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Discrete Task Conversation Framework
A method for organizing AI agent interactions by creating separate conversations for each distinct development task rather than maintaining long-running chats
How It Works
Each new conversation gets fresh context window allocation (avoiding memory degradation that occurs when context reaches 80-90% capacity), allowing the AI agent to focus entirely on the specific task without being confused by unrelated previous context
Components
Identify discrete development tasks (30-75 line changes typical)
Start new conversation for each task
Monitor context window usage (aim to stay under 80%)
Include relevant files explicitly using @ tagging
Complete task before moving to next conversation
When to Use
For any development workflow using AI agents, especially when building production applications that require consistent quality output across multiple features or bug fixes
When Not to Use
When tasks are highly interdependent and require continuous context from previous interactions, or for simple single-step operations
Anti-Patterns to Avoid
Example
“Developer needs to add event tracking, fix a layout bug, and update documentation. Instead of one long chat covering all three, they create three separate conversations: one for event tracking (45 lines changed), one for layout fix (30 lines), and one for docs update (75 lines).”