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Claim check:

• The New Stack published a guide on how to build repeatable AI-agent evaluation into the delivery process. The article explains why a successful demonstration is not enough to make a release decision. (not found in the primary source)
• The article says that an agent answering several test questions successfully does not prove that the next version will preserve the behavior users and operators need after changes to the retrieval configuration or model. (not found in the primary source)
• To pass a release gate, an evaluation must reproduce a run or a material regression in a high-risk scenario. A repeatable evaluation system runs fixed scenarios through the product execution path and gathers evidence for a release decision. (not found in the primary source)
• The evaluation must test the code that assembles context, the tools available for the agent to call, and the permissions applied by the runtime. (not found in the primary source)
• Before choosing a tool and writing tests, the author recommends describing the agent’s tasks, the constraints for each task, and unacceptable outcomes. For a support agent, an example is an answer using data from the correct account with a valid link to the policy, no ability to change a plan or disclose another customer’s data, and acknowledgment of the gap when a policy is unavailable. (not found in the primary source)

Primary sources:

• https://thenewstack.io/ai-agent-evaluation-gates

score 62.4 · kind guide · revision 1 · stories st-1gnyj8u