Core Principles
Context engineering, verification-first development, and the three-phase workflow that produces the best outcomes.
Agentic AI Development Guide
Research-backed patterns, experiments, and tutorials for getting the best results from AI coding agents on complex, large codebases.
Project Structure
Optimal repository layout, CLAUDE.md mastery, skills and agents architecture for complex codebases.
Prompting Patterns
Prompt taxonomy, task decomposition, and anti-patterns — backed by comparative experiments with scoring matrices.
Multi-Agent Orchestration
Hierarchical, pipeline, and adaptive patterns for scaling AI agents across large features.