AI News & Strategy Daily with Nate B. Jones

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.

September 21, 2026·33 min
Episode Description from the Publisher

For deeper playbooks and analysis: https://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.Subscribe for daily AI strategy and news.Hosted on Acast. See acast.com/privacy for more information. Hosted on Acast. See acast.com/privacy for more information.

Podzilla Summary coming soon

Sign up to get notified when the full AI-powered summary is ready.

Get Free Summaries →

Free forever for up to 3 podcasts. No credit card required.

Listen to This Episode

Get summaries like this every morning.

Free AI-powered recaps of AI News & Strategy Daily with Nate B. Jones and your other favorite podcasts, delivered to your inbox.

Get Free Summaries →

Free forever for up to 3 podcasts. No credit card required.