Principal Researcher
Research Profile & Impact
PRINCIPAL_RESEARCHER_PROFILE:
├── Identity & Affiliation
│ ├── Name: Michael Shatny
│ ├── Title: AI Orchestration Architect & Research Pioneer
│ ├── Location: Ontario, Canada
│ ├── ORCID: 0009-0006-2011-3258
│ └── DOI: 10.5281/zenodo.17114972
│
├── Research Focus Areas
│ ├── Semantic Intent Patterns
│ ├── AI-Assisted Development
│ ├── Immutable Governance
│ └── Software Architecture
│
├── Methodology Expertise
│ ├── Empirical Software Engineering
│ ├── Case Study Research
│ ├── Action Research
│ └── Design Science
│
└── Research Impact Metrics
├── Published Papers: 1 (featured research)
├── Performance Improvement: 78% (empirically validated)
├── Debugging Efficiency: 3+ weeks eliminated
└── Innovation: First unified semantic intent pattern
Research Focus Areas
Current Research Domains
RESEARCH_FOCUS_AREAS:
├── Semantic Intent Patterns
│ ├── Unified approaches combining semantic anchoring (WHAT)
│ ├── Intent mapping (WHY) into atomic behavioral contracts
│ └── Cross-domain pattern synthesis methodology
│
├── Immutable Governance
│ ├── Runtime protection mechanisms for semantic contracts
│ ├── Violation detection in transformation layers
│ └── Contract enforcement across system boundaries
│
├── AI-Assisted Development
│ ├── Clear semantic boundaries for human-AI collaboration
│ ├── Enhanced AI effectiveness through intent preservation
│ └── Architectural integrity maintenance patterns
│
└── Software Architecture
├── Intent preservation across complex enterprise systems
├── Multi-layer transformation handling
└── Pattern synthesis for diverse software domains
Published Research
Semantic Intent as Single Source of Truth: Immutable Governance for AI-Assisted Development
Research Overview
PUBLISHED_RESEARCH:
├── Publication Details
│ ├── Title: Semantic Intent as Single Source of Truth
│ ├── Subtitle: Immutable Governance for AI-Assisted Development
│ ├── Journal: semanticintent.dev Research Papers
│ ├── Publication Date: September 2025
│ └── Type: Original Research
│
├── Research Methodology
│ ├── Background: AI-assisted development challenges in intent preservation
│ ├── Methods: Unified Semantic Intent pattern with immutable governance
│ ├── Case Study: Real-world PDF differentiation problem
│ └── Validation: Empirical testing with measurable outcomes
│
├── Key Results
│ ├── Performance Improvement: 78% behavioral differentiation enhancement
│ ├── Problem Resolution: 9 vs 16 pages (dramatic improvement)
│ ├── Time Savings: Weeks of traditional debugging eliminated
│ └── Innovation: First unified semantic intent pattern
│
└── Implementation & Access
├── Full Paper: Read Complete Research
├── Source Code: GitHub Repository
├── Keywords: semantic intent, immutable governance, AI development
└── Citation: Available in standard academic formats
Research Methodology
Scientific Research Approaches
RESEARCH_METHODOLOGY:
├── Case Study Research
│ ├── Real-world enterprise problem solving
│ ├── Measurable outcomes and empirical validation
│ ├── Contextual analysis of practical implementations
│ └── Industry-relevant problem domains
│
├── Action Research
│ ├── Iterative development of solutions
│ ├── Practical implementation and testing cycles
│ ├── Continuous refinement based on results
│ └── Real-time problem-solving approach
│
├── Empirical Software Engineering
│ ├── Evidence-based approaches with quantitative metrics
│ ├── Reproducible results and statistical validation
│ ├── Performance measurement and benchmarking
│ └── Data-driven research conclusions
│
└── Design Science
├── Creation of novel artifacts (patterns, frameworks)
├── Solution-oriented research methodology
├── Practical problem-solving through innovation
└── Artifact evaluation in real-world contexts
Current Research
Active Research Projects
CURRENT_RESEARCH_PROJECTS:
├── Performance Optimization of Semantic Intent Patterns
│ ├── Status: In Progress (Expected Q1 2026)
│ ├── Focus: Efficient implementation strategies for enterprise systems
│ ├── Goal: Minimal runtime overhead while preserving intent
│ └── Scope: Large-scale system optimization
│
└── Regex Optimization within Semantic Anchoring Frameworks
├── Status: Planning Phase (Expected Q2 2026)
├── Focus: Pattern matching performance optimization
├── Goal: Maintain semantic intent preservation in text processing
└── Scope: Text processing pipeline efficiency
Future Research Directions
Research Roadmap & Future Work
FUTURE_RESEARCH_DIRECTIONS:
├── Cross-Domain Pattern Synthesis
│ ├── Extending semantic intent patterns across software domains
│ ├── Architecture-agnostic implementation strategies
│ └── Universal pattern applicability research
│
├── AI Collaboration Enhancement
│ ├── Advanced semantic boundaries for human-AI workflows
│ ├── Improved development collaboration patterns
│ └── AI-assisted semantic intent validation
│
├── Framework Development
│ ├── Production-ready semantic intent framework
│ ├── Enterprise adoption guidelines
│ └── Industry-standard implementation patterns
│
├── Empirical Studies
│ ├── Large-scale validation across multiple organizations
│ ├── Cross-industry effectiveness measurement
│ └── Statistical validation of pattern benefits
│
└── Tool Development
├── IDE plugins for semantic violation detection
├── Automated development tools
└── Real-time intent preservation monitoring
Research Resources
Available Research Materials & Tools
RESEARCH_RESOURCES:
├── Implementation Resources
│ ├── Implementation Guide: Step-by-step codebase integration
│ ├── Framework Documentation: Complete API reference
│ └── Usage Examples: Practical application patterns
│
├── Source Code & Data
│ ├── GitHub Repository: Working implementation
│ ├── Git History: Complete development evolution
│ └── Validation Data: Empirical testing results
│
├── Educational Materials
│ ├── Case Studies: Real-world applications
│ ├── Academic Resources: Methodology explanations
│ └── Application Examples: Domain-specific implementations
│
└── Research Documentation
├── Methodology Papers: Theoretical foundations
├── Empirical Results: Performance data and analysis
└── Pattern Library: Reusable semantic intent patterns
Citation Information
How to Cite This Research
APA Style:
Shatny, M. (2025). Semantic Intent as Single Source of Truth: Immutable Governance for AI-Assisted Development. semanticintent.dev Research Papers. https://doi.org/10.5281/zenodo.17114972
BibTeX:
@article{shatny2025semantic,
title={Semantic Intent as Single Source of Truth: Immutable Governance for AI-Assisted Development},
author={Shatny, Michael},
journal={semanticintent.dev Research Papers},
year={2025},
doi={10.5281/zenodo.17114972},
url={https://semanticintent.dev/papers/semantic-intent-ssot},
note={ORCID: 0009-0006-2011-3258}
}