The chess analogy is instructive but may understate the difference. Chess has fixed rules and a bounded state space. The universe of coded solutions operates over an unbounded problem space where the rules themselves can change.

What LLMs actually demonstrated is something more specific: that the mapping between natural language intent and formal code is compressible. The distance between what humans want and what machines can produce collapsed faster than anyone expected. The implication is not that AI will be smarter — it is that the bottleneck shifts from writing solutions to defining problems clearly. The scarce skill becomes knowing what to ask for.