When Economic Insider asked me to write a piece about how artificial intelligence is reshaping the way businesses operate, I knew I didn’t want to write the usual article. The world doesn’t need another column about AI replacing jobs or another breathless prediction about the future of automation. What I wanted to do was share something I’ve been observing firsthand — something that most people in the industry are not yet talking about clearly enough.
The idea that sparked the article
For the past several years, running Hybrid Digital Consultancy with a team of around one hundred specialists, I’ve had a front-row seat to a profound shift. I’ve watched the value of execution — the ability to write code, produce content, build things — decline steadily as AI tools have become more capable. And I’ve watched something else rise in its place: the ability to make good decisions about what to build in the first place.
This is not an abstract observation. It’s something I see every week in conversations with founders and executives. The companies that are winning right now are not the ones with the fastest engineers or the most sophisticated tech stacks. They’re the ones where the people making decisions truly understand the problems they’re solving. They’re the ones where judgment sits at the center, not at the periphery.
I wanted Economic Insider’s audience to understand this distinction, because I believe it’s the most important strategic insight of this moment.
Vibe coding and the end of execution as a moat
One of the concepts I explored in the article is vibe coding — a pattern that has quietly transformed software development. The developer’s role has shifted. They’re no longer the person who writes every line of code. They’re the person who defines what the code needs to accomplish and why. AI handles the execution. The human holds the frame.
This matters enormously, because it means that technical skill — while still necessary — has stopped being the deciding factor. What has replaced it is harder to teach and impossible to automate: the ability to read a real problem clearly, to tell the difference between a technically impressive solution and one that actually solves something, to decide what is worth building at all.
These are judgment calls. And judgment doesn’t scale the way execution does.
I’ve been thinking about this shift for a long time, and it’s one of the reasons I structured Hybrid Digital Consultancy the way I did — strategy, development, content, and data under unified governance, so that the people who decide what to build are never separated from the people who build it. The gap between organizations that work this way and those that don’t is becoming more visible every quarter.
Judgment capital: a concept I’ve been developing
In the article, I introduced a concept that I’ve been refining over the past year: judgment capital. It’s the idea that when code production becomes cheap — and it has — the quality of thinking that precedes and directs execution becomes the real constraint. Organizations that invest in judgment capital, that structure themselves around better decision-making rather than faster output, are the ones that will hold ground.
This isn’t just theory. It’s the foundation of the conversations I have with clients every day. The question I ask isn’t “What technology should you adopt?” Most leaders already understand AI well enough. The question is: “Where, in your particular structure, is human judgment worth the most? Where should you stop executing and start choosing?”
That’s a different conversation from the one most AI consultants are having. It starts with the organization — its structure, its decision points, where it gets stuck — and works back to find where intelligence, not processing power, is the real bottleneck.
The Hybridocene: a framework for what comes next
The article also gave me the opportunity to share a framework from my forthcoming book, Inside the Artificial Revolution. I’ve been developing the concept of the Hybridocene — a term I coined to describe the phase we’re entering, where humans and AI systems coexist in shaping economic and social structures. Not competing for the same work, but operating according to different logics.
The organizations that learn to combine those logics with intention will outlast those that treat AI as a faster version of what they were already doing. This is the central argument of the book, and writing this article for Economic Insider was in many ways a chance to test it against a business audience and see how it resonated.
The response has been encouraging. The idea that we’re not in a replacement story but in a transition — from the Anthropocene to the Hybridocene — seems to click with leaders who feel that the current narrative about AI is too simplistic. They know it’s not just about speed. They know it’s about something deeper. The Hybridocene gives them a language for what they’re already sensing.
Why I chose to write in English
There’s a deliberate choice behind publishing this piece in English on an international outlet. As Hybrid Digital Consultancy expands its presence beyond Italy, I need to participate in the global conversation about where business is headed — not just observe it from a distance. Writing for Economic Insider allowed me to reach an audience of decision-makers across markets, in a language that travels without translation.
This is something I’ve learned through experience: if you want to be part of a conversation, you have to show up where that conversation is happening. And right now, the conversation about AI and business strategy is happening in English, on platforms that reach across borders.
The response
What surprised me most about the response to this article was how many people reached out not to debate the technology, but to talk about the organizational implications. CEOs asking how to restructure their teams around judgment rather than execution. CTOs wondering whether their hiring criteria are still relevant. Founders questioning whether they’re optimizing for speed when they should be optimizing for clarity.
These are exactly the right questions. And the fact that a single article could spark them tells me that the market is ready for this conversation — even if most of the industry hasn’t caught up yet.
Looking ahead
The closing line of the article is one I’m particularly proud of: “The shift from knowing how to do, to knowing what to do, is already the terrain competition is moving onto. The businesses that see it now will be building the next economy. The others will be refining the one that is ending.”
I wrote those words because I believe them deeply. And I believe that the companies and leaders who internalize this shift — who stop measuring their value by how fast they can execute and start measuring it by how well they can decide — will be the ones who define the next decade.
This is the work I’m committed to. At Hybrid Digital Consultancy, with my book, and in every conversation I have with leaders who are trying to figure out what comes next. The future belongs to those who can think clearly in the presence of machines that can do everything else.
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