Error Recovery & Graceful Degradation
Problem
AI systems inevitably make mistakes or encounter unhandleable situations, potentially frustrating users.
Solution
Design graceful degradation and clear recovery paths to maintain user trust when AI fails.
Examples in the Wild
Interactive Code Example
Implementation & Considerations
Implementation Guidelines
Provide clear indicators when AI confidence is low or uncertain.
Offer multiple recovery options when primary AI solutions fail.
Make error states informative, not just generic messages.
Allow users to easily bypass AI and use manual alternatives.
Learn from failures to improve future AI performance.
Design Considerations
Maintain user trust even when AI systems make mistakes.
Ensure critical functions have reliable non-AI backup options.
Provide appropriate user education about AI limitations.
Design recovery flows that don't frustrate or confuse users.
Consider the safety implications of AI failures in critical applications.