SanctumOS Naming Rubric
SanctumOS is neuro-inspired, not neuro-identical. We mirror brain roles where it clarifies behavior (e.g., consolidation, gating, cleanup) and adopt computationally efficient mechanisms where software can outperform biology. Our invariants—provenance, append-only history, gated action selection—preserve the spirit of cognition while keeping the system debuggable and fast.
Naming Categories
Here's how we label our terminology as we develop it:
N1 – Neuro-faithful
Strong functional analogy (Hippocampus/Neocortex/Glymphatic; Basal Ganglia)
N2 – Neuro-inspired
Shape matches, mechanics diverge (Dream loop/DMN-ish)
C – Computational
No useful analogy; pure tech (UI, MCP plumbing, indexes)
SanctumOS models the human brain while remaining grounded in AI/tech conventions. To keep naming consistent and intuitive, every new component falls into one of four naming camps.
1. Global Modules → Technical Names
These are OS-level or infrastructure pieces that aren't specific to cognition.
Examples: MCP, UI, Kernel (Letta)
Naming rule: Plain tech terminology (short acronyms or descriptive engineering words)
Audience: Developers/sysadmins
Purpose: Clarity of function, not metaphor
2. Agent Modules → Neuroanatomical Names
These model functions of the human brain.
Examples: Broca (speech center), Thalamus (routing/refinement), Cerebellum (filter/reflex)
Naming rule: Single-word brain regions/networks, chosen to match function
Audience: AI/agent architects
Purpose: Reinforce the metaphor of SanctumOS as a cognitive architecture
Guideline: Choose macro-level regions (hippocampus, amygdala) rather than microanatomy, so non-specialists can still infer meaning
3. Letta/AI Extensions → Industry Terms
These are continuations of Letta or AI ecosystem concepts.
Examples: agents, tools, memory blocks, SDK
Naming rule: Preserve existing AI/ML vocabulary
Audience: Broader AI/ML community
Purpose: Leverage familiarity, avoid needless reinvention
4. Agents/Primes → Personal/Mythic Names
Agents themselves follow a distinct naming track.
Examples: Athena, Monday, Sentinel
Naming rule: Proper nouns (mythic, literary, or thematic), chosen for narrative identity
Audience: End users, collaborators
Purpose: Convey personality and individuality
Neuroanatomical Reference
| Brain Region | SanctumOS Component | Function | |--------------|-------------------|----------| | Thalamus | Input Preprocessing Hub | Routing, refinement, sensory relay | | Cerebellum | Real-time Filter | Reflex processing, motor control | | Basal Ganglia | Task Orchestrator | Action selection, habit formation | | Hippocampus | Memory Consolidation | Short-term to long-term memory | | Neocortex | Knowledge Integration | Complex reasoning, pattern recognition | | Glymphatic System | Memory Optimization | Waste clearance, memory pruning | | Broca's Area | Communication Layer | Language production, message processing |
Deeper Reasoning
The why of this rubric is as important as the rules:
Cognitive Fidelity
SanctumOS is not just an agent system — it's a cognitive OS. By naming agent modules after brain regions, we preserve the metaphor that "this is a brain," not just software stitched together. That makes the architecture intuitive, teachable, and extensible.
Division of Concerns
- Tech names (MCP, UI, Kernel) = engineering plumbing
- Neuro names = cognition, perception, memory
- Industry names = AI standards everyone already recognizes
- Mythic names = personality and identity
This prevents namespace collision and tells new developers immediately "what layer they're working on."
Scalability of Metaphor
The brain has many regions, but only ~10–15 high-level ones matter for modeling cognition. That's enough to cover SanctumOS's foreseeable roadmap without getting too esoteric. If a module feels shoehorned, that's a clue it may not be core cognition.
Recruitment & Onboarding
New contributors immediately see "Thalamus → routing," "Hippocampus → memory consolidation," and understand the metaphor without reading 50 pages of docs. It's sticky and pedagogical.
Future-proofing
As SanctumOS grows, we can always extend into new brain regions (limbic system, cortex layers, etc.) without breaking convention. If something doesn't map naturally to neuroanatomy, it probably belongs in the tech or industry bucket instead.
Implementation Guidelines
When to Use Each Category
Use Neuroanatomical Names When:
- The component directly models a brain function
- The analogy helps users understand behavior
- The component is part of core cognitive architecture
- The function maps clearly to a well-known brain region
Use Technical Names When:
- The component is infrastructure or plumbing
- No clear brain analogy exists
- The component is OS-level or system-level
- Clarity of function is more important than metaphor
Use Industry Terms When:
- Extending existing AI/ML concepts
- Maintaining compatibility with broader ecosystem
- The component follows established patterns
- Familiarity aids adoption
Use Mythic Names When:
- Creating agent personalities
- Naming user-facing entities
- Building narrative identity
- Conveying character and individuality
Naming Best Practices
- Consistency: Stick to the category once chosen
- Clarity: Names should immediately suggest function
- Scalability: Leave room for future expansion
- Accessibility: Avoid overly technical neuroanatomy
- Memorability: Choose names that are easy to remember and pronounce
Examples in Practice
✅ Good Examples
- Thalamus: Clear brain analogy for input routing
- Basal Ganglia: Well-known for action selection
- MCP: Standard technical acronym
- Athena: Strong mythic identity for main agent
❌ Avoid These
- Prefrontal Cortex: Too specific, not macro-level
- Neural Network: Generic, doesn't specify function
- Agent-1: No personality or meaning
- Thalamus-Processor: Redundant, breaks single-word rule
Related Documentation
- Architecture Overview: Complete system architecture
- Components: Detailed component documentation
- Development Guidelines: How to contribute to SanctumOS
SanctumOS Naming Rubric - Maintaining cognitive fidelity while building practical AI systems.