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This episode examines the transition to rubric-based AI evaluation and its importance for assessing model reasoning. We discuss how adversarial benchmarks like Poker Arena and new agentic testing integrations are redefining QA for autonomous systems. These methodologies provide a structured path for testers to build more accurate, self-improving quality frameworks.
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In the previous parts we covered the project and the problem, reactive work and the s...
There's a version of Quality's future being written right now, and most of it is being written by people who are stuck in the state of "this is how it's always been done".
Vendors are deciding what your job is. Executives are deciding how many of you they need. AI tools are getting deployed into pipelines by people who've never sat with a flaky test at 11pm trying...
…also don’t tell lies. But I’m getting ahead of myself already. I keep running into people online who openly say that they use AI to do their writing for them. Now, technically, they may say they use AI to “help” their writing. It doesn’t matter. The distinction is immediately lost on everyone who sees that […]
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This episode examines the industry’s move toward production-realistic testing for AI applications. We cover OpenAI’s deployment simulation patterns, new strategies for testing AI agent security, and frameworks for benchmarking models against specific production toolsets.
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