Claude Code auto‑creates AI scaling algorithms; new...

This is not a story about a machine that simply followed instructions. It is a story about a machine that discovered a better way to think. The algorithm it wrote is lean, efficient, and alien, a logic humans would likely never have drafted.

It slashes token waste by 70%, transfers across models and benchmarks, and cost less than a dinner out to find. The real breakthrough, however, is not the 70% savings. It is the method itself: an agent that iterates on its own control logic, learning from its own failures, and distilling that experience into code.

This is not automation. This is invention. The machine did not just execute a search; it redefined the search space.

It found a path we would have overlooked, because it was not burdened by our assumptions about how compute should be spent. The implications are stark. If an algorithm can discover better algorithms for allocating its own resources, the bottleneck shifts.

The question is no longer how much compute we have, but how cleverly we let the machine decide to use it. The $40 run is a proof of concept. The real product is a new kind of intelligence, one that designs its own efficiency.

And that is a logic we are only beginning to understand.