Best practices for incorporating prompt evaluation into your team’s development lifecycle.
Effective prompt evaluation isn’t just about running tests; it’s about integrating the process into your team’s regular development and deployment workflows. Here are some strategies:
Live Evaluations: Enable live evaluations for critical metrics (e.g., format validation, safety checks, basic relevance) to monitor real-time performance.
Regular Review Meetings: Discuss evaluation trends and results as a team.
Analyze Failures: Dig into logs with poor evaluation scores to understand the root causes.
Leverage Suggestions: Use the Prompt Suggestions feature to guide improvements.
Update Golden Dataset: Periodically add new challenging examples or successful edge cases from production logs to your golden dataset.
Refine Evaluations: Adjust evaluation criteria or prompts as your understanding of quality evolves.
By embedding these practices, your team can systematically ensure prompt quality, reduce regressions, and continuously improve the reliability and performance of your AI applications.