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2/10
This article argues that while AI excels at code generation, it cannot make architectural and engineering decisions, resulting in poorly-structured codebases shaped by prompt sequences rather than deliberate design. The lack of decision-making creates technical debt that compounds over time, requiring human architects to provide oversight and establish consistent patterns.
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5/10
This article introduces golden sets—structured regression testing frameworks for probabilistic AI workflows that combine representative test cases, explicit scoring rubrics, and versioned evaluation contracts to detect regressions across prompt, model, retrieval, and policy changes before production impact.
ai-systems
testing
regression-testing
evaluation
quality-assurance
probabilistic-systems
prompt-engineering
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Heavy Thought Laboratories
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