AGI won't be one big brain
The monolithic-superintelligence story is the wrong mental model. Real general intelligence looks more like an orchestra of specialists than a single giant model.
The Hollywood version of artificial general intelligence is a single, all-powerful brain. That makes a good film and a bad forecast. AGI is unlikely to spring fully formed out of one ever-larger language model. It’s more likely to emerge from coordinating many specialised systems.
The brain isn’t a monolith either
Your brain is not one homogeneous mass. It’s a collection of specialised regions - visual cortex for sight, motor cortex for movement - that share information and coordinate into something far greater than the sum of its parts. General intelligence, biological or artificial, looks like that.
This isn’t a radical claim. It’s how software already works. We stopped building monoliths and moved to specialised services that compose into complex behaviour, because modularity is more robust, more scalable, and easier to maintain. There’s no obvious reason intelligence should be the exception.
Hiding the complexity is the hard part
The real challenge isn’t the specialists. It’s the coordination layer that orchestrates them without exposing the machinery to the user. Picture an interface where you state a goal and an underlying composer breaks it into sub-tasks, routes each to the right specialised system, and assembles the result. That layer of abstraction - not raw model size - is what makes such a system genuinely useful.
Not smarter, just more connected
People say AI will become “smarter” than us, which is misleading. AI is already superhuman in narrow domains: it beats the best Go players, and diagnoses some conditions with remarkable accuracy. Raw capability in a slice is not the bottleneck.
The bottleneck is context and connection. AI lacks the rich, real-world context humans take for granted, and the means to act on the physical world in a meaningful way. A toddler learns through constant interaction, experimentation, and feedback. AI needs the equivalent: better sensors, actuators, and interfaces, plus more diverse data. As systems get better connected to the world, they get more capable at real-world tasks - not because any single model got bigger, but because the system got more connected.
The monolith is the wrong thing to build and the wrong thing to fear. The interesting work is in the wiring.