Research

AgentNexus Research / May 4, 2026 / 6 min read

Scenario-based evaluation for agent reliability

A practical framework for testing whether an AI agent completes the right workflow under realistic constraints.

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EvaluationReliabilityQA

Scenario evaluation turns vague trust into observable checks: task completion, source use, tool boundaries, recovery behavior, and human escalation paths.

AgentNexus ResearchMay 4, 20266 min read

Research question

How can teams evaluate an AI agent in a way that reflects real product use rather than isolated prompt quality?

Method

  • Define a small set of representative user scenarios.
  • Attach expected artifacts or decisions to each scenario.
  • Capture browser, API, and tool-failure signals where relevant.
  • Score completion, correctness, recovery, and escalation behavior.

Product implication

Agent evaluation should be visible enough for non-technical owners to understand and structured enough for engineering teams to repeat.

Artifacts

Method notes become product checks

Research notes should feed repeatable evaluation cases, docs updates, and launch review guidance.

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