I've been working through Coursera's Generative AI for Software Engineering specialization, and one idea has stayed with me. When you can run 1,000 agents in parallel, the interesting question stops being how fast can you code and starts being how many different solutions did you evaluate before you picked one? The human's job shifts. You're no longer typing the code — you're generating multiple designs, comparing them against your standard, and picking the one worth shipping.

It sounds like a coding productivity claim. It isn't. Sit with it and it opens onto something bigger.

The constraint most of us have never operated without

For most of history, imagination has been cheap and execution has been expensive. You had a vision. Your organization existed to execute it. So you brought one plan to the room. One strategy. One roadmap. One product bet. Not because one was best — because one was what your workflow allowed.

That constraint just changed. AI agents make execution cheap in a way we've never experienced. Ten variations of a design in the time you used to sketch one. Five roadmap scenarios stress-tested against different futures. Twenty candidate solutions before you pick which one to prototype.

Here's what I've been noticing about myself: I don't do this. Even though I could. My default is still to work out one plan, one design, one path — because my thinking was calibrated in a world where imagining ten was a waste of time. The constraint is gone, but the habit hasn't caught up. I suspect I'm not alone.

What actually shifts when imagination is cheap

You can now get to make decisions from a much wider set of alternatives. That doesn't sound revolutionary until you notice how consequential it is. Most bad strategic decisions in enterprises aren't bad because someone was stupid — they're bad because the leadership team considered two options when there were fifteen, and picked the better of the two while the best one never surfaced. Most bad hires aren't process failures — they're what happens when you evaluate four candidates deeply instead of fifty. Most bad roadmaps aren't judgment failures — they're what happens when judgment is applied to a range of options too narrow to include the right answer.

The generational shift isn't "AI does the work." It's "the number of options a single human can seriously evaluate just went up by an order of magnitude." The humans who learn to expand into that space will out-decide the humans who use the same tools to just move faster.

What I'm trying to do differently

Since the framing landed, I've been experimenting with a small shift: on every meaningful decision — a client proposal, a piece of writing, a hiring conversation, a strategic call about my own work — I ask agents to generate at least three genuinely different framings before I commit. Not three versions of the same answer. Three approaches that would lead to different outcomes.

What I've noticed: the first option I would have gone with is rarely the best one, and the third option I would never have generated on my own is often the one that changes the shape of the answer. That's the reframe. Not "AI does my work faster" — but "AI shows me the work I wouldn't have thought to do."

Imagination used to be expensive. It just became free. The leaders who take that seriously will make better decisions than the ones who use the same tools to just move faster.