 to 5 prioritised experiments per team
15:15 – 15:30 Break
15:30 – 16:15 13.Run the Continuous Learning Loop

Turn all the elements into an operating rhythm: Customer Problem, Value Proposition, Business Model and Go-to-Market, Assumptions, Experiments, Evidence, Learning, Decision, next iteration.

Activity: Simulation

  • Teams receive real experiment results
  • They decide: PERSEVERE, PIVOT or KILL
  • AI acts as data synthesiser, devil’s advocate and scenario generator
  • Humans stay responsible for the judgement and the decision
Deliverable Augmented Innovation Operating Rhythm: what happens weekly, monthly, who joins and what evidence is required
16:15 – 17:00 14.Install the Collaborative Operating System

The final and most important step. How do we make sure this does not remain a two-day workshop?

Activity: 90-Day Installation Plan

  • First 30 days, START: first team, first Customer Problem, first Human + AI workflow, first experiment
  • Days 31 to 60, PRACTISE: run multiple loops, improve templates, build team habits, capture evidence
  • Days 61 to 90, INSTALL: establish the operating rhythm, train additional teams, define roles and metrics
Deliverable 90-Day Augmented Collaboration Installation Plan with actions, owners, cadence and metrics

Dates to be announced

Two days that end with a plan, not a feeling.

Register your interest for the next open cohort, or ask about running both days in-house for your own team.