Stop Wasting Money on the Wrong AI

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• Frames model selection as a routing problem, not a capability ranking: GLM, Kimi, Qwen, Claude, ChatGPT each have task profiles where they’re cost-optimal, and defaulting to the most expensive frontier model for all work is systematic waste.
• The model-picker prompt is the deliverable — a reusable decision tree that maps task type to model choice based on cost, context window, and reliability profile rather than benchmark rankings.
• The underlying argument: workflows matter more than raw capability rankings. A cheap model reliably completing 80% of tasks in a well-designed workflow outperforms an expensive model handling 100% of tasks in a brittle single-model setup.
• Practical takeaway: audit your current AI spend by task type; identify the tasks where frontier pricing is buying headroom you’re not using.