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Free Lesson
Evaluate AI Agents with Simulated Users
30 min
Aug 7, 2026 3:00 PM
Virtual (Zoom)
In this video
What you'll learn
Understand how user simulation works
See how an LLM-based user simulator interacts with an agent
Create real-world-like evaluation scenarios
Define user context, data states, policies, and measurable success criteria.
Build and run a custom simulation with τ²-bench
Follow a live end-to-end implementation of a student financial-aid domain.
Why this topic matters
Agents rarely succeed or fail because of a single response. They must manage evolving conversations, request missing information, call the correct tools, follow policies, and complete the user’s task.
User simulation gives us a repeatable way to test these interactions before they reach real users.
In this lightning lesson, let's walk through how to use τ²-bench to build user simulation.
You'll learn from
Stella Liu
Head of Applied Scientist, AI Evals
Previously at
