Continuous Feedback and Improvement › Learning from Success Too

Michael BrenndoerferAugust 4, 20251 min read
AI Agent HandbookAll chapters
Part 11 of 15Evaluation - Measuring Your Agent's Performance
Chapter 32Continuous Feedback and Improvement › Learning from Success Too
Reading section 7 of 12 · Learning from Success Too · 1 minSection 7 of 12 · 1 min

Book contents

Section 7 of 12 · 1 min read

Continuous Feedback and Improvement › Learning from Success TooOne section · Sections in this chapter7 / 12 ↓

Don't only focus on failures. Pay attention to what your agent does well. When users give positive feedback or an interaction goes particularly smoothly, that's valuable information too.

Maybe you notice that your agent handles scheduling requests exceptionally well, but struggles with information lookup tasks. This tells you where the agent's strengths are. You might decide to emphasize the scheduling capabilities in how you present the assistant to users, and focus improvement efforts on information lookup.

Or perhaps you find that when the agent explains its reasoning to users ("I'm checking your calendar first, then I'll look up the weather"), users are more satisfied even when the final answer takes longer. This suggests adding more transparency about the agent's process.

Success patterns can guide you toward doing more of what works, not just fixing what doesn't.