# Technical AI Articles & Digital Garden Welcome to AIXplore, a curated digital garden exploring AI development, systems architecture, and practical applications. Written by Justin Johnson ([@bioinfo](https://twitter.com/bioinfo)). --- ## 📊 Content at a Glance <div class="topic-area"> - **51 Articles** across 5 categories - **4+ hours** of technical content - **145+ Tags** covering AI topics - **7 Learning Paths** for structured exploration </div> --- ## 🆕 Latest Articles ### [[Practical Applications/building-ai-research-night-shift|My AI Research Assistant Works the Night Shift (A Claude Code Skill Story)]] 🆕 *Practical Applications* • intermediate • 10 min How I built a Claude Code skill that researches AI developments overnight using intelligent automation that adapts, prevents duplicates, and provides instant answers. ### [[Practical Applications/prompt-build-ai-landscaping-skill|Prompt for Claude Code: Build AI Landscaping Skill]] 🆕 *Practical Applications* • intermediate • 8 min Copy-paste prompt for Claude Code to build a complete AI research intelligence skill with duplicate prevention, structured storage, and instant retrieval. ### [[AI Systems & Architecture/dgx-spark-week-one-finding-the-right-stack|DGX Spark: Week One Update - Finding the Right Stack]] *AI Systems & Architecture* • advanced • 15 min Systematic debugging reveals configuration fixes that transformed DGX Spark performance from frustrating to transformative with 3.6x speedups. ### [[Practical Applications/medical-llm-fine-tuning-70-to-92-percent|How I Delegated a 9-Day Medical AI Experiment (and Learned When to Step In)]] *Practical Applications* • intermediate • 14 min • **DGX Lab Chronicles Part 6** Delegating a complex 60-hour ML experiment to Claude revealed when to intervene and when to trust. Learn the decision points that turned 70% accuracy into 92.4%. ### [[Practical Applications/dgx-lab-benchmarks-vs-reality-day-4|DGX Lab: When Benchmark Numbers Meet Production Reality - Day 4]] *Practical Applications* • intermediate • 10 min • **Series Part 4** NVIDIA's DGX Spark benchmarks show 82,739 tokens/sec for training and sub-1% accuracy degradation with FP4. After 6 days of intensive ML workloads, I reveal what the benchmarks don't tell you about GPU inference failures, memory fragmentation, and production workarounds. ### [[Emerging Trends/the-hidden-crisis-in-llm-fine-tuning-catastrophic-forgetting|The Hidden Crisis in LLM Fine-Tuning: When Your Model Silently Forgets Everything]] *Emerging Trends* • intermediate • 13 min Catastrophic forgetting in LLM fine-tuning is a silent killer that produces zero-token outputs without errors or warnings, and the solution might surprise you. ### [[Practical Applications/three-days-to-build-ai-research-lab-dgx-claude|Three Days to Build an AI Research Lab: My DGX + Claude Experiment]] *Practical Applications* • intermediate • 7 min • **Series Part 1** From hardware delivery to production ML experiments in 72 hours, building an AI research lab with Claude Code as a thought partner and documenting the entire journey. ### [[Practical Applications/dgx-lab-supercharged-bashrc-ml-workflows-day-2|DGX Lab: Supercharge Your Shell with 50+ ML Productivity Aliases - Day 2]] *Practical Applications* • beginner • 10 min • **Series Part 2** Transform your default shell into a productivity powerhouse with GPU monitoring shortcuts, smart aliases, and custom functions—setup in 5 minutes, benefit forever. ### [[Practical Applications/dgx-lab-intelligent-gateway-heuristics-vs-ml-day-1|DGX Lab: When Simple Heuristics Beat ML by 95,000x - Day 1]] *Practical Applications* • intermediate • 14 min • **Series Part 1** Building an intelligent AI gateway that routes requests 95,000x faster than ML while maintaining 90% accuracy—proving that smart heuristics can outperform deep learning. ### [[Practical Applications/syncing-claude-code-configs-across-machines|Syncing Claude Code Configurations Across Multiple Machines: A Practical Guide]] *Practical Applications* • intermediate • 15 min Learn how to intelligently sync Claude Code configurations across Mac, Pi, and DGX boxes while preserving machine-specific settings like model endpoints and API keys. ### [[Practical Applications/building-production-ml-workspace-part-5-collaboration|Building a Production ML Workspace: Part 5 - Team Collaboration and Workflow Integration]] 🎉 *Practical Applications* • intermediate • 14 min • **Series Part 5/5 - Complete!** Complete your production ML workspace with team collaboration patterns, workflow automation, version control strategies, and integration frameworks that scale. ### [[Practical Applications/building-production-ml-workspace-part-4-agents|Building a Production ML Workspace: Part 4 - Production-Ready AI Agent Templates]] *Practical Applications* • intermediate • 10 min • **Series Part 4/5** Build production-ready AI agents with standardized templates, tool integration patterns, comprehensive testing, and deployment readiness frameworks. ### [[Practical Applications/building-production-ml-workspace-part-3-experiments|Building a Production ML Workspace: Part 3 - Experiment Tracking and Reproducibility]] *Practical Applications* • intermediate • 12 min • **Series Part 3/5** Master experiment tracking with MLflow, implement reproducible workflows, and build structured systems for managing ML research that scales from prototype to production. ### [[Practical Applications/building-production-ml-workspace-part-2-documentation|Building a Production ML Workspace: Part 2 - Documentation Systems That Scale]] *Practical Applications* • beginner • 7 min • **Series Part 2/5** Build a three-tier documentation system that captures ML work for debugging, review, and blog content—turning your experiments into shareable knowledge. ### [[Practical Applications/building-production-ml-workspace-part-1-structure|Building a Production ML Workspace: Part 1 - Designing an Organized Structure]] *Practical Applications* • beginner • 8 min • **Series Part 1/5** Learn how to design a scalable ML workspace structure that handles Ollama models, fine-tuning, agents, and experiments without becoming chaotic. ### [[Practical Applications/roo-code-codebase-indexing-free-setup|Supercharging Code Discovery: My Journey with Roo Code's Free Codebase Indexing]] *Practical Applications* • beginner • 12 min Set up professional-grade semantic code search using Roo Code's codebase indexing with completely free tools - Qdrant Cloud and Google Gemini. ### [[Cutting-Edge AI/sakana-ai-ab-mcts-collective-intelligence|Sakana AI's AB-MCTS: Orchestrating Collective Intelligence in Frontier AI Models]] *Cutting-Edge AI* • advanced • 7 min Deep analysis of Sakana AI's breakthrough AB-MCTS algorithm achieving 39.2% solve rate on ARC-AGI-2 through adaptive branching Monte Carlo tree search. ### [[AI Development & Agents/dspy-programming-language-models-at-scale|DSPy: The Programming Revolution for Language Model Applications]] *AI Development & Agents* • intermediate • 5 min Deep dive into DSPy, Stanford NLP's framework that provides systematic, programming-first approach to LLM development with 25-65% performance improvements. ### [[AI Development & Agents/anthropic-multi-agent-research-system|Anthropic's Multi-Agent Research System: Engineering Autonomous Scientific Discovery]] *AI Development & Agents* • advanced • 5 min Deep dive into Anthropic's engineering approach to building a multi-agent research system that autonomously conducts scientific research. ### [[Cutting-Edge AI/gemini-diffusion-google-deepmind-analysis|Gemini Diffusion: What if Text Generators Worked Like Stable Diffusion for Words?]] *Cutting-Edge AI* • advanced • 9 min Google DeepMind's Gemini Diffusion brings discrete-token diffusion to production scale, achieving 1-2k tokens/second through block-parallel denoising. ### [[AI Development & Agents/crct-v7-7-roo-code-adaptation|CRCT: A Technical Overview of the Cline Recursive Chain-of-Thought System]] *AI Development & Agents* • intermediate • 3 min Technical exploration of CRCT, examining how it enhances AI agent memory management and integration with existing codebases. ### [[AI Development & Agents/claude-code-best-practices|Claude Code: Best Practices for Agentic Coding]] *AI Development & Agents* • beginner • 7 min Comprehensive guide to optimizing your workflow with Claude Code, covering setup customization, effective workflows, and advanced techniques. ### [[AI Development & Agents/building-effective-ai-agents-openai-guide|Building Effective AI Agents: Key Insights from OpenAI's Practical Guide]] *AI Development & Agents* • intermediate • 5 min Comprehensive analysis of OpenAI's practical guide to building agents, covering foundational concepts, orchestration patterns, and implementation best practices. --- ## 🗂️ Browse by Category <div class="topic-area"> ### [[AI Development & Agents/⌂ AI Development & Agents|AI Development & Agents]] Building autonomous systems and multi-agent architectures (7 articles) </div> <div class="topic-area"> ### [[Cutting-Edge AI/⌂ Cutting-Edge AI|Cutting-Edge AI]] Latest model releases and research breakthroughs (8 articles) </div> <div class="topic-area"> ### [[AI Systems & Architecture/⌂ AI Systems & Architecture|AI Systems & Architecture]] System design patterns and production implementations (12 articles) </div> <div class="topic-area"> ### [[Practical Applications/⌂ Practical Applications|Practical Applications]] Hands-on guides and real-world implementations (21 articles) </div> <div class="topic-area"> ### [[Emerging Trends/⌂ Emerging Trends|Emerging Trends]] Future directions and strategic analysis (1 articles) </div> --- ## 🧭 Navigation <div class="quick-nav"> ### Browse Content - [[index/by-date|Browse by Date]] - Chronological timeline - [[index/by-tag|Browse by Tag]] - 145 tags across all articles - [[index/by-difficulty|Browse by Difficulty]] - Beginner (11), Intermediate (28), Advanced (12) - [[index/by-topics|Browse by Topics]] - 80 specific topics - [[index/reading-paths|Learning Paths]] - 6 curated learning journeys ### Start Learning - **New to AI Agents?** → [[index/reading-paths#Path 1 Getting Started with AI Agents|Getting Started Path]] - **Building Systems?** → [[index/reading-paths#Path 2 Building Production AI Systems|Production Systems Path]] - **Learning LLMs?** → [[index/reading-paths#Path 3 LLM Development Mastery|LLM Development Path]] </div> --- ## 📈 Content Distribution ### By Category - **AI Development & Agents**: 7 articles (14%) - **Cutting-Edge AI**: 8 articles (16%) - **AI Systems & Architecture**: 12 articles (24%) - **Practical Applications**: 21 articles (41%) - **Emerging Trends**: 2 articles (4%) ### By Difficulty - **Beginner**: 11 articles (22%) - **Intermediate**: 28 articles (55%) - **Advanced**: 12 articles (24%) --- ## 🎯 Featured Learning Paths <div class="callout" data-callout="tip"> <div class="callout-title">New to AIXplore?</div> <div class="callout-content"> Start with these curated learning paths designed to build your knowledge systematically: 1. **[[index/reading-paths#Path 1 Getting Started with AI Agents|Getting Started with AI Agents]]** (45 min) - Build foundational knowledge from basics to practical implementation 2. **[[index/reading-paths#Path 3 LLM Development Mastery|LLM Development Mastery]]** (40 min) - Master LLM development from prompt engineering to optimization 3. **[[index/reading-paths#Path 5 Practical AI Implementation|Practical AI Implementation]]** (35 min) - Get up and running with AI tools quickly </div> </div> --- ## 💡 About AIXplore This digital garden is maintained by **Justin Johnson** ([@bioinfo](https://twitter.com/bioinfo)), focusing on: - **Technical Depth**: In-depth analysis and practical implementation - **Current Relevance**: Latest developments in AI and LLMs - **Practitioner Focus**: Real-world applications and lessons learned - **Open Learning**: Sharing knowledge and building in public ### Publishing Cadence - **Target**: 2-3 articles per week - **Focus**: Quality over quantity - **Updates**: Regular refreshes of existing content ### Topics Covered - AI Agent Development & Orchestration - LLM Application Development - System Architecture & Design - Production Implementation - Latest AI Research & Models - Practical Tools & Workflows --- ## 📬 Stay Connected - **Twitter**: [@bioinfo](https://twitter.com/bioinfo) - Latest updates and discussions - **Blog**: [rundatarun.io](https://rundatarun.io) - Additional content - **GitHub**: Open source contributions and examples --- **Last Updated**: 2025-11-06 **Total Articles**: 52 **Total Reading Time**: ~4 hours 45 min