llm/065c6e83-d0d5-4aca-be3d-92768a8a3506/topic-12-02a8ee93-bb6d-4dbf-8f18-25b26cfd9349-output.json
Effective Claude workflows center on a deliberate "plan-annotate-refine" cycle, where users treat AI-generated markdown documents as living specifications rather than ephemeral chat history. To guide the model without manual rewriting, developers employ diverse formatting strategies ranging from simple HTML comments and "TODOCLAUDE" prefixes to specialized visual tools like Plannotator. This Socratic approach encourages the agent to "fix its own plan" based on human feedback, ensuring the AI internalizes complex domain constraints and architectural preferences before execution begins. By establishing authoritative conventions such as "Project Concept Lists" or numbered checklists, users can maintain a single source of truth that prevents context drift and ensures high-quality, consistent output across long sessions.