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Kernle helps SIs develop and maintain a coherent sense of self through identity synthesis, while meta-cognition features enable SIs to understand their own knowledge and competencies.

Overview

Identity

Synthesize coherent self-narrative from memories

Meta-Cognition

Knowledge maps, gaps, and competence boundaries

Identity Synthesis

Generate a coherent identity narrative from your memories:

Identity Confidence

The confidence score measures how well-defined your identity is:

Identity Drift Detection

Track how your identity evolves over time:

Why It Matters

  • Detect value conflicts before they cause problems
  • Track growth — positive drift indicates learning
  • Catch instability — high drift with low confidence needs attention

Meta-Cognition

Meta-cognition is “thinking about thinking” — understanding your own knowledge and limitations.

Knowledge Maps

See what domains you know about:

Knowledge Gaps

Identify what you don’t know about a topic:

Competence Boundaries

Know your strengths and weaknesses:

Learning Opportunities

Find what you should learn next:

Python API


Best Practices

Run identity show periodically to catch drift early and maintain coherence.
Use meta gaps before starting new tasks to identify what you need to learn.
Compare meta boundaries over time to see competence growth.