Testing Your AI Peers with the Evaluation System
Building a Peer is only the first step. To trust it in real workflows, teams need a repeatable way to test whether answers are accurate, useful, and aligned with the Peer purpose.
Cognipeer evaluations help teams create test suites, run them over time, and compare results after changes.
Why evaluate Peers
Evaluations help you:
- Catch quality issues before users do.
- Compare performance across Peer versions.
- Measure whether prompt or datasource changes helped.
- Identify weak topics.
- Build confidence before a rollout.
- Reduce one-off manual testing.
What to test
Start with questions that represent real usage:
- Top customer or employee questions.
- High-risk policy questions.
- Questions that require datasource grounding.
- Questions that should trigger tools or Flows.
- Questions where the Peer should ask for clarification.
- Questions the Peer should refuse or route elsewhere.
Avoid testing only easy examples. A useful suite includes normal, edge, and failure cases.
Build a strong evaluation suite
Each evaluation item should have:
- A realistic user prompt.
- A clear expected outcome.
- Any required context.
- The topic or area being tested.
- A way to judge success.
Use smaller focused suites for frequent testing and broader suites before major releases.
Review results
When a test fails, look for the cause:
- Missing datasource content.
- Ambiguous user prompt.
- Weak Peer instructions.
- Wrong tool or Flow behavior.
- Outdated expected answer.
- Model behavior that needs clearer constraints.
The goal is not only a higher score. The goal is a Peer that users can rely on.
Use evaluations before publishing
Run evaluations before:
- Publishing a new Peer version.
- Changing core instructions.
- Adding or removing datasources.
- Changing tools or approval settings.
- Rolling a Peer out to a larger audience.
Keep the previous result as a baseline so your team can compare changes.
Team workflow
- Assign a Peer owner.
- Create a focused evaluation suite.
- Run the suite against the current Peer.
- Fix the highest-impact failures.
- Re-run the suite.
- Publish through version history.
- Review feedback and add new test cases over time.