/behavioral-consistency

name: behavioral-consistency
description: Ensuring the AI behaves predictably across sessions, edge cases, and modalities.

Behavioral Consistency

Users build mental models of how the AI behaves. Consistency is what makes those models reliable. Inconsistency — even if each individual response is good — erodes trust.

Dimensions of Consistency

• **Across sessions**: The AI should behave the same way whether it's the user's first conversation or their hundredth
• **Across topics**: Switching subjects shouldn't change the AI's personality or approach
• **Across modalities**: The AI should feel the same in chat, voice, and email
• **Across users**: Different users get the same quality and character (unless personalisation is designed)
• **Across time**: The AI shouldn't randomly change behavior after updates without user awareness

Sources of Inconsistency

• **Temperature and sampling**: Randomness in generation creates natural variation
• **Context sensitivity**: Different conversation histories lead to different behaviors
• **Prompt drift**: System prompts evolve over time without consistency checks
• **Edge cases**: Unusual inputs trigger unpredictable responses
• **Model updates**: New model versions may shift behavior subtly

Designing for Consistency

• **Behavioral specifications**: Document expected behavior for common and edge-case scenarios
• **Golden responses**: Maintain a library of reference responses that define the standard
• **Regression testing**: When anything changes, test against the golden response library
• **Consistency metrics**: Track behavioral variance across sessions and users
• **User expectations**: Set and maintain expectations about what the AI does and how

Consistency vs. Adaptation

Consistency doesn't mean rigidity. The AI should adapt to:

• User preferences (if designed for personalisation)
• Contextual needs (tone shifts as discussed in tone-calibration)
• Learning from feedback (if memory systems exist)

The key is that adaptation should be predictable and explainable, not random.

Design Artefacts

• Behavioral specification documents
• Golden response libraries
• Regression test suites
• Consistency monitoring dashboards
• Adaptation rules (what changes and what stays constant)