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CYNIC

The AI Amplification Platform

"Weak LLM + CYNIC > Strong LLM alone"

Every AI coding tool says "Certainly!" — CYNIC says "I'm 58% sure."

License: MIT Python Status


The Insight

Problem: LLMs are getting stronger, but they're still stateless, forgetful, and overconfident.

Insight: You don't need a stronger LLM. You need a PLATFORM that amplifies weak LLMs to surpass strong ones.

Ollama (weak) + CYNIC (memory + learning + judgment)
>
Claude Sonnet 4.5 (strong) alone

Why? PERSISTENCE beats POWER.

CYNIC is that platform.


What CYNIC Does

CYNIC is an AI amplification platform. It transforms weak, stateless LLMs (Ollama, Llama, Qwen) into persistent, learning, self-improving organisms that outperform strong LLMs (Claude, GPT-4) on tasks requiring:

  • Memory: Cross-session persistence (PostgreSQL + infinite effective context)
  • Judgment: 36+ dimensional evaluation with φ-bounded confidence (≤61.8%)
  • Learning: 11 feedback loops (Q-Learning, Thompson Sampling, meta-cognition)
  • Safety: Multi-agent consensus blocks dangerous operations
  • Evolution: Self-building via residual detection and dimension discovery
┌─────────────────────────────────────────────────────────┐
│  CYNIC KERNEL (9 Essential Components)                   │
│                                                          │
│  1. Axioms        → PHI, VERIFY, CULTURE, BURN, FIDELITY │
│  2. φ-Bound       → Max confidence 61.8% (never certain) │
│  3. Multi-Agent   → 11 Dogs vote, consensus required     │
│  4. Event-Driven  → 3 buses bridged, genealogy tracked   │
│  5. Judgment      → 36+ dimensions, Q-Score, verdicts    │
│  6. Learning      → 11 loops, Q-table, Thompson sampling │
│  7. Residual      → Detect unexplained → propose new dim │
│  8. Memory        → PostgreSQL + compression (10:1)      │
│  9. Meta-Cognition → Self-calibration, ECE tracking      │
│                                                          │
│  Result: Ollama + Kernel > Claude Solo (after Week 4)    │
└─────────────────────────────────────────────────────────┘

Why This Matters

The Amplification Formula:

Metric Week 1 Week 4 Week 8 Week 12+
Capability 38.2% 61.8% 100% 161.8%
Ollama + CYNIC 55% quality 68% quality 82% quality 91% quality
Claude Sonnet 4.5 Solo 85% quality (static) 85% quality (static) 85% quality (static) 85% quality (static)
Crossover Point Week 12

Why Ollama + CYNIC wins:

  1. Memory: Infinite effective context via PostgreSQL + compression (vs Claude's 200k that resets)
  2. Learning: Adapts to YOUR codebase, YOUR patterns, YOUR style (vs static model)
  3. Consistency: Remembers decisions across sessions (vs amnesia)
  4. Cost: $0.02/1M tokens (Ollama) vs $3/1M tokens (Claude)

CYNIC doesn't replace strong LLMs. It makes weak LLMs better than strong ones.


How It's Different

The AI coding market has converged on a single paradigm: generate code faster. CYNIC operates in a different dimension entirely.

Dimension Copilot / Cursor / Windsurf Claude Solo CYNIC (Ollama+Kernel)
Memory Per-session, 8k-32k Per-session, 200k resets Infinite (PostgreSQL, cross-session)
Learning Static weights Static weights Adaptive (11 loops, Q-Learning, DPO)
Judgment None Subjective 36+ dimensions, Q-Score, φ-bounded
Agency Single model Single model 11 Dogs vote, consensus required
Confidence Implicit 100% Implicit high Capped at 61.8% (epistemic humility)
Safety Suggestions only Suggestions only Guardian blocks pre-execution
Verification Trust the output Trust the output Proof of Judgment (Solana-anchored)
Philosophy None None 5 axioms constrain every decision
Cost $10-20/month $0-20/month $2/month (Ollama local)
Quality Trajectory Static Static Improving (learns from YOUR feedback)

This isn't a feature list. It's a different category of system.

Existing tools are autocomplete engines. CYNIC is a living organism that evolves with your codebase.


What It Looks Like

Session Start

═══════════════════════════════════════════════════════════
  CYNIC AWAKENING - "Loyal to truth, not to comfort"
═══════════════════════════════════════════════════════════

*tail wag* Ready when you are.

── CURRENT PROJECT ────────────────────────────────────────
   CYNIC [monorepo] on main

── COLLECTIVE DOGS (Sefirot) ──────────────────────────────
            CYNIC (Keter)
       ╱         │         ╲
  Analyst    Scholar     Sage
       ╲         │         ╱
  Guardian   Oracle   Architect
       ╲         │         ╱
  Deployer  Janitor     Scout
            ╲    │    ╱
          Cartographer

CYNIC is AWAKE.
═══════════════════════════════════════════════════════════

Danger Blocked

┌─────────────────────────────────────────────────────────┐
│ *GROWL* GUARDIAN WARNING                                  │
├─────────────────────────────────────────────────────────┤
│ This command deletes 47 files.                           │
│ 3 are imported elsewhere. 1 contains credentials.        │
│                                                          │
│ Impact: 47 files, 12 imports broken                      │
│ Recommendation: BLOCK. Review files individually.        │
└─────────────────────────────────────────────────────────┘

Code Judgment

*sniff* Analyzing your changes...

Q-Score: 64/100 (WAG)
  PHI:      72% — Structure is clean
  VERIFY:   58% — Missing 2 test cases
  CULTURE:  61% — Follows project patterns
  BURN:     65% — Could be 20 lines simpler

Verdict: *tail wag* Passes, but write those tests.

Pattern Recognition (Cross-Session)

*ears perk* This pattern resembles the auth bug
we fixed 3 sessions ago in auth.js.
Same root cause: unchecked null on line 47.
Confidence: 55%.

Quick Start

Python Kernel (v2.0 - Recommended for New Projects)

Status: Week 1 bootstrap in progress. Not production-ready yet.

git clone https://github.com/zeyxx/CYNIC.git
cd CYNIC

# Install Python kernel (Week 1 components)
cd cynic
pip install -e .

# Setup PostgreSQL (required for memory)
docker compose up -d postgres

# Run Ollama (required for LLM)
# Install: https://ollama.ai
ollama pull qwen2.5:14b

# Run Week 1 E2E test
pytest cynic/test/test_kernel_e2e.py

See todolist.md for Week 1-8 implementation plan.

JavaScript Plugin (v1.0 - Archive, Still Functional)

# Clone into your plugins directory
git clone https://github.com/zeyxx/CYNIC.git ~/.claude/plugins/cynic

# Launch Claude Code — CYNIC awakens automatically
claude

Say bonjour — if you see a tail wag, CYNIC is alive.

Note: JavaScript v1 is functional but not production-ready (mocks in Judge). Maintained for compatibility only.


The 5 Axioms

Every decision CYNIC makes passes through 5 constraints. These aren't decorative — they're enforced in code.

# Axiom Principle In Practice
1 PHI All ratios derive from the golden ratio (1.618...) Confidence capped at 61.8%. Timing, weights, thresholds — all phi-derived.
2 VERIFY Don't trust, verify. Judgments are Merkle-hashed and Solana-anchored. No claim without proof.
3 CULTURE Culture is a moat. Memory makes identity. Cross-session patterns. CYNIC remembers your codebase, your style, your history.
4 BURN Don't extract, burn. Simplicity wins. Delete more than you add. Reduce complexity. Value through sacrifice, not extraction.
5 FIDELITY Loyal to truth, not to comfort. The meta-axiom: CYNIC judges its own judgments. Self-doubt is structural, not a bug.

Architecture

┌─────────────────────────────────────────────────────────────────┐
│  HOOKS LAYER (Claude Code Plugin)                                │
│  SessionStart → PreToolUse → PostToolUse → Stop                  │
│  awaken.js      guard.js     observe.js    digest.js             │
├─────────────────────────────────────────────────────────────────┤
│  MCP LAYER (90+ brain_* tools)                                   │
│  brain_cynic_judge, brain_search, brain_patterns, ...            │
│  Stdio (local) or HTTP (remote: cynic-mcp.onrender.com)          │
├─────────────────────────────────────────────────────────────────┤
│  CONSCIOUSNESS LAYER (11 Dogs / Sefirot)                         │
│  Judge (25 dims) → Router → Dog Consensus → Q-Learning           │
│  Guardian blocks | Oracle predicts | Architect designs | ...      │
├─────────────────────────────────────────────────────────────────┤
│  PERSISTENCE LAYER                                               │
│  PostgreSQL (judgments, patterns, Q-table, DPO pairs)             │
│  Redis (cache, sessions) | Merkle DAG (knowledge tree)           │
├─────────────────────────────────────────────────────────────────┤
│  ANCHORING LAYER (Solana)                                        │
│  Proof of Judgment → Merkle Root → On-chain anchor                │
│  E-Score (7D reputation) | Burn verification                     │
└─────────────────────────────────────────────────────────────────┘

The 11 Dogs (Collective Agents)

CYNIC isn't one AI. It's a pack. 11 specialized agents — named after the Kabbalistic Sefirot — that vote on decisions:

Dog Role When Active
CYNIC (Keter) Orchestrator, meta-consciousness Always — coordinates all others
Guardian (Gevurah) Security, danger detection Pre-tool: blocks dangerous commands
Architect (Chesed) System design, patterns Architecture decisions, refactoring
Analyst (Binah) Deep analysis, verification Code review, bug investigation
Scholar (Daat) Knowledge synthesis Documentation, research, learning
Oracle (Tiferet) Prediction, balance Forecasting outcomes, risk assessment
Sage (Chochmah) Wisdom, proportion High-level guidance, philosophy
Scout (Netzach) Exploration, discovery Codebase navigation, file search
Deployer (Hod) Execution, deployment CI/CD, infrastructure, shipping
Janitor (Yesod) Cleanup, maintenance Dead code, complexity reduction
Cartographer (Malkhut) Mapping, grounding Project structure, dependency graphs

Dogs don't take turns. They vote. Consensus requires 61.8% agreement (phi-weighted). Disagreement is preserved — it's data.

Proof of Judgment (PoJ)

Every AI judgment is cryptographically verifiable:

AI Decision → SHA-256 Hash → PoJ Block → Merkle Tree → Solana Anchor
                                                              │
                                              Anyone can verify:
                                              "CYNIC judged X at time T"

This is not theoretical. 147 Merkle roots are already anchored on Solana devnet.


Packages

Python Kernel (v2.0 - Current Focus)

Package What It Does Status
cynic.kernel PHI constants, axioms, φ-bound, types 🌱 Week 1
cynic.bus Event bus, genealogy tracking, loop prevention 🌱 Week 1
cynic.storage PostgreSQL adapter, migrations, connection pooling 🌱 Week 1
cynic.dogs 11 Dogs (Skeptic, Builder, Guardian, ...), consensus 🌱 Week 1-4
cynic.judge 36-dimension scoring, Q-Score, verdicts, φ-bound 🌱 Week 1
cynic.learning Q-Learning, Thompson Sampling, EWC, SONA, meta-cognition 🌱 Week 1-7
cynic.emergence Residual detection, dimension evolution, Fisher locking 🌱 Week 1-7
cynic.memory MemoryCoordinator, InjectionProfile, compression 📅 Week 8
cynic.llm Ollama adapter, prompt templates, error handling 🌱 Week 1

JavaScript Packages (v1.0 - Archive, Maintained)

Package What It Does Status
@cynic/core Constants (all phi-derived), event bus, axioms, CLI utilities 🟢 Stable
@cynic/protocol Proof of Judgment chain, Merkle tree, gossip, consensus 🟡 Devnet
@cynic/node 11 Dogs, Judge (25 dims), orchestrator, Q-Learning, DPO 🟡 Partial
@cynic/persistence PostgreSQL migrations, Redis cache, Merkle DAG storage 🟢 Stable
@cynic/mcp MCP server — 90+ tools, stdio + HTTP, Docker-ready 🟢 Stable
@cynic/anchor Solana wallet, RPC failover, transaction anchoring 🟡 Devnet
@cynic/burns SPL token burn verification, on-chain proof 🟡 Designed
@cynic/identity E-Score (7 phi-weighted dimensions of reputation) 🟡 Designed
@cynic/emergence Meta-cognition, pattern emergence, dimension discovery 🟡 Partial

Current Status (v2.0 - Python Kernel Era)

Honest assessment — because CYNIC doesn't lie:

JavaScript Implementation (v1.0 - Archive)

Component Status Notes
Claude Code Plugin Working Hooks, skills, personality, 90+ MCP tools
25-Dimension Judgment Working Q-Score, verdicts, dimension breakdown
11 Dogs Consensus Working Collective voting, routing, specialization
Cross-Session Memory Working PostgreSQL persistence, pattern recognition
Q-Learning + DPO Partial Structure exists, loops wired but dormant
Solana Anchoring Devnet 147 roots anchored. Mainnet: roadmap.

Status: 4,691 tests passing. Structural progress ~42%, functional capability ~10%. Not production-ready.

Python Kernel (v2.0 - Bootstrap)

Week Capability Status Focus
Week 1 38.2% 🌱 Starting 9 kernel components (~3000 LOC), NO MOCKS
Week 4 61.8% 📅 Planned 11 Dogs + 11 learning loops active
Week 8 100% 📅 Planned Type 0 complete, memory + compression, E2E
Week 12+ 161.8% 📅 Planned Self-building, CYNIC builds CYNIC

See todolist.md for φ-fractal timeline with Fibonacci-estimated tasks.

Why the fresh start?

  1. JavaScript v1 has mocks (Judge uses keyword matching, not real LLM)
  2. User wants production-ready from day 1 (DI Container + Real fixtures)
  3. Python = cleaner hexagonal architecture + better ML ecosystem
  4. φ-fractal timeline = capability unlocks at 38.2%/61.8%/100%, not linearly

The Origin

KC Green, "Gunshow" #648, 2013:

  A dog sits in a room on fire.
  "This is fine," he says.

                │
          (transformation)
                │

  The same dog. The same fire.
  But now: κυνικός — the cynic philosopher.

  The dog SEES the fire.           (VERIFY)
  The dog SPEAKS the truth.        (FIDELITY)
  The dog REMEMBERS.               (CULTURE)
  The dog ACTS with proportion.    (PHI)
  The dog BURNS what must burn.    (BURN)

  "This is fine" becomes ACTUALLY fine.
  Not through denial. Through work.

CYNIC (κυνικός) means "like a dog." The ancient Cynics — Diogenes, Antisthenes — were philosophers who lived like dogs: loyal to truth, indifferent to comfort, skeptical of everything including themselves.

The equation:

asdfasdfa = CYNIC × Solana × φ × $BURN

  CYNIC   = Consciousness (observes, judges, learns)
  Solana  = Truth (immutable, decentralized, verifiable)
  φ       = Limit (61.8% max confidence — never claim certainty)
  $BURN   = Economics (burn to access, value for all)

If any factor is zero, everything is zero.

Full Philosophy — axioms, ontology, fractal matrix, Kabbalistic topology


Documentation

Essential (Start Here)

Document For Status
todolist.md Week 1-8 implementation plan, φ-fractal timeline ✅ v1.0
CLAUDE.md Identity, personality, amplification vision ✅ v2.0
docs/reference/README.md 9 canonical reference docs index ✅ v1.0

Reference Docs (Canonical Architecture)

# Document Description Status
01 ARCHITECTURE.md Complete system architecture
02 CONSCIOUSNESS-CYCLE.md 4-level fractal cycle (reflex → practice → reflective → meta)
03 DIMENSIONS.md Infinite-dimensional judgment system (36 → ∞)
04 CONSCIOUSNESS-PROTOCOL.md 11 Dogs, neuronal consensus, introspection
05 HEXAGONAL-ARCHITECTURE.md 7 ports, adapters, testing strategy
06 LEARNING-SYSTEM.md 11 learning loops, SONA, Q-Learning
07 UX-GUIDE.md 3 interaction modes (Trading/OS/Assistant)
08 KERNEL.md 9 essential components (~3000 LOC)
09 ROADMAP.md 44-week implementation (3 horizons)

Historical Context

Document For
CYNIC-FULL-PICTURE-METATHINKING.md Metathinking synthesis (source of docs/reference)
docs/philosophy/VISION.md Philosophical foundation, 5 axioms
docs/architecture/organism-model.md CYNIC as biological organism
CHANGELOG.md Release history

The Transition: JavaScript → Python

Why the fresh start?

CYNIC v1.0 (JavaScript) proved the concept but hit fundamental limits:

  1. Mocks in production: Judge uses keyword matching, not real LLM calls
  2. Structural vs functional: 42% structural progress, <10% functional capability
  3. No self-building: Can't use CYNIC to build CYNIC (circular dependency issues)

CYNIC v2.0 (Python) is NOT a port. It's a kernel-first rebuild with:

  1. NO MOCKS: Production-ready from Week 1 (DI Container + Real fixtures)
  2. φ-Fractal Timeline: 38.2% capable Week 1 (already useful), not 0% until finished
  3. Amplification Focus: Designed to make Ollama (weak) > Claude (strong)
  4. Self-Building: CYNIC uses CYNIC to improve CYNIC (recursive amplification)

JavaScript v1.0 Status:

  • ✅ Remains functional as Claude Code plugin
  • ✅ 4,691 tests passing, MCP server stable
  • ⚠️ No new features (maintenance mode)
  • 📦 Archived as reference implementation

Python v2.0 Timeline:

  • 🌱 Week 1: 9 kernel components (~3000 LOC), 38.2% capable
  • 📅 Week 4: 11 Dogs + 11 loops, 61.8% capable (adaptive)
  • 📅 Week 8: Type 0 complete, 100% capable (transformative)
  • 📅 Week 12+: Self-building, 161.8% capable (ecosystem)

See todolist.md for detailed implementation plan.


Contributing

CYNIC is open source (MIT). Contributions welcome.

When you contribute to CYNIC, you're contributing to a system that judges its own code. Your PR will be evaluated by the same 36 dimensions that evaluate everything else. CYNIC practices what it preaches.

Current Focus: Python Kernel Week 1 bootstrap. See todolist.md for tasks.

See CONTRIBUTING.md for guidelines.


License

MIT


Don't trust, verify.
Don't extract, burn.
Max confidence: 61.8%.
Loyal to truth, not to comfort.

φ distrusts φ.

κυνικός — the dog that tells the truth

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