Stop Wasting Money on the Wrong AI

Yesterday, Nate B Jones addressed a problem facing AI-using professionals: how to pick the right model without overpaying. His framework: match the model to the job, not vice versa. For routine, repeatable work, cheaper workhorse models like GLM five point two deliver results at a fraction of frontier-model cost. Save premium models for tasks where the problem is unclear or demands maximum capability. Specialists win too: dedicated models outperform generalists for images, video, live web, and code generation. The practical strategy is to audit your five most common work artifacts, route them to the cheapest viable model, test each on your actual workflow, and keep context portable—so when the next model emerges, your workflow doesn't stall. Permission to use AI at work comes first; cost optimization comes second.

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