What’s The New State?
Oh hi there. I’m Mike and this is my weird little online space. What even is this place? Good question, Greg. On the one hand, it’s a shop where I hock my services and products. On the other hand, TNS is where I’ll begin sharing the practical or commercial applications of my research, musings, or observations. In time, I hope it becomes a resource and perhaps a platform where other ops nerds can let their freak flags fly.
Deep solutioning
Nearly pathological drive to understand. To intuit the causes, effects, the factors, the solutions; a sense derived from incremental model-building, testing, and gradual expansion of deeper and deeper conditions, attributes, relationships, and emergent properties. A type of organic algorithm. By developing a more and more accurate model, our conception of the whole begins to enable our ability to perceive the emergent reality, complete with macro-level motions and inertia. That in turn imbues into us a type of “physics code” where we can predict the high-level mechanics, anticipate, plan, and build hyper-networked solutions.
Interests
Taxonomies
- New ways of organizing things and relating attributes or conditions
- Codifying ideas, things, or information into a digital system
- Quantifying and tracking ideas, things, activity, or information
- Enabling integrations, discoverability, comparative analytics, and automation
- Balancing system categories with metadata, research, and analytics
Process
- New variations of modalities for organizing human activities or computer actions
- Discovery of previously unknown steps
- Folk workflows and localized shortcuts
- Testing process modifications
- Representation and documentation of processes
- Standardized or automated workflows
Reference & research
- Intersection of taxonomies, metadata schema, and usage
- Revealing hidden information or objects through organizational structures
- Integrating the forgotten, unnamed through description and systems
Metadata
- Methods of enrichment and ingestion
- Research needs and requirements for analytics
- Grouping, collections, and relationships
- Metadata-driven automations and smart folders
Knowledge structures
- Knowledge capture and validation
- Natural structures (plainly descriptive) for advanced usage
- Behavioral structures (engineered) that elicit particular workflows or behavior
- Knowledge cycle: variations, versioning, and archiving information
- Engineering the means of identifying and categorizing knowledge, and verifying it for truth and accuracy
Language & meaning
- Human languages and systems of meaning
- Mathematical truth, experiential truth, and the relationships to syntax/lexicons
- Differentiating descriptive language from prescriptive
- Technical languages and prescribed syntax/lexicons
- Codifying complex expressions into rules-based environments
- Finding meaning and experience in data
