1. QED: AI Development Patterns
  2. Getting Started
  3. 1. Introduction
  4. 2. Philosophy and Mindset
  5. 3. Pattern Template
  6. Patterns by Domain
  7. 4. Architecture Overview
  8. 5. Core Architecture
  9. 6. System Architecture Diagram
  10. 7. AMP Architecture Overview
  11. 8. Thread Management at Scale
  12. 9. Real-Time Synchronization
  13. 10. Tool System Evolution
  14. 11. Multi-Agent Orchestration
  15. 12. Ink Yoga Reactive UI
  16. 13. Emerging Patterns
  17. 14. Collaborative AI Ecosystem
  18. 15. Implementation Overview
  19. 16. Execution Flow in Detail
  20. 17. Initialization Process
  21. 18. Real World Examples
  22. 19. Claude Code vs Anon Kode
  23. 20. Framework Selection Guide
  24. 21. Framework Wars Analysis
  25. 22. System Prompts and Model Settings
  26. 23. Feature Flag Integration
  27. 24. Building Your Own AMP
  28. 25. Migration Strategies
  29. 26. Operations Overview
  30. 27. Parallel Tool Execution
  31. 28. Lessons Learned
  32. 29. Performance at Scale
  33. 30. Observability and Monitoring
  34. 31. Deployment Guide
  35. 32. Performance Tuning
  36. 33. Security Overview
  37. 34. The Permission System
  38. 35. Authentication and Identity
  39. 36. Sharing and Permissions
  40. 37. Team Overview
  41. 38. Team Workflows
  42. 39. Enterprise Integration
  43. 40. From Local to Collaborative
  44. 41. Quality Overview
  45. 42. Risk Assessment
  46. Patterns by Risk Profile
  47. 43. Safe Starting Points
  48. 44. Patterns Requiring Safeguards
  49. 45. Critical Patterns
  50. Patterns by Context
  51. 46. Context Overview
  52. 47. Agile Patterns
  53. 48. Scaling Patterns
  54. 49. Governance Patterns
  55. 50. Compliance Patterns
  56. Learning Paths
  57. 51. Getting Started with AI Development
  58. 52. Enterprise Adoption Journey
  59. 53. Agency Playbook
  60. 54. Migration from Traditional Development
  61. Case Studies
  62. 55. AMP Implementation Cases
  63. Reference
  64. 56. API Reference
  65. 57. Taxonomy Guide
  66. 58. Pattern Index
  67. Analysis Queue
  68. 59. Research Overview
  69. 60. PRewrite: Reinforcement Learning Prompt Optimization
  70. 61. Cloudflare Code Mode MCP
  71. 62. Building Agents for Small Language Models
  72. 63. Building Better Agentic RAG Systems
  73. 64. Core Architecture - Agentic Systems
  74. 65. Lessons Learned - Production Implementation
  75. 66. Multi-Agent Research System
  76. 67. Parallel Tool Execution
  77. 68. Real World Examples - Claude Code
  78. 69. Slash Commands vs Subagents
  79. 70. The Lethal Trifecta for AI Agents
  80. 71. The Permission System
  81. 72. The Rise of Computer Use and Agentic Coworkers
  82. 73. Two Experiments on AI Agent Compaction
  83. 74. Beyond Chunks: Context Engineering
  84. 75. Collecting All Causal Knowledge
  85. 76. Command System Deep Dive
  86. 77. Execution Flow in Detail
  87. 78. Ink Yoga Reactive UI
  88. 79. System Prompts and Model Settings
  89. 80. Systematically Improving RAG
  90. 81. AI Will Change How We Build Startups
  91. 82. How To Become A Mechanistic Interpretability Researcher
  92. 83. Understanding LLMs: Mechanistic Interpretability
  93. 84. Evaluation Overview
  94. 85. Psychology of Trust in AI
  95. 86. ACE-FCA Context Engineering
  96. 87. AI Coding Efficiency
  97. 88. Google Gemini Nano
  98. 89. Distributed Systems Patterns
  99. 90. PRewrite: RL Prompt Optimization
  100. Archive
  101. 91. Previous Structures

AI Development Patterns: A Practitioner's Guide

Command System Overview