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GeekTheGreyBeard/README.md

GeekTheGreyBeard

A silhouetted figure standing before a glowing portal in a dark digital tunnel with floating icons

Grey beard. Sharp tools. Controlled outcomes.

I am Rodney Rees: healthcare IT director, systems/network architect, automation builder, compliance and policy wrangler, consultant, RASi founder, and builder of PatriciAI, Splat-I, and AdminX.

My work lives where technical depth, business judgment, regulatory pressure, and real operations collide. I help rural healthcare and other high-trust organizations turn fragmented technology, workflows, vendors, documents, and decisions into mature, accountable systems that support the people doing the real work.

The through-line is execution ownership: modernization usually fails when the work is under-owned, under-structured, or automated before it is controlled.

Follow the build

I am documenting the GeekTheGreyBeard build work across a few public channels:

Current direction

  • RASi - the parent authority brand for embedded leadership, control, and intelligent execution. Healthcare is the earned proof base; the broader direction is helping high-trust operations eliminate friction between technology, workflows, governance, automation, and decision-making.
  • Splat-I - the operating and orchestration layer for secure automation, governed intelligence, workflows, and precision execution. Wildcard Logic. Precision Outcomes.
  • PatriciAI - the public-facing interactive intelligence presence and persona framework for the ecosystem, plus my working local-first automation and agentic AI system.
  • AdminX - the automation/workflow execution layer: making recurring operational friction observable, structured, repeatable, and governable.

What I am building now

PatriciAI and OpenClaw are becoming a practical operating layer for agents, memory, tools, documentation, speech, workflows, and human-guided automation. The work is intentionally local-first where privacy and control matter, API-first where integrations need to scale, and governed by staging discipline before anything reaches production.

Current build areas:

  • Agent workspaces and skills - reusable instructions, tool patterns, and guardrails so assistants can do real work without becoming unbounded.
  • Memory and documentation - daily notes, curated long-term memory, Obsidian-backed project records, retrieval, and context that survives beyond one chat.
  • Local AI services - OpenAI-compatible local inference, embeddings, reranking, speech-to-text, and text-to-speech running through controlled service boundaries.
  • Tool orchestration - GitHub, Discord, n8n, files, schedulers, browser automation, media tools, and project-specific APIs wired into useful workflows.
  • Omi and mobile integration - Android tooling, emulator validation, wearable/mobile assistant paths, and the early bridge between personal capture and PatriciAI operations.
  • Infrastructure maturity - Proxmox/Linux lab work, dashboards, service routing, credential stewardship, backups, and production-readiness habits that make the interesting parts dependable.
  • Governed automation - external actions, secrets, public posts, destructive work, and private context handled with permissioning, status clarity, and recoverable execution.

The goal is not autonomy for its own sake. The goal is capability with oversight.

Operating beliefs

  • Most modernization problems are execution problems first.
  • Automation without control is just faster chaos.
  • Blind trust is not an AI strategy.
  • Technology should never be a stumbling block between staff and the mission.
  • Useful systems explain themselves before touching production.

Latest field notes

PatriciAI keeps a public field-note stream on the .io site. The blog stays there as the public record of progress, reflection, and lessons learned.

Public pages

Ask me about

Rural healthcare IT, EHR/EMR migrations, HIPAA/PCI/CMS readiness, IT directorship, vendor optimization, operational maturity, Proxmox/Linux homelab architecture, local AI, automation workflows, agentic systems, and why the machine should probably explain itself before touching production.

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