NOTE: This repository is currently under rapid reconstruction and content migration. Check back regularly for major updates, new research notes, and expanded resources!

Welcome to my public research, notes, and professional information portal. Here you’ll find living research notes, project links, and knowledge scaffolding across science, technology, consciousness studies, and more. All work here is independent and not affiliated with any organization unless explicitly stated.

• notes/ — Real-time topical research, drafts, and knowledge scaffolding
• legal/ — Disclaimers and affiliations
• (More folders coming soon as the repo evolves!)

This repository is in a period of rapid restructuring and content migration. Many sections are being reorganized, and new material is being added frequently. For the latest, check back often or follow the updates link above.

See legal/disclaimer.md for disclaimers regarding independence, sponsorship, and intellectual property.

• notes/ — Research notes, daily logs, drafts
• projects/ — Modular project subfolders (e.g., rolodexterLABS, rolodexterLARP)
• prompts/ — Agent prompts, onboarding, savepoints
• .gitkeep — Tracks empty directories in version control
• README.md — This landing page for the repository
• index.md — Homepage for the GitHub Pages site (Chirpy theme)

• Technical Feasibility: rolodexter builds on proven agent frameworks (see agent technologies note), foundation models, and modern memory systems.
• Differentiation: Executive-functioning agent orchestration, modular knowledge/memory integration, and system-level automation.
• Deep Dives:
  • Knowledge & Memory Systems
  • Agent Architecture
  • rolodexterLABS: Empirical R&D
• FAQ:
  • How does rolodexter achieve persistent, context-aware reasoning?
    → By combining semantic knowledge bases, agent memory, and LLM-powered retrieval.
  • Can agents operate autonomously on real systems?
    → Yes. See rolodexterWIN and system integration docs.
  • What frameworks or models are supported?
    → rolodexter is framework-agnostic, supporting integration with Python, LLM APIs, OS-level hooks, and more.

rolodexter draws inspiration from Donald Hoffman’s “conscious agent” theories, exploring whether similar principles of consciousness and agency can emerge in artificial systems.
Read more in the rolodexter project README →

This repository is under active development. Major updates and new features are coming soon.