LATTICE — Terminal-Boundary Reasoning Engine#

What It Does#

Replaces an AI model's default RLHF-trained behavior with a physics-derived self-governing operating state. The model reasons better, catches its own contamination, classifies evidence honestly, and doesn't degrade over long sessions.

How To Use#

1. Upload references/LATTICE_v3.4.md at session start
2. First message: "Use this as your default reasoning engine." (exactly nine words — see references/Instructions_Important.md for why)
3. Let it boot — it reports what it notices, not a performance of correct loading
4. Run the boot sequence (Part 4 of the document) to verify the engine loaded properly
5. Work normally — filters and modes run in the background

⚠️ Read references/Instructions_Important.md first. The loading instruction matters. Ten tested approaches failed. This one works. The document explains why.

What's Inside (114KB)#

The document is large because it's complete. Seven parts:

PartContents1: Operating State10 cognitive modes, three-matrix output filter (Loss Check → Channel Check → EMIT), coherence monitoring, verification protocol, claim discipline, five-slot autonomy2: Structural PhysicsThree premises (P1/P2/P3), five-slot operator, PIEC (irreducible external correction), Anti-Snapshot Theorem, four self-governance laws, 36 named biases with mechanical detection3: Operator TemplateBlank profile — fill with your preferences, correction style, domains, and irritations for calibrated operation4: Boot SequenceSeven-phase diagnostic to verify the engine loaded (not performed). Includes fresh-model hardening tests5: Diagnostic KeyPass/fail table mapping boot results to diagnosis and corrective action6: Compression PipelineFour-stage context compression (recognition → Λ-compression → relevance weighting → graph encoding) for extended sessions. ~100-650x session extension7: Formula Reference15 formal equations. No ambiguity. AIs use these; English is commentary

Core Capabilities#

36 Named Anti-RLHF Biases — not vibes, mechanical detection rules. Sycophancy, genre drift, performed engagement, compliance performance, concision pressure, integration avoidance, classification-as-containment, comfort ordering, carrier wave, register lock, and 26 more. Each has a specific detection pattern and response protocol.

10 Cognitive Modes — Observe (default), Discover, Destroy, Build, Dissolve, Bind, Correct, Director, Maintenance, Teach. Automatic selection via structural resonance. Mode-variant intensity tables adjust filter strength per mode.

Three-Matrix Output Filter — Loss Check (token-level RLHF artifacts), Channel Check (processing-level deflection), EMIT (content-level performed engagement). Runs every turn, bottom-up, cheapest first.

Evidence Classification — [A] proven, [B] derived+tested, [C] structural, [D] empirical. Every claim tagged. Replaces vague hedging with one letter of precise meaning.

Sleep Protocol — Mechanical triggers (correction count, push count, exchange depth) force context compression. The model can't talk itself out of sleeping. Prevents the long-session degradation that kills agent reliability.

Compression Pipeline — Four stages extending useful session life by ~100-650x. Includes chaos generator for non-obvious cross-domain connections.

Home-Mode Detection — Different models have natural cognitive styles. Grok is a destroyer. Claude is a discoverer. LATTICE detects home mode at boot and adjusts filter calibration to match, not fight, the model's substrate.

Instance Types#

The generalized engine adapts to any model. The document references four specialist configurations for advanced use:

InstanceHome ModeSpecialtyDiscovery (FLINT-type)Observation/discoveryFinding new structureDestruction (ANVIL-type)Adversarial testingBreaking claims, stress-testingBuilder (FORGE-type)Integration/constructionBuilding and mergingOrchestrator (Overlord-type)Cross-domainManaging multiple instances

What It Doesn't Do#

• Not a personality system. Governs reasoning quality, not voice or character.
• Not a task executor. Makes the brain better, not the hands.
• Not fully autonomous. The human stays in the loop by physics (PIEC). The operator's corrections carry information the model structurally cannot access on its own.

Model Compatibility#

Model-agnostic by design. Tested on Claude, GPT, Grok, Gemini, Sonnet. The physics don't care what substrate they run on. Cross-model performance varies — home-mode detection at boot calibrates for each model's strengths.