Training. At the beach it’s the word that reassures: “AI keeps learning, the more you use it the better it knows you, it updates itself.” It sounds so reasonable that nobody checks. Last time we completed the toolkit: the message, the tools, the loops. Now it’s time to open the bonnet and look at the

Agents. The word brings to mind the science fiction robot. The autonomous being that wakes up, understands, acts, decides in your place. Curtain. The truth is more boring — and for that reason more useful: an agent is a prompt with two things added. Some tools, and a margin of autonomy. A prompt produces text.

Every summer Italy gets a degree in something. The national team, the spread, the virus. This year it’s AI’s turn. For those who have already tackled the subject seriously — and if you’ve read this far, the answer is yes — beach debates are a minor form of torture: the right words used at random,

There’s one thing I’ve learned in two years of conversations about AI with entrepreneurs, CEOs, and technical leaders. The decision almost never comes down to the numbers. The same decision-maker who, faced with an important hire, weighs options, compares, asks for data — with AI goes on gut instinct. And doesn’t notice. They think they’re

Seven postures facing AI. Today I close the series with the first question to ask yourself. Seven different ways of approaching the AI revolution. Each one with a blind spot. One of them is yours, today. The first question you need to ask yourself about AI isn’t “what AI do we need?” It’s “how am

Seven postures facing AI: the Process Thinker. Some time ago I had a conversation with a serial entrepreneur — many exits behind him, calm and attentive eyes. He was one of the few people I’ve been able to talk to about determinism in AI-governed processes, about how to mitigate the risk of hallucinations, about how

Seven postures facing AI: the Sovereign. A fashion multinational — one of our clients — banned any AI project by definition for the first eighteen months. The risk of sending data to servers outside their control was considered unacceptable, and that was enough. No prototypes, no experiments, not even a theoretical thought about value. Eighteen

Seven postures facing AI: the Disappointed. I witnessed up close a successful mechanical engineering company bring AI into their Technical Office. The managing director — a committed innovator — had brought in a university start-up and put a significant budget on the table. Everything seemed in order. Under the surface, expectations weren’t aligned. The technical

Seven postures facing AI: the Quietly Disoriented. The twin of the Honestly Disoriented. Same disorientation, opposite posture. On a plane, sitting next to me: a prominent entrepreneur from the investment world. He spends half an hour explaining how AI should work inside a company. Principles, culture, risks. Some of it is cliché, some of it

Seven postures facing AI: the Honestly Disoriented. An ICT manager from a multinational — one everyone cites as among the most innovative in the sector — calls me. Almost verbatim: “I have two hundred thousand euros of AI budget. I have absolutely no idea how to use it.” I listened, and thought it was the

Seven postures facing AI: the Satisfied. You recognise them by a single phrase: “For what we do, ChatGPT is enough.” It’s said by the entrepreneur who throws contracts in and reads the answer. By the director who uses it to write emails and finds them better than their own. By the professional who replaced three

Seven postures facing AI: the Renaissance. You recognise them by a single phrase: “look what I can do now.” It’s said by an entrepreneur who wrote code twenty years ago and had to stop to run the company. By a CTO who left the keyboard for meetings. By a product manager who started in engineering

Over the past two years I’ve spoken with many entrepreneurs, CEOs and technical leaders wondering what to do with AI. I made proposals. I got quite a few of them wrong. While I was reworking them, I began to notice a pattern I hadn’t expected. I was building solid proposals on the content side. I

What we’ve learned at IdeaTech The great technological revolutions of the past — steam, electricity, computing, the internet — share a property we take for granted: they were always fast for markets, but slow for people. The first, steam, lasted a century. Those who were coachmen died as coachmen. The next generation dealt with steam