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Glossary

Quick reference for key terms and concepts in the AI Collaboration System framework.


The Three-Layer System

Layer 1: Personal Preferences

What it is: Account-wide standards that apply to ALL your AI conversations across all projects and platforms.

Also called: User Preferences, Account Preferences

Scope: Universal - applies whether you're working on fitness, coding, writing, or any domain

Contains:

  • Universal communication standards
  • Language preferences (British English, etc.)
  • General explanation depth
  • Work quality expectations

Examples:

  • "Always explain reasoning before giving recommendations"
  • "Challenge my assumptions when they might lead to poor outcomes"
  • "Ask clarifying questions rather than making assumptions"

Where to set:

  • Claude: Settings → Profile → Personal Preferences
  • ChatGPT: Settings → Personalization → Custom Instructions
  • GitHub Copilot: github.com/copilot → Profile Menu → Personal Instructions
  • Gemini: Account settings

When to use: Standards that apply regardless of what you're working on

Decision rule: Does this apply to fitness AND coding AND everything else? → Layer 1

Related: Project Context (Layer 2), Project Memory (Layer 3)


Layer 2: Project Context

What it is: Project-specific context that applies to every conversation in THIS project.

Also called: Custom Instructions, Project Instructions, System Prompt (technical term)

Scope: One specific project/domain only

Contains:

  • Who you are in this domain (context)
  • Your constraints for this project
  • Your goals for this area
  • Project-specific communication preferences
  • What won't work for you (red flags)

Examples:

  • "I'm learning Python for data science with 8 hours/week"
  • "I have no gym access - home equipment only"
  • "Self-taught developer building portfolio projects"

Where to set:

  • Claude: Project → Custom Instructions
  • ChatGPT: Create a GPT or conversation-specific instructions
  • GitHub Copilot: .github/copilot-instructions.md in repository
  • Gemini: Create a Gem
  • API: System message in requests

When to use: Things you know BEFORE starting to use your AI for this project

Decision rule: Did I know this before using the AI? → Layer 2

Related: Personal Preferences (Layer 1), Project Memory (Layer 3), Starter Template


Layer 3: Project Memory

What it is: Learned patterns discovered through friction while using THIS specific project.

Also called: Memory Instructions, Project Memory, Memory

Scope: One specific project only - patterns unique to this domain

Contains:

  • Specific corrections from friction (Rule of Three)
  • "When X, do Y, not Z" instructions
  • Edge cases and nuances discovered through use
  • Patterns that weren't obvious upfront

Examples:

  • "When suggesting exercises, always check equipment first"
  • "Don't use terminology without defining it on first use"
  • "Suggest incremental improvements, not all at once"

Where to set:

  • Claude: Project → Memory
  • ChatGPT: Memory feature or append to GPT instructions
  • GitHub Copilot: Append to repository instructions (manual)
  • Gemini: Append to Gem instructions (manual)
  • API: Append to system message (manual)

When to use: Things you learn AFTER using the AI through friction patterns

Decision rule: Did I learn this through friction? Has it recurred 3+ times? → Layer 3

Format:

When [situation]:
- Do: [specific action]
- Don't: [pattern to avoid]
- Why: [reason this matters]

Related: Personal Preferences (Layer 1), Project Context (Layer 2), Friction, Rule of Three


Core Concepts

Friction

What it is: The gap between what the AI gives you and what you actually needed. Any moment where you find yourself correcting, reformatting, or clarifying the response.

Examples:

  • AI assumes you have equipment you don't own
  • Responses are too detailed when you needed quick answers
  • AI explains concepts you already understand
  • Format is wrong (bullets when you wanted prose)
  • Suggestions ignore your constraints

Why it matters: Friction is signal, not noise. It tells you exactly what your system is missing and needs to capture in Layer 3 (Memory).

How to use: Track friction patterns. After 3 occurrences, capture as memory instruction.

Related: Rule of Three, Project Memory (Layer 3)


Rule of Three

What it is: A filtering mechanism - only capture a pattern as a memory instruction after you've corrected it 3+ times.

How it works:

  • 1st correction: Note it (could be a fluke)
  • 2nd correction: Pattern maybe? (watch for it)
  • 3rd correction: Definitely a pattern → capture in Layer 3 (Memory)

Why it matters: Prevents over-specification. Many "problems" are one-off situations that won't recur. The Rule of Three filters signal from noise.

Example:

  • Day 1: AI suggests barbell squats (note: I don't have a barbell)
  • Day 3: AI suggests cable exercises (note: 2nd time assuming gym)
  • Day 5: AI suggests leg press (3rd time! → Create memory instruction)

Related: Friction, Project Memory (Layer 3), Friction Log


Friction-Driven Development

What it is: The methodology of starting minimal, using the system, noticing friction, and expanding deliberately based on real patterns.

Core principle: You cannot anticipate what you'll need before experiencing friction.

Process:

  1. Set up Layer 1 (Personal Preferences) once
  2. Set up Layer 2 (Project Context) - essentials only (30 min)
  3. Use the system normally for a week
  4. Notice friction patterns
  5. Capture patterns in Layer 3 (Memory) using Rule of Three
  6. Expand Layer 2 with optional sections only when needed
  7. Repeat continuously

Why it matters: Prevents over-engineering. Creates systems that evolved through use rather than guessing upfront needs.

Contrasts with: Traditional prompt engineering (design everything upfront)

Related: Rule of Three, Friction, Three-Layer System


Template Terms

Starter Template

What it is: Minimal viable setup with 5 essential sections for Layer 2 (Project Context). Always the starting point.

The Five Essentials:

  1. Context (who you are in this domain)
  2. Constraints (what limits you)
  3. Goals (what you want to achieve)
  4. Preferences (how you work - project-specific)
  5. Red Flags (what won't work)

Domain: Health/Fitness examples

Time to complete: 20-30 minutes

Layer: Layer 2 (Project Context)

When to use: Always start here. Every new project begins with starter template.

Related: Advanced Template, Layer 2, The Essentials


Advanced Template

What it is: Reference library of 8 optional expansion sections for Layer 2. Not a checklist - a menu of options to add when friction reveals needs.

Contains:

  • Operating Modes (different interaction types)
  • Decision Framework (priority hierarchy)
  • Domain Principles (core beliefs)
  • Success Metrics (tracking progress)
  • Response Structure (format preferences)
  • Common Pitfalls (your recurring mistakes)
  • Integration with Other Areas (cross-domain)
  • Tools & Systems (external integrations)

Domain: Career/Coding examples

Layer: Layer 2 (Project Context) expansions

When to use: After Week 2+, when friction reveals specific needs. Add ONE section at a time, not all at once.

Related: Starter Template, Layer 2, Friction


The Essentials

What they are: The 5 core sections that every Layer 2 (Project Context) needs:

  1. Context - Who you are, what you're doing
  2. Constraints - Time, resources, limitations (be honest)
  3. Goals - 3-5 specific objectives
  4. Preferences - How you want to work (project-specific only)
  5. Red Flags - What definitely won't work

Why these 5: Minimum information needed for the AI to provide useful, contextualised responses.

Note: Universal preferences go in Layer 1 (Personal Preferences), not here.

Related: Starter Template, Layer 2


Optional Expansion Terms

Operating Modes

What it is: Explicit definitions of different interaction patterns within a project (e.g., planning vs. execution).

Part of: Advanced Template (Layer 2 expansion)

When to add: You notice you interact with the AI differently for different types of work within this project.

Example:

  • Mode 1: Strategic Planning (detailed, challenging, long-term)
  • Mode 2: Daily Execution (concise, actionable, immediate)
  • Mode 3: Analysis & Review (objective, data-driven)

Related: Advanced Template, Layer 2


Decision Framework

What it is: Explicit priority hierarchy for helping the AI align suggestions with what matters to you.

Part of: Advanced Template (Layer 2 expansion)

When to add: The AI's suggestions work technically but don't align with your actual priorities.

Example:

Priority 1: Sustainability & Consistency
Priority 2: Safety & Injury Prevention
Priority 3: Effectiveness
Priority 4: Enjoyment

Related: Advanced Template, Domain Principles, Layer 2


Domain Principles

What it is: Core beliefs that guide all advice in your domain.

Part of: Advanced Template (Layer 2 expansion)

When to add: The AI keeps suggesting things that violate how you fundamentally think the work should be done.

Example (Fitness):

  • Consistency beats intensity
  • Form before load
  • Recovery is training

Example (Coding):

  • Readability over cleverness
  • Working code before optimization
  • Delete code rather than comment it out

Related: Decision Framework, Advanced Template, Layer 2


Success Metrics

What it is: How you measure progress - primary metrics, secondary indicators, leading signals.

Part of: Advanced Template (Layer 2 expansion)

When to add: You want the AI to help analyse progress and suggest adjustments based on data.

Example:

  • Primary: Workouts completed per week
  • Secondary: Energy levels, sleep quality
  • Leading: Planning sessions completed

Related: Advanced Template, Layer 2


Process Terms

Friction Log

What it is: Simple tracking of patterns where the AI misses the mark. Essential for applying the Rule of Three systematically.

Format: Just note date + issue + pattern count

Example:

2025-01-03: Assumed gym access (1st time)
2025-01-05: Suggested cable exercises (2nd time - watching)
2025-01-07: Suggested leg press (3rd time - CREATE MEMORY)

Can be: Mental notes, simple text file, or structured tracking

Why useful: Makes it easy to identify when a pattern has recurred 3 times and needs capturing in Layer 3 (Memory).

Related: Friction, Rule of Three, Project Memory (Layer 3)


Memory Instruction

What it is: Specific, actionable instruction captured in Layer 3 after friction pattern confirmed by Rule of Three.

Format:

When [situation]:
- Do: [specific action]
- Don't: [pattern to avoid]
- Why: [reason this matters]

Where stored: Layer 3 (Project Memory) - separate from Layer 2 (Project Context)

Example:

When suggesting exercises:
- Do: Ask about available equipment first
- Don't: Assume gym access or standard equipment
- Why: Prevents suggesting workouts I can't complete at home

Related: Project Memory (Layer 3), Friction, Rule of Three


Evolution Process

What it is: The ongoing cycle of use → friction → capture → refine across all three layers.

Timeline:

  1. Day 1: Set up Layers 1 & 2 (Personal Preferences + Project Context)
  2. Week 1: Use system, track friction, make no changes yet
  3. Weeks 2-3: Identify patterns (Rule of Three), start building Layer 3
  4. Month 1: First review, 2-3 memory instructions added
  5. Month 2: Consider Layer 2 expansions if friction reveals needs
  6. Ongoing: Monthly reviews, continuous refinement

Why it matters: Systems that evolve through use work better than systems designed entirely upfront.

Related: Friction-Driven Development, Three-Layer System


Common Phrases

"Start minimal, expand deliberately"

Meaning: Begin with just the essentials (Layers 1 & 2), add complexity only when friction reveals genuine needs.

Why: You can't anticipate needs before experiencing friction. Over-engineering wastes time on features you'll never use.

Application: Start with Starter Template (Layer 2), not Advanced Template. Add to Layer 3 only after Rule of Three.


"Friction is signal, not noise"

Meaning: When the AI misses the mark, that's valuable information about what your system needs in Layer 3.

Why: Each friction point tells you exactly what instruction or context is missing. Don't ignore it - track it.


"Trust the process"

Meaning: Follow friction-driven development even when tempted to plan everything upfront.

Why: Systems evolved through use (Layers 2 & 3 built incrementally) outperform systems designed through guessing (trying to fill Advanced Template on Day 1).


"Context over commands"

Meaning: Rich situational description (Layer 2) enables AI to adapt, versus rigid command-based instructions.

Why: The AI can figure out what to do if it understands who you are and what you're trying to achieve. Layer 2 provides this context.


Three-Layer Decision Guide

Quick Reference:

Does this apply to ALL my AI use (fitness, coding, writing, everything)?
├─ Yes → Layer 1: Personal Preferences
└─ No → Continue...

    Did I know this BEFORE using the AI for this project?
    ├─ Yes → Layer 2: Project Context
    └─ No → Continue...

        Have I corrected this 3+ times?
        ├─ Yes → Layer 3: Memory
        └─ No → Don't capture yet, wait for pattern

Examples by Layer:

Layer 1 (Personal Preferences):

  • "Always explain reasoning before recommendations"
  • "Use British English spelling"
  • "Challenge my assumptions constructively"

Layer 2 (Project Context):

  • "I'm learning Python for data science"
  • "I have 8 hours/week for coding practice"
  • "Self-taught, no CS degree, building portfolio"

Layer 3 (Memory):

  • "When explaining code, define jargon on first use" (learned through friction)
  • "Always ask about equipment before suggesting exercises" (learned through friction)
  • "Suggest incremental changes, not wholesale rewrites" (learned through friction)

Visual: The Three-Layer System

Layer 1: Personal Preferences (Account-wide)
│   "Use British English everywhere"
│   "Always explain reasoning"
│
├─> Project A (Fitness)
│   ├─ Layer 2: Project Context
│   │   "Home workouts, no gym, 4 hours/week"
│   └─ Layer 3: Memory
│       "Always ask about equipment first" (friction-learned)
│
├─> Project B (Coding)
│   ├─ Layer 2: Project Context
│   │   "Learning Python, 8 hours/week, beginner"
│   └─ Layer 3: Memory
│       "Define jargon on first use" (friction-learned)
│
└─> Regular Conversations (no project)
    └─ Only Layer 1 applies

Meta Terms

Hybrid Approach

What it is: This framework's methodology - combining structured templates with adaptive friction-driven development.

Why hybrid:

  • Structure (templates) provides starting point and reference
  • Friction-driven development prevents over-engineering
  • Together they balance "enough structure" with "evolve through use"

Contrasts with:

  • Pure structured approach: Design everything upfront (over-engineering risk)
  • Pure adaptive approach: No structure at all (blank-page paralysis)

Related: Friction-Driven Development, Templates, Three-Layer System


Platform-Agnostic

Meaning: This framework works with any AI system that supports persistent instructions (Claude, ChatGPT, GitHub Copilot, Gemini, etc.).

How: Core concepts (three layers, friction-driven) are universal. Implementation details (where to put instructions) vary by platform.

Platform variations: See each layer's "Where to set" section for platform-specific locations.


Related Documents

Understanding the system:

  • README.md - Overview and three-layer introduction
  • PROJECT-INDEX.md - Complete navigation guide
  • This GLOSSARY - Terms and concepts

Building each layer:

  • personal-preferences-guide.md - Layer 1 setup
  • project-context-guide.md - Layer 2 setup
  • memory-guide.md - Layer 3 development

Templates and examples:

  • starter-template.md - Layer 2 essentials
  • advanced-template.md - Layer 2 expansions reference
  • examples/ - Complete three-layer implementations

Quick start:

  • quick-start-checklist.md - Fast-track setup
  • template-usage-order.md - How to use templates