Paul Everitt is a Python and Web Developer Advocate at JetBrains. He previously co-founded Zope Corporation, helped bootstrap the Python Software Foundation and Plone Foundation, and served as a US Navy officer who started www.navy.mil in 1993.
Paul and Dan discuss how local agentic AI could reshape software engineering, from smaller models supported by static analysis and better tool calling to workflows built around specs, tests, and focused handoff packets. They compare local, cloud, and hybrid model setups and examine what happens when agents work with less supervision.
The episode's titular handoff packet sits at the center of a three-level workflow. A large model understands the project, a medium model creates an execution plan, and a small local model carries out a tightly scoped task. The packet gives that smaller model the context, constraints, tools, and success criteria it needs.
They also discuss spec drift, Markdown debt, community-maintained Python training data, and the responsibility developers retain to read, test, and own the code they ship.
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