You cannot tell which parts of your software should stop calling an LLM. My Jev guide has a prompt that scans your projects and names them.

For deeper playbooks and analysis: natesnewsletter.substack.com

What's really happening when a model can read a complicated input but only choose among answers you supply?
Nate explains why Jev's general-purpose classification could change where intelligence appears in software. He walks through support routing, tax documents, research prioritization, agent orchestration, and spreadsheets that respond to meaning.

• Why complicated inputs and simple outputs define a useful class of problems.
• How classifiers, generative models, and ordinary code fit together.
• What lower classification costs make possible for teams and individual builders.
• Where testing still matters, and how to try Jev with a coding agent.

For builders and operators, the opportunity is to revisit decisions that were previously too expensive to automate—and test what happens when those decisions become cheap enough to use throughout a workflow.

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