Four four-hour sessions
An AI workspace
for your product team
Set up an AI workspace around your product: research, a metrics tree, cohort analysis and unit economics. Build a prototype and make an evidence-based case for what to prioritise.
From €10,000 · excl. VAT and applicable taxes
Product managers and product teams
For product teams that need to find opportunities and justify priorities with evidence. Set up an agent workspace that uses your product’s context, then take one product question from research to a prototype and a recommendation.
Work on the same question throughout the programme: reconsider monetisation, find a promising segment or improve paid conversion. Review your existing research and analytics with the facilitator, assess hypotheses and build a prototype.
For example, should a B2B product switch from per-seat to usage-based pricing? Agents analyse usage, payment and cost data alongside findings from customer interviews. You compare cohorts, model revenue and margins, and find segments at risk of churn. The result is a prototype of the proposed pricing approach and an estimate of when the change would pay off. Keep the data, assumptions and reusable skills in your workspace.
An AI workspace you can keep using
Product context
Goals, metrics, customer research, constraints and team decisions, with instructions for how AI should use and update them.
Reusable research and analysis skills
Skills for research, cohort analysis, unit economics and prototyping. Instructions and checks help agents cite sources, distinguish facts from hypotheses and flag missing data.
Tools and connections
Connections to available knowledge bases, analytics and external tools, with checks that help identify AI errors.
One product question across four sessions
Before the start, choose the task and AI tools and prepare existing research, product analytics exports and financial data. In the final session, begin another task with the saved setup and check the first findings.
1. Set up the workspace and build a metrics treeFour hours
Bring together your product’s business model, goals, research and constraints. Connect revenue and margin to activation, conversion and retention in a metrics tree. Connect available data sources and create skills and agents for your task.
Output: An agent workspace with product context, initial skills and a metrics tree, plus a list of data needed for analysis.
2. Combine qualitative and quantitative researchFour hours
Use research agents to examine existing interviews, feedback and support requests. Compare findings with product analytics: segment the audience, compare retention and conversion across cohorts, and identify where users drop out of the funnel. Check hypotheses against sources and identify gaps in the data.
Output: A map of problems by segment and cohort, and a hypothesis to test first with evidence that supports or challenges it.
3. Model unit economics and build a prototypeFour hours
Compare solutions by their expected impact on product metrics. Calculate customer lifetime value (LTV), customer acquisition cost (CAC), payback period and contribution margin. Test how the estimate changes with different conversion and retention assumptions. Use AI to prototype the main user journey for the selected solution.
Output: A prototype and a unit-economics model with several scenarios, showing which assumptions have the largest effect.
4. Decide what to prioritise nextFour hours
Check the calculations and assess the hypothesis by expected impact, confidence in the data and effort. Prepare a product brief covering the problem, solution, target metric, success criteria and risks. Save the research and analysis skills, then apply the workspace to another task.
Output: A product brief with an impact estimate and a recommendation on what to prioritise, plus an AI workspace the team can use for its next tasks.
Training for your team
Four four-hour sessions
Online or in person, for a team of 5–20
From €10,000 · excl. VAT and applicable taxes
Four four-hour sessions for 5–20 participants, working on your products. A 60-minute preparation call with the sponsor establishes the task and available materials.
You leave with the AI workspace, prototype, unit-economics model and product brief. Sessions can run online or in person; dates and any facilitator travel are agreed with your team.
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Discuss AI for product teams
Tell us what your team needs. We’ll reply to arrange a 30-minute call and talk through the options.
