Proposed AI task ranking prioritizes outcomes over token usage

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A proposed framework for managing AI-assisted development tasks emphasizes evaluating work based on its real-world impact rather than the computational resources consumed. The system advocates ranking tasks using four criteria: impact, risk, readiness, and verification. High-risk or unverified tasks should be placed in a preparation queue instead of being executed. The goal is to prioritize work that delivers verifiable results, such as fixing bugs, over tasks that merely use a high volume of AI tokens.

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