Agentic AI has captured the industry's attention. As more people experiment with LLMs, they develop intuition aka vibes around whether models perform well. While math and classification are easy to verify, generative tasks aren't. Adding agents makes evaluation far more complex. This talk highlights key challenges in productionizing agentic applications: non-deterministic outputs, elusive ground truth, and models that mysteriously regress. Yet 'LGTM' isn't a deployment strategy.
Unlike chatbots that resemble sophisticated search engines, we expect agents to actually perform tasks; making security, bias, and privacy non-negotiable before unlocking real use cases in healthcare, finance, and legal. We'll explore why agent evaluation is fundamentally harder than traditional ML testing: multi-step reasoning chains, tool-use side effects, and more. Topics include building evaluation datasets reflecting production scenarios, automated LLM-as-judge pipelines, knowing when human-in-the-loop is unavoidable, and detecting regressions before users do.
Agent evaluation is fundamentally harder than traditional ML testing.
"LGTM" isn't a deployment strategy.
Build evaluation datasets that reflect production, not benchmarks.
Implement automated evaluation pipelines with LLM-as-judge patterns.
Detect regressions before users do.

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