We already had Slick: structured processes that worked. And when you have a solid foundation, the temptation is natural — take every block and layer AI on top. Opportunity management, sales management, software analysis, architecture, project management, task assignment for developers, coding. For each one, one or more agents. The plan looked solid. It was

From the outside it looked like a cult… and maybe at the start, it was a little. It was 2024. AI had shown itself to be disruptive, and I wanted to build an AI culture inside IdeaTech straight away. But right out of the gate, I made the classic mistake. I thought it would be

Over more than 24 months of AI on the market, I’ve had the chance to meet many companies and many teams — and I’ve had to navigate the introduction and evolution of AI inside IdeaTech itself (and it’s not over yet…). At first I supported every approach to AI that came my way, proposing projects,

The most common objections when AI comes up in a company: “AI will never do it as well as we (I) do today.” “Our sector is different…” “So we’ll all end up indistinguishable?!” “Let’s wait for it to mature…” “I have the 360-degree view. AI doesn’t.” “Only we humans can guarantee our company’s values.” “In

It sounds like wordplay. It isn’t. Each of those fifty saves an hour a day. Produces cleaner reports. Closes tasks faster. Look at the individual and all you see is improvement. Then look at the company — and throughput hasn’t moved. Decisions still arrive with the same delays. The handoff between two departments is the

The experiment Let’s do an exercise together. It’s simple, it takes five minutes, and by the end you’ll know something important about yourself and the way you work with AI. Take a photo. Any photo. One you like — a landscape, a portrait, an urban scene. Something you look at and think: “yes, this one

Everyone’s at the AI party. I’d suggest talking about the morning after. “Ask AI to recreate Salesforce.” — incredible, forty minutes later you have a free CRM. “Rebuild Jira.” — twenty minutes later, a ticketing system, ready to go. The conclusion everyone seems to draw? “SaaS is dead!” Neat trick. Wrong conclusion. What nobody is

I recently took part in two public events on AI that gave me the chance to discuss the mindset we need to bring to this new era — the one with AI in it. The first was a webinar where, starting from the ideas in the book I wrote over the summer, we talked about

I’ve just returned from the AI Transcend Summit in Istanbul, where I picked up some interesting signals about how roughly 150 entrepreneurs from around the world understand and are adopting AI. Here’s what I saw: What I was hoping to find, but didn’t, was: And yet, it’s precisely these questions about the transitional phase and

Prompt Engineering: The Essential New Skill – Surviving and thriving in the age of artificial intelligence I decided to put into writing everything I’ve learned over the years studying, testing and applying prompt engineering to improve my own performance and that of the IdeaTech team.It’s not a theoretical essay — it’s a field manual, built

It’s NOT about writing longer prompts. Writing 500 words of prompt doesn’t guarantee better results. If anything, it often makes everything worse. It’s NOT about using technical language. You don’t need to learn complicated terms or programmer jargon. AI understands plain language. It’s NOT a magic formula. There’s no such thing as the “perfect prompt”

Working well with artificial intelligence means learning to formulate clear requests, structuring the dialogue with models and guiding the process towards useful, reliable results. It’s not about tricks. It’s about method. With the right approach, you can: The future doesn’t belong to those who use AI occasionally. It belongs to those who learn to work