Agentic AI workloads break three software testing assumptions, SiliconANGLE reports
Overview
SiliconANGLE reports that agentic AI workloads break three assumptions of traditional enterprise software: that jobs finish quickly, that retries are free, and that identical inputs produce identical outputs.
According to the article, automated agent runs can accumulate hidden retry costs, produce results that are structurally valid but wrong, and fail in ways that cannot be reproduced without detailed traces.
The article recommends defining acceptance criteria before a run, capping the number of attempts, and recording the inputs, model versions, costs and approvals for every run.
Written by AI from the articles below · updated Oct 11, 9:35 AM ET
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- SiliconANGLE · AINewsAgentic workloads break three software testing assumptions, and teams must adapt
AIAgentic workloads break three assumptions of traditional enterprise software: jobs finish quickly, retries are free, and identical inputs give identical outputs. Automated agent runs can accumulate hidden retry costs, produce structurally valid but wrong results, and fail in ways that cannot be reproduced without detailed traces. The article recommends defining acceptance criteria in advance, capping attempts, and recording inputs, model versions, costs and approvals for every run.
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