RESEARCH 2025NEW The Missing Key to True LLM Intelligence 3.0: An Operational Roadmap for the S VectorNEW The Mechanistics of Hallucination Version 3.0NEW: Research Summary: A Unified Theory of LLM EvolutionNEW: Applied Research: Why the S-Vector Matters: The Missing Dimension in Enterprise AI — and What Companies Should Try includes pilot overview.The S-Vector: Topographic Attention and the Architecture of IntelligenceWhy Hallucinations Happen: Fracture and Repair in Transformer Systems v1The When Where and How of LLM Failures, MeasuredDoes Agentic AI Exist? v6.0Why Agentic AI Is Problematic: The Architectural RisksAI's Accountability Gap: A Policy Blueprint for PolicymakersAI's Unmeasured Reality: How Users Are Left BehindEvans' Law 5.0: Long-Context Degradation in Multimodal Models and the Cross-Modal Degradation TaxEvans' Law: Scaling, Coherence, and Governance Implications V4.0Evans’ Law v4.1 (Extended)Evans' Law: A Predictive Threshold for Long-Context Accuracy Collapse in Large Language Models
⸻ARTICLES 2023-2025NEW The Intelligence Paradox: Why AI Researchers Can’t See What’s MissingNEW Is Human Feedback Breaking AI? Testing Whether “Alignment” Actually Degrades IntelligenceNEW: Why AI Hallucinates — and What Executives Need to UnderstandNEW: Memory, Architecture and Meaning: Why MIRAS Confirms the Significance Deficit in Modern AINEW: The Enterprise AI Era Is Splitting in TwoDeepSeek-R1 Shows Reinforcement Learning Can Reshape LLM ReasoningSnowflake’s Role in the AI Ecosystem, And Two Rivals Trying to Replicate Its SuccessNEW: Why the S-Vector Matters: The Missing Dimension in Enterprise AI, and What Companies Should TryArchitectural Constraints: The Physics of AI SystemsWhy Evans Law and Evans Ratio MatterWhy AI Models Don’t Know Who the Prime Minister IsIs AGI Mastery or Systems?Why AI Sounds So Smart While Being So WrongHow Transformers Actually BreakBooking.com’s AI Agent Case StudyArchitectural Regression: How GPT-5.0 Became Less Reliable Than GPT-4.0Can Generative AI Prompt Token Usage Be Tracked Today?What AI Platforms Must Do for Safety in the Face of Evans’ LawA Conversation about Enterprise AI with the CIO of ADP (part one)ADP at Web Summit Vancouver - – Part TwoWhy Crowds Behave Like a Reinforcement LearnerRedefining AI Policy: A Critical Analysis of Global FrameworksHow AI Is Transforming Legal Practice Management SoftwareAI Innovation & the Future of Canadian Business: A Conversation with PwC's Chris Dulny6 Functional Types of Artificial IntelligenceGenerative AI in Canada: Accelerating Adoption Amid Caution and OpportunityLeading the Transformation of the Enterprise Through Generative AIHow Four B2B Tech Providers Integrate AIManaging a Big, Huge Unknown: AI Risk Management StandardsThe AI Ecosystem Wars BeginAI Crossroads: Velocity and Vision After OpenAI’s First DevDayHow Elon Musk’s Strategic Inconsistencies Will Define AI EvolutionYoshua Bengio Appointed to AI Governance Leadership RolesWhat Is a Model Context Protocol – And Why Does It Matter?Prompting 101: Revenge of the HumanitiesPrompting 101: Revenge of the Humanities (Part Two)AI and Your Communications StrategyChatGPT: Better Business Communications With AIThe Multimodal Phase: Generative AI AcceleratesCanada’s AI Code of Conduct: A CritiqueIs This Report Written in ChatGPT? Does It Matter?The Intersection of AI & Digital Marketing: A Conversation With Neil PatelServiceNow to Acquire Element AI

SERVICESAI Policy Consulting and DevelopmentI provide evidence-based policy guidance and development for internal or external use by companies, not for profits and governments, inclusive of platform suitability, employee use, vendor use, agreements, SLAs, risk assessments, AI system reliability, context window limitations, and failure mode prediction. Internal AI policies make acceptable practices clear and limit risk.My research on conversational coherence collapse (Evans' Law) informs security frameworks, procurement standards, and deployment risk assessment.Services include:
- AI system reliability auditing
- Context window testing and validation protocols
- Policy frameworks for AI use
- Policy frameworks for procurement and deployment
- Security risk assessment for agentic AI systems
- Expert testimony and technical documentationClients include organizations deploying conversational AI at scale, public sector organizations, and AI safety standards, and companies requiring independent verification of AI vendor claims."Your work is years ahead of the rest of the field." - US public sector client at the state levelVector Database & RAG ArchitectureStrategic consulting on retrieval-augmented generation (RAG) systems and vector database implementation. I help organizations move beyond basic chatbot deployments to robust, production-grade AI systems that maintain coherence and reliability.Services include:
- Vector database selection and architecture design
- Pilot design
- RAG pipeline optimization
- Context management strategies for extended conversations
- Performance testing and degradation monitoring
- Integration planning for existing systems
- Significance coding integration into RAG including taxonomies and semantics.
Ideal for organizations building internal AI tools, companies scaling from prototype to production, and teams experiencing reliability issues with existing implementations.

LICENSINGThe S-Vector framework, Evans’ Law methodology, and related research are available for commercial licensing. Organizations interested in implementing significance-weighted architectures, using Evans’ Law for system evaluation, or incorporating Fracture-Repair analysis into their AI safety protocols should contact us to discuss licensing terms.Available for Licensing:• S-Vector Architectural Specifications
Complete framework for implementing significance-weighted attention in transformer systems and orchestration layers• Evans’ Law Evaluation Methodology
Validated approach for measuring coherence limits, predicting degradation, and establishing functional context windows• Fracture-Repair Diagnostic Framework
Mechanistic theory for identifying hallucination onset, classifying repair behaviors, and understanding vendor-specific signatures• AI Conversational Phenomenology Methodologies
Research protocols for studying real-world, customer-specific AI system behavior and user interaction dynamicsLicensing includes implementation guidance, technical documentation, and ongoing research updates.
Contact us to discuss licensing arrangementsCOPYRIGHT & LICENSING
© 2023-2025 Jennifer Evans / PatternPulse.AI. All rights reserved.Research Publications
Academic papers published on Zenodo are licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). You may share and adapt this work with appropriate attribution.Frameworks & Methodologies
Evans’ Law, the Fracture-Repair framework, S-Vector specifications, policy frameworks, and AI Conversational Phenomenology methodologies are proprietary intellectual property. Commercial use requires licensing. Contact us to discuss terms.Website Content
All articles, analysis, and original content on this site are protected by copyright. You may link to and quote from our work with attribution, but reproduction or republication requires permission.Attribution
When citing our work, please use:Evans, Jennifer. [Title]. PatternPulse.AI, [Year]. [URL or DOI]
For licensing inquiries: [email protected]