Microsoft Reactor

AI agents rarely rely on a single model to solve every task.

In this episode of Model Mondays, we'll explore how model router helps developers apply a hill-climbing approach to agent development by continuously finding better models for different steps in a workflow.

Learn how to evaluate models, compare performance across providers and model families, and dynamically route requests to the model best suited for each task.

Through discussions and demos, we'll show how model router helps agents improve quality, efficiency, and cost by treating model selection as an ongoing optimization process rather than a one-time decision.

• Explore the Resources
• Read the Newsletter
• Continue the conversation on the Discord