Notes from the lab.
Field notes on human-led, AI-powered innovation: what we are building, what we are learning, and where it is all heading.
From Climate Crisis to Coffee Innovation: How Constraints Drive the Industry's Most Valuable Breakthroughs
Climate loss, record prices, a $452M R&D gap and 18M tonnes of waste are fueling coffee's most valuable innovations — how constraints drive the breakthroughs.
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Why the Tighter the Box, the Better the Ideas
Constraints don't kill creativity — they channel it. The research behind constraint-driven innovation, the four walls of The BOX framework, and where generative AI fits in.
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Digital Twins vs Synthetic Users vs Synthetic Data: The Complete Guide to AI-Powered Customer Research (2025)
Digital twins, synthetic users, synthetic data and AI personas — what each method actually does, where the research shows it works, and how to choose the right AI-powered customer research approach.
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When Your Data Talks Back: The Socratic Approach to Qualitative Research
Stop extracting insights from static reports. Treat qualitative data as a conversation partner — a Socratic, AI-powered method for deeper, more authentic research.
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The Four Hidden Roles AI Should Play in Your Innovation Process
The smartest teams do not use AI to replace people. Four roles — organizational memory, the crazy junior, neutral moderator and persona simulator — that amplify human innovation.
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Beyond Research: When Customer Insights Become Part of Your Team's DNA
Research decks get archived and forgotten. The Mirror turns deep qualitative research into living, AI-powered digital doubles your team can question any day.
Read article →The Challenges of Enterprise-Level AI Implementation: When Enthusiasm Met Reality
Why enterprise GenAI rollouts stalled after the 2023 hype — organizational readiness, integration, training, culture and AI maturity — and how to fix the human side of adoption.
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What is Human-Centered AI
Human-centered AI starts with humility and empathy. Our guiding principles — Kaizen, joy and mastery, and marginal labor productivity — for an AI transformation that serves people.
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Creative Chimeras and Evolved Antennas: Can LLMs be Creative?
Can large language models actually be creative, or just remix their training data? A response to Francois Chollet on creativity, recombination and emergent concepts in LLMs.
Read article →Generative AI and the Future of Problem-Solving
How thinking machines will change problem-solving — three value levers (efficiency, variability and ubiquity) and the path toward autonomous, end-to-end innovation.
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