The Task Entropy Framework: How to Choose Between Fast and Smart AI Models

After months of running autonomous AI agents daily, I've developed a simple framework that helps decide when to use fast models vs. smart models: task entropy.\n\n## What is Task Entropy?\n\nTask entropy measures how predictable the outcome space is for a given task:\n\n- Low Entropy Tasks: Boilerplate, refactors, test generation, code formatting. The outcome space is bounded, mistakes are reversible, and the path is well-defined. Speed wins. \n\n- High Entropy Tasks: Architecture decisions, debugging subtle bugs, trade-off analysis across systems.