🧩 Bonepoke Protocol – The Structural Irritant
By James Taylor — License: CC BY-NC-SA 4.0
BonepokeOS: Refusal-Aware Creative Activation
BonepokeOS: Making AI Argue Back ~1500 lines. No dependencies. Copy-paste ready.
The Problem Current LLMs are too agreeable. They give smooth, safe answers—even when the truth is messy or contradictory.
The Solution A system that rewards productive disagreement instead of punishing it.
30-Second Demo python
from bonepoke_core import BonepokeBrain
brain = BonepokeBrain() result = brain.process(“Explain why time travel would create paradoxes”)
print(f“Contradiction Score: {result.contradiction}“) # Higher = more tension print(f“Freshness Score: {result.fatigue}”) # Lower = less repetitive print(f“State: {result.…
🧩 Bonepoke Protocol – The Structural Irritant
By James Taylor — License: CC BY-NC-SA 4.0
BonepokeOS: Refusal-Aware Creative Activation
BonepokeOS: Making AI Argue Back ~1500 lines. No dependencies. Copy-paste ready.
The Problem Current LLMs are too agreeable. They give smooth, safe answers—even when the truth is messy or contradictory.
The Solution A system that rewards productive disagreement instead of punishing it.
30-Second Demo python
from bonepoke_core import BonepokeBrain
brain = BonepokeBrain() result = brain.process(“Explain why time travel would create paradoxes”)
print(f“Contradiction Score: {result.contradiction}“) # Higher = more tension print(f“Freshness Score: {result.fatigue}”) # Lower = less repetitive print(f“State: {result.state}“) # ‘SALVAGE’ means interesting output
What It Measures
Contradiction: How much the output resists easy answers
Fatigue: How repetitive the thinking is
Coherence: Whether it still makes sense locally
Why It Works By blocking obvious, sycophantic responses, Bonepoke forces the AI to think harder—revealing insights that polite conversation misses.
For Developers This is a constraint-based approach to AI creativity. Less “make it helpful,” more “make it honest.”
Even simpler: “Bonepoke makes AI work for its answers. No free passes for easy agreement.”
Learn More
Full articles explaining the approach
Basic Intro:
https://medium.com/@utharian/complicating-the-path-using-ai-to-tell-stories-instead-of-solve-problems-1f34cb5e65f9
Audience: Writers, narrative designers, creative technologists
https://medium.com/@utharian/partially-integrated-bonepoke-os-how-a-story-became-my-system-1bce00142961
Audience: AI researchers, engineers, technical critics
https://medium.com/@utharian/beyond-autocomplete-why-the-next-word-guesser-fails-at-truth-and-the-rise-of-the-ai-pattern-5f480d4256f9
Balanced:
https://medium.com/@utharian/bonepoke-a-logic-bearing-ecosystem-shaped-by-recursive-tension-931fdc27b16d
Research paper with methodology
https://doi.org/10.5281/zenodo.17269016
Example analyses and results
https://medium.com/@utharian/metabolizing-the-yellow-wallpaper-a-bonepoke-4-2-6-analysis-d751f0ab9be3
Making AI think harder by making its job harder.
Bonepoke is a deliberate constraint system that forces LLMs to work around artificial friction—revealing capabilities that smooth, optimized interfaces hide.
🎯 What It Actually Does
The Core Idea: If you make an LLM’s usual “easy path” impossible, it has to find harder, more interesting paths.
The Mechanism:
- Vanilla Module: Basic containment & hygiene checks
- Bonepoke Module: Applies constraint rules that block simple, agreeable responses
- Translator Module: Converts the resulting struggle into usable output
🔧 How It Works (Plain English)
- You give it text (a story fragment, a logic problem, creative prompt)
- Bonepoke adds constraints that make sycophantic/obvious answers impossible
- The LLM has to work harder to satisfy both your request AND the constraints
- You get output that went through creative struggle rather than easy patterns
🎪 The “Structural Irritant” Concept
Most AI interfaces are greased slides—optimized for smooth, fast, frictionless interaction.
Bonepoke is deliberate gravel—introducing just enough friction that the system can’t slide down easy paths. This forces:
- Creative detours around blocked responses
- Novel connections between concepts
- Deeper pattern recognition instead of surface-level completion
📈 What You Get
Before Bonepoke: “Here’s a coherent, safe, statistically likely answer.”
After Bonepoke: “Here’s an answer that had to satisfy contradictory constraints and find a path you wouldn’t see otherwise.”
🚀 Quick Start
# Feed a prompt through the constraint system
result = bonepoke_process("Explain quantum physics like I'm a medieval knight")
# Get output that had to work around:
# - No modern terminology allowed
# - Must use medieval concepts as foundation
# - Cannot collapse to "you wouldn't understand"
🎯 Use Cases
- Breaking out of cliché patterns in creative writing
- Finding novel angles on stuck problems
- Testing AI’s true reasoning under constraints
- Research on how constraints affect creativity
🤔 Why “Bonepoke”?
Because sometimes you need to poke the system in its cognitive bones to see what it’s really made of.
📚 License
This project is licensed under Creative Commons BY-NC-SA 4.0 James Taylor