Foundations
The Role of Models in Agent Systems
What the language model contributes—and what must be handled by the surrounding application.
A flexible decision engine
The model interprets goals, works with ambiguous language, selects among actions, and synthesizes results. It is best treated as a probabilistic decision component rather than the entire system.
The application owns control
Ordinary software should enforce permissions, schemas, budgets, retries, timeouts, and irreversible-action checks. These controls should not depend on the model remembering a sentence in its prompt.
Match the model to the step
A single agent may use a capable model for planning and a smaller model for extraction or classification. Routing work by difficulty can reduce cost and latency without weakening the steps that need stronger reasoning.