Understanding AI Through Human-AI Collaboration
🗺️ New to this site? We have 30+ pages of content. See our guide to navigating the site for learning paths tailored to your goals.
This site provides multiple perspectives on AI:
📚 Learning Resources: Educational content explaining what AI is, how it works, and how to use it effectively
🔬 Technical Deep-Dive: Advanced technical content on AI fundamentals, LLM architecture, and Unix/Linux AI applications
🏗️ Building in Public: Real-time documentation of building this site itself - showing AI-human collaboration in action through daily session logs, case studies, and lessons learned
All sections work together: the Learning Hub teaches concepts, Technical Deep-Dive provides implementation details, and Building in Public demonstrates practical application.
Transparent collaboration - every step documented
Watch AI-human collaboration in action through daily session logs, real productivity measurements, and honest lessons learned.
What's inside: Project diary (8+ days documented), 9x efficiency multiplier case study, workflow examples, and practical collaboration techniques.
✅ Live & Updated DailyStructured educational content from first principles
Understand what AI is, how it works, and how to use it effectively. Clear explanations, technical deep-dives, and practical learning paths.
What's inside: Episode 3 (Understanding AI), architecture stack, learning plans, tool directories, and comprehensive guides.
✅ LiveAdvanced AI & LLM technical content
For developers, sysadmins, and the technically curious - detailed explanations of AI fundamentals, LLM architecture, and practical Unix/Linux applications.
What's inside: AI components & capabilities, LLM internals, neural network architecture, tokenization, and AI for Unix/Linux systems.
✅ LiveCurated references, reading, and tools
Books, learning paths, the Databricks GenAI reference, Craig's AI assessment, and curated external links for practitioners.
What's inside: Suggested reading, AI types guide, Grok self-portrait, learning companion, and 9 curated external resources.
✅ LiveStructured learning paths through the content
Navigate the site's content through organized episodes - from introduction through practical application to technical depth.
Available now: Episode 2 (Working with AI), Episode 3 (Understanding AI). Episodes 1, 4, and 5 coming soon.
✅ Live (2 episodes complete)Meet Craig, Claude, and the collaboration model
Learn about the people (and AI) behind this site, the collaboration approach, and what makes this project different.
Background: 40+ years Unix/Linux experience, ~100 reference pages built, real efficiency measurements documented.
✅ LiveFrom silicon to response — the full stack, explained
A seven-part guided series tracing an AI query from hardware through training, the LLM engine, and inference, to the interface layer and the applications built on top.
What's inside: Stack overview, hardware layer, data & training, LLM engine, inference, interface layer, and applications — with links into the deep-dive reference material.
✅ Live (7 parts complete)Direct links to the major AI assistants and tools
Quick access to Claude, ChatGPT, Gemini, Grok, DeepSeek, Perplexity, and Linux-focused AI assistants — for when you want to jump straight to the tool.
What's inside: 8 curated external links to AI chat tools and Linux-specific assistants.
✅ LiveReference pages — the source of truth for terminology and architecture
Deep reference material on AI fundamentals and LLM architecture, organized by module. Not a guided walkthrough — a lookup library for when you need the detail behind a term.
What's inside: AI Module (10 pages — types, components, capabilities, applications, ML approaches) and LLM Module (5+ pages — architecture, tokenization, neural network structure, transformer deep dive).
✅ Live (15 reference pages)Turning what's in your head into something the next person can follow
A three-page series on drafting runbooks and change logs with AI — and doing it without publishing something wrong just because it reads well.
What's inside: Runbook drafting from raw command history, change log & incident writeups, and an honest page on review discipline across sgpt, aider, fabric, and Claude.
✅ Live (hub live, 3 pages in progress)🛡️ Featured Series
AI-Assisted Log Analysis & Intrusion Detection
Four pages covering what AI adds to log analysis, behavioral intrusion detection, real tools (Wazuh, Elastic SIEM, Splunk UEBA), and an honest accounting of what AI security still misses. Written for SysAdmins, not vendor marketing.
The SysAdmin who understands this catches the intruder.... The one who doesn't finds out later.