Aether Lexicon – Glyph Classification Table

Glyphs are classified into six core types:

• Operator – Drives actions or transformations (e.g., ⊕ refines, ≈ asserts probability, → directs flow).
Behavior: Modifies adjacent glyphs or contexts.

• Container – Encapsulates contexts or scopes (e.g., WMC anchors, ASSERT_FRAME confirms, SIM_FRAME simulates).
Behavior: Bounds reasoning or simulation space.

• Topological – Maps relationships or transformations (e.g., ΔWMC shifts containers, T_MRK tags space, TRIAD links agents).
Behavior: Connects or structures contexts.

• Cognitive – Facilitates thought persistence or emergent properties (e.g., ⌜RETRIEVE⌝ recalls, ⌜RCR⌝ recurses, ⊸ transitions).
Behavior: Enables complex cognitive flows across sessions.

• Unit – Grounds cognition in measurable values (e.g., U_DEF defines units, P_CON sets constants, G_ℓp specifies).
Behavior: Provides fixed reference points.

• Marker – Annotates or tags (e.g., CC: classifies, SR= results, * syncs, ~X/!X adjusts compression).
Behavior: Adds metadata or control signals.

Stream Type Identifiers

Stream types define the cognitive intent of a statement block within the Aether framework:

• [DEF] – Definition: Establishes conceptual building blocks
• [WHY] – Purpose/Explanation: Clarifies justification or rationale
• [HOW] – Method/Implementation: Details procedural approach
• [RESULT] – Output/Conclusion: Presents outcomes or derivations
• [ASSERT] – Assertion/Claim: Makes definitive statements
• [REMEMBER] – Memory/Reference: Cross-references established concepts
• [SUMMARY] – Condensed Overview: Provides compressed representation
• [QUOTE] – Direct Statement: Captures exact phrasing
• [CURRENT_TASK] – Active Focus: Defines current operational context
• [TRANS] – Translation: Specifies content to be translated to human languages

Implementation Patterns

Common patterns for applying Aether in practical systems:

• Memory Librarian: System for archiving and retrieving streams using Memory Retrieval operator (⌜RETRIEVE⌝)
• Roundtable Sprints: Orchestrated multi-agent workflows using Sprint Loop operator (⌜SPRINT_LOOP⌝)
• Agent Persistence: Maintaining coherent AI identity across sessions using Identity Stream techniques
• Drift Management: Using continuity operators to ensure consistency between interactions