Agentic workflows are supposed to get boring.
The first pass can be exploratory and pretty expensive. The tenth pass should be boring and not have to rediscover the solution through a completely new set of tools. That workflow has earned a promotion.
That is the useful part of the new Progressive Crystallization paper. It names a lifecycle agent teams are going to rediscover the painful way: agents explore, traces prove repeated behavior, tests turn that behavior into workflow code, and telemetry from those runs decides when the workflow gets demoted back to the agent layer.
The paper presents data from a cloud-network operations system handling real incidents in which deterministic executions went from 0% to 45% over eight months. In the meantime, the per-incident agent cost went down by more than 70% and the number of incidents doubled. The model did not simply get cheaper. Solved work stopped being agent work.
Exploration belongs upstream
