agentic-development-principles
Framework for effective AI collaboration defining task decomposition, context management, abstraction selection, and automation philosophy.
- Divide complex tasks into small, independently verifiable steps; AI performs significantly better with clear, bounded instructions than large ambiguous requests
- Keep context fresh and single-purpose; use separate conversations for different topics and apply HANDOFF.md summaries when conversations grow long to prevent context drift
- Adjust abstraction level by situation: use high-level "vibe coding" for prototypes and rapid iteration, deep-dive line-by-line review for production code, bugs, and security work
- Default to plan mode (70-90% of work) for analysis and review before execution; use execute mode only for simple, well-validated tasks in safe environments
- Automate any task repeated 3+ times; verify all outputs through tests, code review, and self-verification before deployment
Agentic development principles (Agentic Development Principles)
"AI is the copilot; you are the pilot" AI agents amplify the developer's thinking and take over repetitive work, but final decision-making authority and responsibility always remain with the developer.
When to use this skill
- When starting a collaboration session with an AI agent
- When deciding an approach before starting a complex task
- When establishing a context management strategy
- When reviewing workflows to improve productivity
- When onboarding teammates on how to collaborate with AI
- When applying baseline principles while adopting a new AI tool
Principle 1: Divide and conquer (Divide and Conquer)
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