Task Decomposition

Breaking complex tasks into smaller, manageable subtasks to overcome limitations like context window constraints in AI systems.

Key Principles

• Atomicity: Subtasks must be small enough to complete within context window limits (e.g., <1k tokens for AI agents).
• Sequential Dependencies: Subtasks ordered to build incrementally (output of one informs next).
• Context Minimization: Each subtask uses only necessary context from prior steps.

AI Coding Workflow (Claude Implementation)

• Problem: AI agents fail at “one-shot” large code generation due to context window limitations.
• Solution: Decompose coding tasks into iterative, context-aware subtasks.
• Workflow:
  • Break feature into atomic steps (e.g., “parse input”, “validate data”, “generate output”).
  • For each step:
    • Provide current code state and minimal relevant context.
    • Give focused instruction (e.g., “Fix the parse_input function”).
    • Use agent output to inform next step.
  • Avoid large “one-shot” prompts; iterate incrementally.

Related Concepts

• context-window
• Iterative Development
• AI Agent
• ai-coding

Backlink: 2026 04 14 Fixing long running Claude code sessions

Source Notes

• 2026-04-08: How to make Claude Code less dumb