Thinking Machines Lab finds batching variance in LLM outputs

The author argues that building reliable AI products requires separating probabilistic interpretation from deterministic execution and human oversight boundaries. The article examines how companies like Routine Labs and Zauber design hybrid workflows that use AI for interpretation while keeping production execution predictable and logged. Furthermore, the author suggests mapping workflow steps into deterministic, fuzzy, and irreversible categories to prevent hidden uncertainties and uncontrolled agent behaviors from breaking user trust. Open article →