Part 2 — Civilisation

The agentic shift goes beyond technology. Our digital reality, and the way we experience it, will be deeply altered too.

What one can do today with an agent is astounding. The capabilities personal agents give us, as well as their form factor (a natural-language interface, literally no barrier to entry), increasingly feel like having superpowers. Never in the history of humanity has any technology so directly augmented the individual by allowing the delegation of almost any knowledge work, from filling in a form on a website to compiling a report on virtually any topic or building a whole app, effectively giving any human the workforce of a ten-person team of three or four years ago. And it does not stop at the screen: AI agents already make phone calls on our behalf, in a very professional and efficient manner, and they become more robust and dependable with each new generation of models.

But it comes with a price. Delegation inherently has its trade-offs. And because it stands between us and almost everything that reaches us, the agent may increasingly act as a general filter, and that filter may extend to our relationships in real life: what reaches us, who reaches us, and how we deal with other people, even those we know.

Not to mention the very real risk of over-reliance. It may become increasingly tempting to delegate everything that can be delegated, at every level, personal and professional. Not because we are lazy, but simply because it is more efficient.

What is even more worrying is delegating our thinking. If the machine has been right most of the time in the past, it starts to look more like an oracle than a counsellor, and we may simply stop challenging it. In the process, we may weaken our own ability to analyse situations and make decisions, which is critical if we are to remain in charge of our collective destiny. We could, of course, set up another agent to challenge the first one, but we would still no longer be part of the conversation.

The pace of change is such that the old paradigm is breaking down. Time is compressed: what used to take a team of geniuses years and huge resources can now be achieved in a matter of days by whoever has enough compute to throw at the problem. In September 2026, OpenAI announced that an internal model had resolved more than a hundred long-standing open problems in mathematics, some of them decades old: problems that generations of mathematicians had failed to solve. Not every one of these results will survive verification, and OpenAI itself set up an independent advisory group to assess them, but the trajectory is clear, and so is the shift it reveals: mathematicians are moving from exploring to verifying. That shift is not specific to mathematics. Across knowledge work, people are moving from doing the work to reviewing it.

And that's exactly the problem. Where do we stand when we are not the smartest species any more? How will we react? There is a real, maybe even existential, risk here; it is without doubt one of the challenges we will have to face as a species. And it will force us to redefine what makes us human.

The chapters that follow look at this side of the shift.