If there are indeed gains to be had in coordination of agents that dwarf gains to be had in improvement of individual agents, why couldn't an AI simply simulate multiple agents?
That may be a faster route to AI. But my point was that making an AI that's smarter than the combined intelligence of humans will be much harder (even for an AI that's already fairly smart and well-endowed with resources) than making one that's smarter than an individual human. That moves this risk even further into the future. I'm more worried about the many risks that are more imminent.
See also: Challenging the Difficult and Tips and Tricks for Answering Hard Questions.
From Michael Nielsen's Reinventing Discovery:
This episode is a microcosm of how intellectual progress happens.
Humanity's intellectual history is not the story of a Few Great Men who had a burst of insight, cried "Eureka!" and jumped 10 paces ahead of everyone else. More often, an intellectual breakthrough is the story of dozens of people building on the ideas of others before them, making wrong turns, proposing and discarding ideas, combining insights from multiple subfields, slamming into brick walls and getting back up again. Very slowly, the space around the solution is crowded in by dozens of investigators until finally one of them hits the payload.
The problem you're trying to solve may look impossible. It may look like a wrong question, and you don't know what the right question to ask is. The problem may have stymied investigators for decades, or centuries.
If so, take heart: we've been in your situation many times before. Almost every problem we've ever solved was once phrased as a wrong question, and looked impossible. Remember the persistence required for science; what "thousands of disinterested moral lives of men lie buried in its mere foundations; what patience and postponement... are wrought into its very stones and mortar."
"Genius is 1 percent inspiration, 99 percent perspiration," said Thomas Edison, and he should've known: It took him hundreds of tweaks to get his incandescent light bulb to work well, and he was already building on the work of 22 earlier inventors of incandescent lights.
Pick any piece of progress you think of as a "sudden breakthrough," read a history book about just that one breakthrough, and you will find that the breakthrough was the result of messy progress like the Polymath Project, but slower: multiple investigators, wrong turns, ideas proposed and combined and discarded, the space around the final breakthrough slowly encroached upon from many angles.
Consider what I said earlier about the problem of Friendly AI:
So: Are you facing an impossible problem? Don't let that stop you, if the problem is important enough. Hack away at the edges. Look to similar problems in other fields for insight. Poke here and there and everywhere, and put extra pressure where the problem seems to give a little. Ask for help. Try different tools. Don't give up; keep hacking away at the edges.
One day you may hit the payload.