About This Session
No single AI model is best at everything. The challenge is knowing which model to use, how to measure whether it is good enough, and how to control cost as agents move across different tasks. You'll learn how to: Compare proprietary, open-weight, and fine-tuned models for different workloads Evaluate models on quality, latency, and cost using LLM judges Use Smart Routing to automatically match tasks and agent subtasks to the right model Govern agent workflows with policies, token limits, and spending controls This session includes practical demos of model evaluation, Smart Routing, and agent cost controls with the open-source tools Omnigent and MLflow. Whether you're building AI applications or coding agents, you'll leave with a practical framework for choosing, evaluating, and governing models without sacrificing quality.
Topics
- AI Coding Assistants
- Anthropic
- Claude
- Databricks