Evaluation Loops for LLM Workflows

Without evaluation loops, teams learn about model drift from angry users.

Evaluate against real tasks

Synthetic tests are helpful, but the best evaluation sets usually come from the workflow itself:

• difficult edge cases
• examples that triggered human overrides
• recent customer escalations
• known policy-sensitive requests

This keeps evaluation aligned with the work that actually matters.

Close the loop every week

An evaluation loop should lead to a decision:

1. keep the current system
2. adjust prompts or routing
3. change the context inputs
4. pause a release

If the loop does not change behavior, it is only reporting.

Share evaluation results across functions

LLM quality is not just an engineering concern. Operators, support leaders, and product owners should all understand what the evaluation is saying, because they feel the consequences first.