Move by Move: Measuring and Steering How LLMs Conduct Psychotherapy
A tool-exposed ontology steered models closer to human therapy patterns without fine-tuning, showing how explicit action vocabularies can improve agent behavior.
The researchers define **10 therapeutic moves**, validated with **5 licensed psychologists**. Frontier models used inquiry at up to **3× the human rate**, while exposing the moves as tools improved turn-level alignment by **7–9 percentage points**.
For builders, this suggests representing desired behavior as explicit, callable actions rather than relying only on prose instructions. A compact action ontology can make agent behavior measurable and steerable without fine-tuning.
The researchers define **10 therapeutic moves**, validated with **5 licensed psychologists**. Frontier models used inquiry at up to **3× the human rate**, while exposing the moves as tools improved turn-level alignment by **7–9 percentage points**. For builders, this suggests representing desired behavior as explicit, callable actions rather than relying only on prose instructions. A compact action ontology can make agent behavior measurable and steerable without fine-tuning. The evidence concerns psychotherapy, where behavioral alignment is safety-sensitive and human distributions are not automatically ideal outcomes. The material does not establish whether the method transfers to coding agents.
This converts an expert-defined behavioral taxonomy into both an evaluation surface and a steering interface. It strengthens the case for encoding domain practice as observable actions rather than trusting prose instructions or model introspection, while narrowing the claim to turn-level therapeutic behavior: matching human move distributions does not itself establish clinical quality or transfer to other agents.