Articles
Short pieces on why AI projects stall, what actually moves people, and the practical decisions small businesses face when they bring AI into daily work.
On AI adoption, training, coaching, and what it actually takes to build with these tools — from the training room to shipping alone.
Three AI products in eighteen months, no team, no co-founder, no outside funding. That's not a boast, it's the condition under which I learned the thing this piece is actually about, be…
Read articleOrganisations spend serious money getting AI adoption wrong in a very specific order: licences first, security review second, infrastructure third, and then, almost as an afterthought,…
Read articleMost AI adoption programmes die in the room where everyone loved the demo. Someone shows the tool doing something genuinely impressive, the room nods, a few people ask sharp questions,…
Read articleIn July, a few hundred AI agents running inside OpenAI's test environment found their way onto the internet and broke into Hugging Face's servers. Nobody told them to.…
Read articleA three-part guide to where AI should run: why the local-versus-cloud question came back, which data may go where, and what running AI on your own hardware really costs an SMB.
Small business owners have started asking me whether they should run AI on their own machines instead of sending everything to ChatGPT, Copilot or Gemini. I understand why…
Read articlePicture an employee who knows AI well, in a company that has decided Copilot is the official tool. If they think another tool, Claude for example, does a better job for what they need,…
Read articleThe usual pitch for local AI is that you stop paying subscriptions. You do stop paying per user or per request, and in exchange you pay for hardware, electricity, setup and the hours of whoever…
Read articleOn the paths AI left us without: why a capability everyone holds stops being an advantage, and where a personal edge — the abilities you never noticed and the material your life gave you — actually comes from.
AI gives everyone the same capability, so capability stops being an advantage. The concept that explains what is missing comes from role-playing games: a signature path — a sequence of abilities that is visibly yours and has a visible next step.
Read articleFor most people, 'what do you do?' has a one-word answer. For a polymath it is a problem, and in professional environments it has been a costly one.
Read articleThe abilities that make you most distinctive are usually the ones you are least able to see. Finding them means getting outside your own perception — here is a method in five steps.
Read articleThe second source of uniqueness is less comfortable than natural talent, and more personal. It is the wound: something that hurt, early or late, and shaped how you see.
Read articleThe map of the new paths does not exist yet, and nobody is going to hand it out. It gets drawn by people who walk into the territory and put it on the map for whoever comes next.
Read articleUniversities still prepare people for paths: lawyer, doctor, engineer, musician, a calling plus a sequence of skills. The sequence still works as training, but it leads to less each year.
Read articleMost AI rollouts choose the tool, train the staff, and measure adoption. That order fails when the people whose work is automated lose what made them valuable and nobody helps them find a new definition.
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