We study what's working, what's failing, and what the frontier looks like, then help teams put it into practice.
Most of the conversation is about tools, models, and implementation. That's the easy part.
The hard part is knowing what's worth building for a specific company. Context changes everything: data maturity, business model, operational readiness, team capability, industry dynamics. All of these shape which AI opportunities are real and which are noise for any given company.
Most AI projects don't fail because the technology is wrong. They fail because the problem was wrong for that company at that moment, or because the foundation wasn't ready. The model is almost never the bottleneck.
When AI works, it shows up as two things teams can measure: speed of shipping, and quality of what ships.
How AI is changing the way founders and teams make product decisions. What information becomes available, who gets access to context, and where the deepest leverage and damage happen.
How AI is reshaping how work actually gets done. What tools can we use now, where coordination is changing, and what restructuring is required to capture the gains.
How AI integrates into what users actually experience. Which capabilities matter, when, and how deeply. Where the noise is and where the real innovation is.
What separates companies that succeed with AI from those that don't. Data maturity, business model, operational readiness, team capability, industry dynamics. Why the same AI investment pays off for one company and fails for another.
Why most AI projects don't pay off. What breaks, at what stage, and why. The recurring patterns across companies that never quite get AI to work.
We combine meta-analysis of existing research with primary fieldwork. The goal isn't to describe what's happening. It's to understand what actually works, what doesn't, for whom, and why.
Where the research gets applied. We partner with a small number of companies, sometimes as deep residencies, sometimes as targeted advisory, to put ideas into practice.
We bring together founders, researchers, and operators for focused exchanges on what's changing. Small, deliberate, and off the record.
Serial entrepreneur with 15 years building products used by millions. Has led teams of forty, and mentored founders running $100M+ in monthly volume.
Built and shipped AI-native products at two consumer companies. Thinks mostly about interfaces and the shape of new categories.
Research scientist turned infra lead. Interested in the systems underneath, and how data maturity gates what teams can build.
Some provide infrastructure and tools. Some contribute funding. Some partner on specific research questions in exchange for early access to what we find.
We're always looking for founders, operators, and researchers to contribute to the chapters in progress. In return, you get early access to what we find: drafts, interviews, and the conversations around them.