How to be more ambitious: A tutorial for humans with models

I frequently proclaim (together with other people working on AI) that we ought to be more ambitious when using it. It’s become a rallying cry. Whenever we see something impressive, we repost and write “we’re not ambitious enough”. I understand how tricky it is to follow that advice, so here’s a tutorial on being more ambitious.

I think of ambition in four types: Speed, Altitude, Depth, and Range.

• Speed: The same work in less time, the bread and butter for AI’s economic value: If you need some code written, I’ll do it faster with Claude. Well established and requires little creativity in how you approach AI, so I’ll skip this one.
• Altitude: Going up in abstraction and considering the outcome rather than the individual task.
• Depth: Considering a task the way a field-leading expert would. Rather than operating at the task’s layer, we go one level deeper and touch the underlying data, tools, and problems.
• Range: Drawing on multiple fields rather than just the one the task might need at the surface, using knowledge, tools, and techniques you normally wouldn’t.