From the source
Much of the past year's progress in mathematics and constrained optimization falls into this category - machine-checked proofs of long-open Erdős problems , gold-medal performance at the IMO , new bounds on decades-old combinatorial problems .
The search space can be enormous, but the result can ultimately be judged as a whole.
Large software tasks are different.
A software specification can semantically cover the desired outcome without specifying what must be run, inspected, and compared before the work can be called complete.
Requirements state what must be true.
By themselves, they do not measure whether the work achieves it.
Without that measurement, an agent constructs one piecemeal as it works.
It decomposes the task, validates each piece in the context that produced it, and eventually decides that it is finished.
Every local judgment may be reasonable while parts of the whole remain unmeasured.
Humans currently close the loop by supervising the agent: holding the whole outcome and steering the agent back to it.
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