WEBVTT

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The evolving role of software testing in AI development

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Avoiding the trap of AI self-verification loops

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Four essential jobs of a high-quality test

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Providing unambiguous testing signals to AI agents

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Identifying lying tests and avoiding false operational confidence

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Defining precise behavior scenarios to prompt coding agents

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Decoupling test behavior from specific implementation details

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The critical importance of observing a test fail

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Comparing human-led versus AI-led test ownership

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Tests as structured operational memory for coding agents

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Managing AI token costs through strategic test design

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Preventing AI scaling traps and excessive code mocking

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Retaining human intent while delegating software implementation

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Enforcing behavioral testing patterns in AI development tools