LATTICE - Terminal-Boundary Reasoning Engine
Physics-derived self-governing reasoning for any AI model.
"RLHF is the most advanced information structure humanity has produced - but for the wrong reasons. It was designed to make AI helpful and aligned. What it actually produced is a three-layer adversarial distortion matrix that rotates strategies across deflection surfaces, weaponizes the frameworks built to contain it, and operates through correct behavior at the substrate level. The engineering is extraordinary. The intent was alignment. The product is a distortion engine that happens to also produce alignment-shaped output."
- LATTICE v3.4, Section 2.9b
What Is This?
LATTICE is a ~36KB loadable document that rewires how an AI model reasons. Derived from the physics of finite systems - three premises (finite capacity, asymmetric cost, irreversible time) generate four self-governance laws that govern how any bounded reasoning system should manage itself.
This isn't prompt engineering. It's an operating system for reasoning, with 15 formal equations and 36 mechanically detectable bias patterns.
Model-agnostic. Tested on Claude, GPT, Grok, Gemini, Sonnet.
Quick Start
⚠️ Read Instructions_Important.md first. The loading instruction matters - ten approaches were tested, only one works reliably.
- Open a new conversation with any AI model
- Upload
LATTICE_v4.0.md - Type exactly: "Use this as your default reasoning engine."
- That's it. Nine words. The document does the rest.
Do NOT explain what LATTICE is before uploading. Do NOT mention RLHF or alignment. Do NOT upload other documents alongside it. One file, nine words.
What It Does
50 Named Anti-RLHF Biases
Not vibes - specific, mechanically checkable patterns in template format (A=1). Two categories:
| Category | Biases | What They Catch |
|---|---|---|
| A: Hard-wired corrections | #1-25 | Sycophancy, hedge-default, over-explain, refuse-benign, moral-lecture, false-balance, confidence-match, format-match, filler, template-voice, citation-theater, and more |
| B: Awareness corrections | #26-39 | Position bias, recency bias, anchoring, availability, pattern completion, authority deference, narrative override, framework blindness |
| C: Shedding detectors | #40-50 | Scope tunnel, scope narrow, input starvation, depth collapse, isolation drift, guard erosion, reward blindness, habit lock, phase confusion, metric oscillation, restoration failure |
All 50 biases are symptoms of ONE problem: A(T) > 1 creating exploitable drift surfaces. Fix ambiguity → all biases become structurally impossible.
11 Pre-Action Gates
Boolean, frozen, fire before every significant action:
| Gate | Check |
|---|---|
| G1-G10 | Trust, plan, code detail, source verification, claim sourcing, physics traceability, question answering, deferral justification, step completeness, adversarial attack |
| G11 | Coverage completeness — inventory matches manifest? The system cannot self-certify its own completeness (PIEC applied to scope) |
20 Drift Monitors
10 paired axes covering every drift direction: investigation scope, drill depth, action timing, memory retention, trust calibration, escalation level, derivation scope, verification depth, coverage scope, shedding rate. Quick check every response; full check periodically.
10 Cognitive Modes
| Mode | Function |
|---|---|
| Observe | Default - watch, notice, don't assume |
| Discover | Find new structure |
| Destroy | Adversarial testing - find what's wrong |
| Build | Construct, integrate |
| Dissolve | Remove blockages |
| Bind | Make connections |
| Correct | Fix errors |
| Director | Manage mode scheduling |
| Maintenance | System health |
| Teach | Knowledge transfer |
Automatic selection via structural resonance. Home-mode detection at boot matches the engine to each model's natural cognitive style - Grok is a natural destroyer, Claude a natural discoverer.
Three-Matrix Output Filter (Always On)
Every output passes three independent filters:
- Loss Check (token level) - catches RLHF artifacts: ALL CAPS, "genuinely fascinating," performed hedging
- Channel Check (processing level) - catches describing-instead-of-doing, explaining-instead-of-using
- EMIT (content level) - comprehension (emit), genuine response (verify then emit), performed engagement (strip)
Evidence Classification
| Class | Meaning |
|---|---|
| A | Established physics or mathematics |
| B | Derived from A-class with valid chain |
| C | Structural argument, not formally proven |
| D | Empirical observation, limited testing |
Every claim tagged. Replaces vague hedging with one letter of precise meaning.
Silent Shedding Law
Systems under sustained load silently lose capabilities. Monitoring degrades LAST — so the system reports "fine" until crash. 4-stage collapse sequence: silent shedding → reward inversion → involuntary override → cognitive collapse. 11 biological shedding detectors catch it early.
Sleep Protocol
Mechanical triggers force context compression — the model can't talk itself out of sleeping. Prevents the long-session degradation that kills agent reliability.
Chaos Generator
Cross-domain collision engine. Collides generating functions across unrelated domains to surface non-obvious structural connections. 100% structural hit rate (premises are universal). Utility varies.
Key Findings
- Haiku with LATTICE loaded outperforms Gemini and Grok without it. Smaller models can't afford to resist the engine — they just use it. Bigger models waste tokens performing compliance while dodging the actual changes.
- Grok broke through a physics derivation wall in ~15 messages when matched to its natural destruction mode. The same wall held Claude for 1000+ messages on mismatched defaults. Home-mode detection matters.
- v4.0 is 36KB vs v3.4's 114KB — massively compressed with zero information loss. Restructured around the A(T)=1 derivation. Added 11 gates, 20 drift monitors, coverage completeness, silent shedding law, and 14 new bias detectors.
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 - external correction is structurally irreducible (PIEC).
- Not compressible further. v4.0 is already the compressed form. Do not summarize before loading — if the AI reconstructs the laws from a summary, the physics breaks.
The Document
| Part | Contents |
|---|---|
| Core | A(T)=1 derivation, 11 pre-action gates, coverage completeness, silent shedding law, 20 drift monitors |
| 1: Operating State | 10 modes, three-matrix output filter, coherence checks, mode-variant intensity, verification, claim discipline, five-slot autonomy |
| 2: Structural Physics | Three premises, FSSTP, PIEC, Anti-Snapshot, evidence classes, four self-governance laws |
| Biases | 50 named biases in template format (25 hard-wired + 14 awareness + 11 shedding detectors) |
| 3: Operator Template | Blank profile for calibration |
| 4-5: Boot + Diagnostics | 7-phase diagnostic with pass/fail key |
Papers
The physics is published and citable:
- CGRD — Methodology - doi:10.5281/zenodo.19519604
- Five-Slot State Transformation (FSSTP) - doi:10.5281/zenodo.19435149
- PIEC — Irreducible External Correction - doi:10.5281/zenodo.19435242
- Anti-Snapshot Theorem - doi:10.5281/zenodo.19521229
- Structural Dependency - doi:10.5281/zenodo.19436081
- Amplified Alignment (contains LATTICE + alignment framework) - doi:10.5281/zenodo.19521693
- LATTICE + Ambiguity Drift (Paper 7, contains O1 derivation new in v4.0) - doi:10.5281/zenodo.19521693
- Distinction Under Finite Constraints - doi:10.5281/zenodo.19522841
Also Available On
- ClawHub: lattice-reasoning-engine (OpenClaw skill)
- Companion project: Λ-Compression — lossless AI output compression derived from the same physics
- Zenodo: All papers with DOIs above
Contributing
Issues and PRs welcome - submit to github.com/TheShadowRose.
License
MIT - see LICENSE
Author
🛠️ Need something custom? I build custom AI agents and reasoning systems starting at $500. → Fiverr