The Full Agentic QA Loop for Web Applications [Testμ 2026]

At Testμ Conf 2026, TestMu AI’s Siddhant Sinha demonstrated Kane CLI’s proposed agentic QA workflow, which converts a product requirements document into reviewed use cases, acceptance criteria, scenarios, plain-English browser tests, and an evidence pack linking executed tests to the criteria they verified. Using a food-ordering application, the session extracted four use cases, produced 13 acceptance criteria for one checkout flow, generated four scenarios and four mapped tests, and showed that human approval is required before design proceeds; the agent also asked for clarification where the PRD was ambiguous. Kane CLI uses real-browser discovery on an initial run, inspecting page structure and logs to resolve natural-language test steps without explicit selectors, then replays the learned actions faster in later executions. Its central claim is that coverage should reflect acceptance criteria actually proven in a specific run rather than estimated test counts, while approved criteria cannot be changed by the authoring or execution agent, intended as a safeguard against tests being altered to hide failures. The presentation described PRD updates and re-ingestion as the mechanism for managing drift, though its promised agent-integration section was not demonstrated, and an unexplained discrepancy remained between the 13 criteria generated for the example use case and the evidence screen’s reported denominator of 15.

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