AI-based discovery
Real customers try your product and your prototypes. AI collects and synthesizes what they say and do. We work inside product teams, including Bolt, mobile.de and Entirely.
What we are working on
Notes, research and reflections from our client projects and workshops, written by the people who were there.
Eight papers on designing an LLM wiki for customer research: what they tested, what we would build and what we have learned in practice.
Read the noteWhat we're learning at Bolt about building an AI user research agent on an LLM wiki, and about making shared knowledge work for a team.
Read the noteOn AI in customer research, continuous discovery and the work of keeping shared knowledge useful.
Read the noteTwo workshops, one pattern: non-technical teams built working LLM wikis with Claude Code in ninety minutes. The entry barrier has fallen. What matters now is designing the knowledge system the agent works in, not writing a better prompt.
Read the noteAlso in 2026
Cases
No engineering team needed.
All casesProduct teams base decisions on what customers write.
All casesFrom assumption mapping to prototype tests with real customers, and a leadership team aligned on the result.
All casesWorking with us
You start with a 30-minute call. When it fits, we run a pilot with your real data. From there we work inside your team week by week: coaching, tools composed from what you already have, and workshops. The capability to keep going stays with your team.
How we work with you
Hand a task to an agent. Hand over a whole job, even — the work moves, but the learning stays with you. The teams pulling ahead turn every loop into capability: human judgment on one side, the agents they own on the other, compounding into an edge no competitor can copy.
“You can offload a task, or even a job, but you can never offload your learning.”
Teams we work with
Sandra May
Zamics
“AI tools have revolutionized Product Discovery! During the AI Product Dojo, I learned how to automate time-consuming processes like creating user profiles or summarizing insights, while balancing the strengths and limitations of AI for evidence-based decision-making.”
Markus (Yong-Min) Jo
Senior User Experience Researcher, mobile.de
“podojo transformed our approach to customer feedback analysis and helped make evidence-based product strategy decisions, automating categorization and saving us countless hours of manual work.”
Uwe Günzel
Co-Founder, RoX Health
“An impressive development within just six months. Our employee is noticeably more self-confident, performance and reliability have increased — and the whole team benefits.”
Bastian Gerhard
Managing Director, Entirely
“Based in Berlin, Stefan is one of the world's best innovation coaches out there, and my go-to-person for agile leadership, customer centricity and product development — not only for the tools and methodologies, but especially for the mindset.”
Marek Janetzke
CEO, Lucid Labs
“Stefan has a knack for bringing clarity with the right questions. We worked on product topics together and I benefited from his deep experience — a solid methodological foundation combined with a contemporary understanding of AI in product management.”
Christian Marx
Zamics
“Last week's Product Dojo was an inspiring experience, combining hands-on AI tool exploration with product development methods to enhance processes and strategic decision-making. A perfect balance of technology and creativity!”
