Our publications
Field notes, practical frameworks and executive perspectives for turning AI ambition into operational reality.
Why 80% of enterprise AI projects fail, and how to avoid it
AI projects rarely fail because of the model. They fail because they start with technology instead of a critical, measurable process owned by the business.
From POC to production: the gap nobody explains
A working POC does not prove an AI product can survive in production. The real work starts with live data, workflow integration, governance and adoption.
Generative AI will not replace your strategy. It will expose it.
Generative AI does not create a strategy. It exposes the grey areas, documentary contradictions and implicit standards an organization had been tolerating.
Business LLM evaluation: the most dangerous sentence in an AI project
Saying an LLM works well means nothing until you define for whom, against which risk, and with what measurable operational impact.
Claude and Obsidian: how I use my second brain
Connecting Claude to an Obsidian vault turns a second brain into a reliable assistant: contextual, aligned with your voice, and able to retrieve what you have already thought through.
Product or service innovation: what really accelerates time-to-market fit
Time-to-market is not enough. What creates value is the speed at which an offer meets a real, recognized and market-ready problem.