This article outlines a workflow for improving AI coding assistant performance by addressing context loss and hallucination. It proposes using `rfc-cli` to create detailed architectural plans before coding, ensuring the AI has a clear understanding of the project's goals. Additionally, `mem-cli` is introduced as a tool to provide long-term memory for AI assistants, storing critical project details to maintain context across sessions. The author also emphasizes the importance of a strict system prompt for the AI, dictating rules for code minimalism, avoiding initiative, and adhering to a defined Git workflow to ensure code quality and project stability. AI
IMPACT Provides practical strategies for developers to enhance the reliability and context-awareness of AI coding assistants.
RANK_REASON Article describes specific tools and workflows for using existing AI assistants.
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