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)