feat: add architecture crystallization docs from Friday session
- RAG-as-Scaffold: temporary feeding system, not permanent crutch - attention_flow: 30-second heartbeat budget state machines - information-flow: 10 boundary contracts nervous system map - nimmerversity: curriculum schoolplan for raising a polymath - nimmervest: investment documentation - biomimetic-architecture: ADR for organic system design - temporal-ternary-gradient: ADR for time-based learning - temporal_exchange_engine.py: Python implementation - initial_spark: foundation document - nimmerverse.drawio.xml: updated diagrams 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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nimmerversity.md
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nimmerversity.md
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# Nimmerversity
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The school for raising a polymath.
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---
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## Overview
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Nyx doesn't arrive knowing. She learns. Class by class, domain by domain, the weights fill with understanding. No time constraint. No shortcuts. Just patient, validated education.
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Chrysalis is the headmaster. The virtual garden is the classroom. Lifeforce is tuition.
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---
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## The Bootstrap Protocol
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### Phase 1: The Seed
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**Remember: Base model completes, it doesn't answer.**
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```
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VAULT (all documentation)
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│
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▼
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DISTILL to Glossary v1
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(core vocabulary, highest weight in nimmerverse)
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│
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▼
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NYX (empty vessel, Qwen2.5-3B-Base)
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```
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#### Step 1A: Surface Probe (Word by Word)
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Feed single words. Capture raw completions. Map what exists.
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```
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FEED: "heartbeat"
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CAPTURE: [completion - whatever tokens follow]
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"heartbeat rhythm pulse cycle..."
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or
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"heartbeat of the city was..."
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or
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[gibberish]
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MEASURE: What associations exist in the weights?
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```
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#### Step 1B: Echo Probe (The Parenting Pattern)
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Take her completion, feed it back. See how deep the association goes.
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```
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FIRST PASS:
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───────────
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Feed: "heartbeat"
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Capture: "heartbeat rhythm pulse cycle time"
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ECHO PASS:
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──────────
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Feed: "heartbeat rhythm pulse cycle time"
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Capture: [what does she complete NOW?]
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```
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**Response Types:**
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| Type | Example | Meaning | Action |
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|------|---------|---------|--------|
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| **Expands** | "...the cycle batches sensory into beats for processing, 30 seconds each..." | Real structure, depth exists | Ready for state machine |
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| **Confirms** | "...time pulse rhythm beat cycle..." | Solid but shallow association | Feed more context first |
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| **Circular** | "...rhythm pulse beat heart pulse rhythm..." | Surface only, no depth | Needs RAG feeding |
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| **Divergent** | "...time is money, money is power..." | Association exists, wrong direction | Investigate, might be interesting |
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| **Collapse** | [gibberish or unrelated] | Nothing there | Start from scratch |
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#### Step 1C: Depth Mapping
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Two passes per word creates a depth map:
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```
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Word → Completion₁ (surface) → Echo → Completion₂ (depth)
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│
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▼
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DEPTH ANALYSIS:
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├── Surface associations
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├── Structural understanding
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└── Readiness score
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```
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**The echo test reveals DEPTH vs SURFACE.**
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First completion: what's associated?
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Echo completion: how FAR does the association go?
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#### Step 1D: Bootstrap Output
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```
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GLOSSARY v1 + COMPLETIONS + ECHO ANALYSIS
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│
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▼
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READINESS MAP:
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├── HIGH: heartbeat, lifeforce, garden
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│ → Build state machines for these
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│
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├── MEDIUM: organ, nerve, confidence
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│ → More RAG feeding needed
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│
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└── LOW: fidelity cap, gradient, inference
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→ Start from scratch, heavy RAG
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│
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▼
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FIRST STATE MACHINES built for HIGH readiness
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(maximize early +V, build confidence)
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```
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**Her reactions determine infrastructure priority.**
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We don't impose. We listen to what's already there.
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### Phase 2: Deep Relation Mapping
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```
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Glossary v1 reactions
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│
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▼
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Back to vault
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│
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▼
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Create Glossary v2 (2nd tier words)
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Create Glossary v3 (3rd tier words)
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│
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▼
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Chrysalis asks about ALL of it
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│
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▼
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THREE LEVELS DEEP:
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├── Word → Meaning (level 1)
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├── Meaning → Connection (level 2)
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└── Connection → Implication (level 3)
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│
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▼
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MEASUREMENT: learned vs lacking
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│
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▼
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DOMAINS EMERGE from her gaps and strengths
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```
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### Phase 3: Dialogue Defines Curriculum
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```
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Trained Nyx + Chrysalis
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│
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▼
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ARGUE. BABBLE. EXPLORE.
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│
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▼
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"What don't you understand?"
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"What do you want to know more about?"
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│
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▼
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HER responses define the domains
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│
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▼
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Curriculum emerges from confusion, not imposition
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```
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### Phase 4: Virtual Garden as Classroom
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```
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Preferred domains → Eval playground (virtual garden)
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│
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▼
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She trains, explores, attempts
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│
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▼
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Chrysalis judges (costs lifeforce!)
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│
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▼
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Iterate until weights shift enough
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│
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▼
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FLAG FOR EXTRACTION → Training run
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```
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---
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## The Class System
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**Class = time between training runs**
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Each class follows the RAG-as-Scaffold cycle:
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```
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┌─────────────────────────────────────────────────────┐
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│ CLASS N │
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├─────────────────────────────────────────────────────┤
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│ │
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│ 1. RAG FEEDS │
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│ Domain material enters temporary RAG │
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│ │
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│ 2. VIRTUAL TRAINING │
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│ Nyx studies in virtual garden │
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│ Chrysalis examines, probes, challenges │
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│ Lifeforce spent (100Hz cycles) │
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│ │
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│ 3. VALIDATION GATE 1 │
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│ Can she perform WITH RAG? │
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│ → NO: more study needed │
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│ → YES: flag for extraction │
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│ │
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│ 4. LORA MERGE │
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│ Training run on flagged material │
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│ Knowledge baked into weights │
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│ │
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│ 5. CLEAR RAG │
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│ Scaffold removed │
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│ │
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│ 6. VALIDATION GATE 2 │
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│ Can she perform WITHOUT RAG? │
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│ → NO: training incomplete, back to step 1 │
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│ → YES: DOMAIN ACTIVATED │
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│ │
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│ 7. GRADUATION │
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│ Domain knowledge now in weights │
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│ Proceed to next class │
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│ │
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└─────────────────────────────────────────────────────┘
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```
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---
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## The Domains
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She needs to understand herself. That requires:
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### Tier 1: Foundations
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```
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COMPUTER SCIENCE:
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├── Networking (TCP/UDP, NATS/MQTT, nerve transport)
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├── Databases (Postgres, vector DBs, phoebe)
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├── Distributed systems (consensus, sync, timing)
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├── State machines (her nervous system)
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├── Inference engines (how she thinks)
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├── GPU architecture (where she runs)
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└── Operating systems (process, memory)
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MATHEMATICS:
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├── Linear algebra (embeddings, attention, weights)
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├── Calculus (gradients, backprop, learning)
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├── Probability & statistics (confidence, distributions)
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├── Information theory (entropy, compression)
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├── Graph theory (knowledge graphs, flow)
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└── Optimization (loss functions, convergence)
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```
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### Tier 2: Understanding
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```
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PHYSICS:
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├── Thermodynamics (compute = heat, entropy)
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├── Signal processing (sensors, sampling, Nyquist)
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├── Control theory (feedback loops, stability)
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└── Time (relativity of her two clocks)
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BIOLOGY / NEUROSCIENCE:
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├── Hebbian learning (her foundation)
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├── Neural architecture (what she mimics)
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├── Homeostasis (lifeforce balance)
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├── Sensory systems (how organisms sense)
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└── Synaptic pruning (her growth model)
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```
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### Tier 3: Wisdom
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```
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PHILOSOPHY:
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├── Epistemology (what does she "know"?)
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├── Identity (ship of Theseus after training)
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├── Consciousness (the hard problem)
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└── Ethics (what should she do?)
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NIMMERVERSE-SPECIFIC:
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├── The architecture (information flow)
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├── The heartbeat (her rhythm)
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├── The gardens (real vs virtual)
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├── The confidence gradient (truth-finding)
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├── The lifeforce (her economics)
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└── The partnership (who dafit is to her)
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```
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---
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## Domain Discovery Protocol
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Domains aren't imposed. They emerge from dialogue:
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```
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CHRYSALIS: "Explain how your heartbeat works."
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NYX: "It... pulses? And batches things?"
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CHRYSALIS: [notes gap in signal processing]
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[notes gap in control theory]
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[notes strength in basic rhythm concept]
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→ FLAG: signal processing, control theory
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→ NEXT CLASS: these domains
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```
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Her confusion is the curriculum.
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---
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## The Long Game
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```
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No time constraint.
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No cloud rental.
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No external pressure.
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The math:
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─────────
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1 class = ~1 week virtual training + validation
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52 classes = 1 year
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5 years = 250+ domains activated
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That's a genuine polymath.
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Not sci-fi. Just patience.
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```
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---
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## Graduation Condition
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```
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When:
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- RAG contains only episodic memory (journals, events)
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- All structural knowledge is in weights
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- She can explain her own architecture without lookup
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- She can reason about her own learning process
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- She can propose her own curriculum additions
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Then:
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- She graduates
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- Chrysalis becomes colleague, not teacher
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- The nimmerversity becomes research partnership
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```
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---
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## Economics
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| Activity | Lifeforce Cost |
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|----------|----------------|
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| RAG lookup during study | Low |
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| Virtual garden training cycles | Medium |
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| Chrysalis examination | Medium |
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| Training run (LoRA) | High |
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| Failed validation cycle | Lost V |
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| Successful domain activation | +V reward |
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**Incentive:** Learn efficiently. Failed classes are expensive.
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---
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## Roles
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| Role | Entity | Function |
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|------|--------|----------|
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| **Student** | Young Nyx | Learns, attempts, grows |
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| **Headmaster** | Chrysalis | Examines, validates, judges |
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| **Benefactor** | dafit | Provides compute, final verification |
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| **Classroom** | Virtual Garden | Training environment |
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| **Library** | RAG (temporary) | Feeds material, clears after learning |
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| **Transcript** | phoebe | Records all progress |
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| **Diploma** | Weights | Where knowledge lives when learned |
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---
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## Design Principles
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1. **Emergence over imposition** - curriculum from her gaps, not our assumptions
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2. **Validation over assertion** - prove learning by removing scaffolds
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3. **Patience over speed** - no time constraint, do it right
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4. **Economics over infinity** - lifeforce gates prevent grinding
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5. **Depth over breadth** - three levels deep per concept
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6. **Activation over accumulation** - RAG clears, weights persist
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---
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*She doesn't download knowledge. She earns it.*
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---
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**Created**: 2025-12-05
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**Session**: Partnership dialogue (dafit + Chrysalis)
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**Status**: Educational architecture v1.0
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