I propose a software farm.

Imagine a large multi dimensional grid. Each axis of the grid represents a spectrum of how a specific feature could be implemented. You thus have one axis per feature.

Now you plot a cloud of random points all over the grid and at each point have an agent build a solution where the features are expressed according to the corresponding intensity values at the point.

Now you go through and review the solutions you like, create more points around clusters where you kind of like what is going on, until the perfect product emerges.

This is the old idea of giving two teams the same project and letting a third team judge/merge a solution incorporating good parts of each. Just like the old idea, of course you would do this with infinite resources.

You can already sort of do this in way that isn't insanely wasteful if your project has strong measures of correctness. But even then things like compilers have a very real axis for friction in "user/developer/agent experience".. doing it at scale involves some kind of LLM-as-Judge pointed at something which is not an objective value. So .. not only piling on additional false work, but work which is very likely to be incorrect/noisy.

Like The Matrix, but it's us who harvest the dreaming machines.

Not a future I envisioned, but a preferable one.