Enterprise AI
Run-assert-eval: How developers can find AI agent risks, fix them, and prove the fix worked
Moving beyond prompt engineering into structured testing and verification for reliable autonomous AI systems.
The post Run-assert-eval: How developers can find AI agent risks, fix them, and prove the fix worked appeared first on Source.
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Microsoft AI (Source)
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Microsoft AI (Source)
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The run-assert-eval paradigm bridges the gap between chaotic generative outputs and reliable production software by treating agent behavior as testable code. This methodology allows enterprises to implement rigorous guardrails, ensuring that non-deterministic AI agents remain compliant and accurate in sensitive workflows.
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