Which AI Model to Use for Any Task Without Overpaying

For deeper playbooks and analysis: https://natesnewsletter.substack.com/

What's really happening when every AI model suddenly looks replaceable?

The common story is that model choice is the strategy, but the reality is that useful work comes from matching the model, the task, and the workflow surface.

In this episode, I share the inside scoop on how to pick AI models without turning model selection into the whole job.

Why daily-driver models are different from cheap workhorse models How to think about GLM, Kimi, Qwen, Claude, ChatGPT, and Codex What specialist tools are actually for Where harnesses and workflows matter more than raw model rankings Why fewer model choices can make teams faster

This is for operators, founders, developers, and team leads who need practical AI work to keep moving even when the model landscape shifts underneath them.

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