Most "AI testing" demos stop at generating a test. Real QA is a loop: you author coverage, capture what actually happened, assure it against intent, and keep it all from rotting as the product changes. In this hands-on session we run that full loop end-to-end with kane-cli, an agentic test tool that drives a real browser and authors runnable tests from plain-language requirements.
You'll leave with a working pipeline on your own machine. We cover:
Author — Turn a one-line requirement into concrete scenarios and cases with kane-cli generate, then let the agent execute them against a live browser instead of hand-writing selectors and waits.
Evidence — Capture every run as a portable, framework-agnostic .evidence pack: the DOM, actions, network, and assertions that prove what the run did — not just a green check.
Assure — Move from brittle exact-match assertions to intent-level verification, so a test fails when behavior breaks, not when a class name changes.
Maintain — Close the loop: keep tests and their knowledge base accurate as the app evolves, using agentic review to catch drift before it ships.
By the end you'll understand where AI genuinely replaces manual QA toil, where a human still owns the gate, and how to wire the author-evidence-assure-maintain loop into your own stack. Bring a laptop with Node installed; we build and run everything live.

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.

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Panel Discussion: Money Moves at Machine Speed - Trust, Risk, and Quality in Agentic Finance
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From Load Testing to Reliability Engineering: Making Performance Testing Predict Production Behavior
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Panel Discussion: Who Tests the Machines? QE Leaders on Quality in the Age of AI-Written Code
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Fireside Chat: The Economics of AI Agents: How Startups Are Rethinking Value and Monetization
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Panel Discussion: Mission-Critical Priorities in Quality Engineering: The Leader's Playbook
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