Trustworthy & Reliable AI

Agent Reflection & Learning

Show users what the agent has learned from corrections so trust builds through visible, cumulative improvement.

What is Agent Reflection & Learning?

Agent Reflection surfaces the agent's learning history: corrections absorbed, mistakes acknowledged, behavior changed. Without it, users repeat corrections indefinitely and assume the agent is broken, not improving.

Example: ChatGPT Memory

ChatGPT memory panel listing saved details about the user with controls to delete individual memories

Explicitly surfaces what it has stored about the user and lets them delete individual memories, making learning visible and controllable.

AI Design Prompt

Want to learn more about this pattern?

Explore the full pattern with real-world examples, implementation guidelines, and code samples.

View Full Pattern

Related Prompts from Trustworthy & Reliable AI