The book left a rare-books dealer with a secret. On a screen, a reporter watched it move through the logistics bloodstream of America until the signal came to rest at VGT3, an Amazon facility in Las Vegas, then went dark. Inside, printed books arrive in bulk. Their bindings are cut away so the loose pages can be scanned faster. The physical volumes are destroyed. The team's logo shows a dinosaur clutching a book in its claws, teeth bared. There is no bonfire, smoke or jeering crowd, only a blade, a scanner and an efficient workflow. Are we watching the last human harvest, or the beginning of a fight over who controls the data that AI's hungry ghosts demand?

The next employee your company hires may not arrive alone. Alongside them will come a personal agent that knows their history, remembers what they forget and is authorized to act in their name. The company will see an external system seeking access. The employee may see part of themselves. That encounter will be the first operational test of distributed intelligence.

Sometimes, as I explain how AI is reshaping the world, I watch as the audience moves through a compressed cycle of grief. Denial appears in crossed arms and sceptical looks. Anger flickers when an example becomes too compelling to dismiss. Then comes bargaining, usually during the questions at the end. Which jobs are safe? When should humans have the final say? What should my children study? Will I get to retire before i have to deal with this?

For most of the modern age, companies have been designed around business processes. Managers mapped how work moved from one team to another, from request to approval, from customer problem to service resolution, from opportunity to invoice. The process was the operating logic of the firm: a way of coordinating people, systems, controls and time. But the arrival of AI agents is beginning to change that picture. Jensen Huang recently put the shift starkly, arguing that companies now built around business processes may, in the future, be built on “frameworks” — proprietary systems that represent a company’s workflows and make their components more autonomous, proactive and efficient.

Last weekend I found myself sitting in a hotel restaurant facing a surprisingly difficult decision. The breakfast buffet cost $34. Coffee was additional. Juice was extra. Alternatively, I could order à la carte. Eggs were $27. Add coffee, perhaps some fruit, maybe juice, and suddenly the economics became unclear. Was the buffet better value? How much breakfast was I actually planning to consume? At what point did the all inclusive offer become the rational choice? And perhaps most importantly, how much mental effort was I willing to spend answering these questions before I had even had my first coffee? The irony was hard to miss. In an age of AI, I was performing an optimization exercise that felt better suited to an algorithm than a human brain.