RL Environments are used by frontier labs to train their latest models and agents. In this talk, I will explain why RL environments are fundamental to all stages of building agents: from evaluations and prompt optimization to post-training agents. I will show concrete industry examples of how practitioners use RL environments to evaluate their agents, and to understand how their agents fail. Lastly, I will also talk about how one can set up data flywheels which helps you figure out how to improve your agents on your specific data and use-cases.

TestMu Conf
Testμ(TestMu) Conference is TestMu AI’s (Formerly LambdaTest) annual flagship event, one of the world’s largest virtual software testing conferences dedicated to decoding the future of testing and development. Built by the community, for the community, it’s a space where you’re at the center, connecting, learning, and leading together. From deep-dive sessions on emerging trends in engineering, testing, and DevOps, to hands-on workshops and inspiring culture-driven talks, every experience is designed to keep you at the heart of the conversation.

From AI Assistants to AI Coworkers: How Engineering Teams Ship Faster with Enterprise Context
TestMu 2026
Keynote: Beyond Benchmarks - Evaluating Agents Against What They Are Actually Supposed to Do
TestMu 2026
Panel Discussion: Money Moves at Machine Speed - Trust, Risk, and Quality in Agentic Finance
TestMu 2026
From Load Testing to Reliability Engineering: Making Performance Testing Predict Production Behavior
TestMu 2026
Panel Discussion: Who Tests the Machines? QE Leaders on Quality in the Age of AI-Written Code
TestMu 2026
Fireside Chat: The Economics of AI Agents: How Startups Are Rethinking Value and Monetization
TestMu 2026
Panel Discussion: Mission-Critical Priorities in Quality Engineering: The Leader's Playbook
TestMu 2026