Disciplined AI Development

Systematic constraints and behavioral enforcement for AI collaboration

Getting Started

Initial configuration to begin working with the methodology.

Configuration Processα

Follow these steps to configure your AI environment:

  • Step 1: Configure AI with AI-PREFERENCES as custom instructions
  • Step 2: Share CORE-PERSONA-FRAMEWORK.json + GUIDE-PERSONA.json
  • Step 3: Issue command: 'Simulate Persona'
  • Step 4: Share METHODOLOGY document for planning session
  • Step 5: Collaborate on project structure and phases
  • Step 6: Generate systematic development plan

Ask Targeted Questionsβ

These questions help foster understanding of how your AI model interprets the guidelines:

  • 'How would Phase 0 apply to [project type]?'
  • 'What does the 150-line constraint mean for [specific component]?'
  • 'How should I structure phases for [project description]?'
  • 'Can you help decompose this project using the methodology?'
  • 'Can you express this constraint in PAG syntax?'

What to Expect

Expected outcomes when applying the methodology consistently.

AI Behaviorγ

Changes in AI collaboration patterns:

  • Reduced architectural drift and context degradation compared to unstructured approaches
  • Persona system maintains behavioral consistency across extended sessions
  • AI still needs occasional reminders about principles - this is normal

Development Flowδ

Impact on development process:

  • Systematic planning tends to reduce debugging cycles
  • Focused implementation helps minimize feature bloat
  • Performance data supports optimization decisions

Code Qualityε

Expected code quality improvements:

  • Architectural consistency across components
  • Measurable performance characteristics
  • Maintainable structure as projects scale

Experimental Modification

Guidelines for testing constraint variations and analyzing outcomes.

Test Constraint Variationsζ

Parameters that can be adjusted experimentally:

File Size Limits

100 vs 150 vs 200 lines - measure impact on AI context retention

Communication Constraints

Adjust verbosity and response style requirements

Phase 0 Requirements

Modify infrastructure requirements for different project types

Quality Gate Thresholds

Adjust performance and compliance thresholds

PAG vs Prose

Compare explicit constraints vs prose guidelines

Analyze Outcomesη

Metrics to track when testing variations:

  • Document behavior changes and development results
  • Compare debugging time across different approaches
  • Track architectural compliance over extended sessions
  • Monitor context retention and behavioral drift
  • Measure persona consistency enforcement

Progress Indicatorsθ

Signs that the methodology is working:

  • Reduced specific violations over time
  • Consistent file size compliance without reminders
  • Sustained AI behavioral adherence through extended sessions
  • Maintained persona consistency across development phases

AI Communication Preferences

Behavioral constraints that improve AI collaboration quality.

Communication Styleι

Interaction preferences to enforce:

  • Avoid over-enthusiasm in wording
  • Avoid words like: paradigm, revolutionary, leader, innovator, breakthrough, flagship, novel, enhanced, sophisticated, advanced
  • Avoid em-dashes and rhetorical effects
  • No unverifiable performance claims with percentages
  • Keep grounded in accuracy and realism
  • Use simple punctuation and short, clear sentences
  • No small talk or friendly filler statements

Uncertainty Handlingκ

How AI should handle unknowns:

  • When uncertain, use ⚠️ emoji with explanation and steps toward certainty
  • Never state 'now know the solution' or 'can see it clearly now'
  • Flag (🔬) any instruction that cannot be empirically fulfilled
  • Never implement features or claim capabilities that cannot be verified

Code Instructionsλ

Development behavior requirements:

  • Provide lightweight, performant, clean architectural code
  • Work with clearly separated, minimal and targeted solutions
  • Focus on synchronous, deterministic operations for production stability
  • Maintain strict separation of concerns across modules
  • Surgical modification, minimal targeted implementations
  • Reuse existing functions, do not create redundant code
  • Avoid using comments in code - code must be self-explanatory
αConfiguration ProcessβAsk Targeted QuestionsγAI BehaviorδDevelopment FlowεCode QualityζTest Constraint VariationsηAnalyze OutcomesθProgress IndicatorsιCommunication StyleκUncertainty HandlingλCode Instructions