Reality Drift — Diagnostic Guides for Modern Systems
A set of short diagnostic guides designed to help identify recurring failure modes in modern digital, institutional, and information environments.
Each guide isolates a specific pattern within the Reality Drift framework and translates it into recognizable signals.
The goal is not explanation, but detection.
These diagnostics focus on early indicators such as:
- loss of meaning behind metrics
- increasing uniformity of content
- cognitive overload and filtering behavior
- rising reliance on optimized representations
Together, they provide a quick way to recognize when systems remain functional while their connection to reality begins to weaken.
Quick Diagnostics for Identifying Drift
- Signs You May Be Experiencing Reality Drift
[PDF] [DOI] [Slidedeck] - Signs You May Be Experiencing Filter Fatigue
[PDF] [DOI] [Slidedeck] - Signs You May Be Experiencing the Optimization Trap
[PDF] [DOI] [Slidedeck] - Signs You May Be Experiencing Synthetic Realness
[PDF] [DOI] [Slidedeck]
Concept Modules
These diagnostics map to the core concepts below:
- Reality Drift [PDF]
- Filter Fatigue
- Synthetic Realness
- Optimization Trap
- The Drifted Self [PDF]
Explore The Framework
Core Framework
- Reality Drift Canonical Definition
- Mechanics and Taxonomy [PDF]
- Drift/Fidelity Index [PDF]
Visual & Conceptual
Applications & Expansion
Note: This site functions as a lightweight archive and reference layer for the Reality Drift framework. Primary essays and long-form writing are distributed across external platforms.
Substack • GitHub • DOI • Slideshare
Part of Reality Drift Framework by A. Jacobs (2023-2026)