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🔧 Practice Patterns / Coding with AI Hub

LLM usage organized into reusable chapters. Starting with outlines and card navigation, expanding incrementally.

📚 Chapters

  • Prompt Design Structured templates and anti-patterns for reproducibility and controllability.
  • Test Automation Extend quality coverage via spec-to-test, regression summaries, and property extraction.
  • Refactoring Assistance Phased model: smell scan → design agreement → fine-grained application → comprehensive verification.
  • Performance Optimization Trade-off control and measurement across latency, cost, quality, and safety.
  • Debugging / Diagnostics Observability stack and classification to improve failure reproducibility.

🔑 Key Guides

  • LLM programming in practice: ../llm-programming-guide.md
  • AI coding tools hands-on: ../ai-coding-tools-practical-implementation-2025.md
  • Development tools comparison: ../ai-development-tools.md

🧪 Future Expansions

ItemStatusPlan
Evaluation workflow standarddraftMacro-ize metrics
Prompt pattern examplesskeleton10 → 30 examples
Automated testing GitHub ActionspendingAdd sample workflow
  • Culture / Methodology: ../methodology/index.md
  • Agent Development: ../agentic/index.md

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