Lesson 1234 of 1596
Agentic AI: building an eval harness before scaling the agent
A frozen set of input scenarios with graded outcomes is the only way to know if your agent got better or worse with each change.
Creators · Agentic AI · ~7 min read
The premise
Without an eval harness, every prompt change is a vibe-based decision. With one, you can measure whether a model swap or prompt edit actually improved success rate or just shifted which cases fail.
What AI does well here
- Run against a fixed scenario list when one is provided
- Output structured results that map to scenario IDs
- Be deterministic enough to score with temperature 0
What AI cannot do
- Generate the scenarios that matter to your business
- Decide what 'pass' means for an open-ended task
- Replace human judgment on subjective outputs
Key terms in this lesson
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