In theory maybe, but in practice companies almost always do care about keeping things like release timing, product status or leadership decisions confidential. Even if they haven't publicly announced a policy about prediction markets specifically, it's usually covered under general confidentiality and acceptable use policies
I'm skeptical that this fully replaces thinking, though. It may replace certain forms of effort, but historically every increase in leverage just shifts where the bottleneck is
The danger is that these nuanced, legitimate use cases get rhetorically stretched to support much bigger claims. That's where skepticism kicks back in.
Radiative cooling scales with surface area, compute scales with volume and density. That mismatch is brutal for high-density workloads like AI training
Yet I do think there's a narrow use case where space compute might make sense (for instance, niche workloads colocated with space sensors), but that's very different from "frontier AI training"
The dream of replacing developers may be less about developers at all, and more about a recurring hope that complex socio-technical systems can be reduced to a one-time translation problem
The rhetoric around "energy independence" always sounded like it was pointing exactly toward renewables, and it's hard not to see the missed opportunity in hindsight