
2 min read
Why most AI agent demos do not survive contact with production workflows
The gap between agent demos and production workflows comes from context quality, task realism, and the absence of repeatable evaluation.
By Agent Software
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The gap between agent demos and production workflows comes from context quality, task realism, and the absence of repeatable evaluation.
By Agent Software

An effective agent eval harness needs scenario design, clear pass criteria, and enough operational realism to catch regressions that demos hide.
By Agent Software

Agent systems feel unreliable because most teams still evaluate them with memory, screenshots, and intuition rather than repeatable tests.
By Agent Software