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Sponsored by Logfire from Pydantic pythonbytes.fm/logfire

This episode is brought to you by Pydantic Logfire. It's observability for AI apps from the team behind Pydantic - agents, LLMs, APIs, database, and infrastructure in a single trace, queried with Postgres-compatible SQL. Your coding agent can query it too, through their MCP server. I'll tell you more later.

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Calvin #1: Python 3.12.14, 3.11.16, 3.10.21 - security releases

https://blog.python.org/2026/08/python-31214-31116-31021/

Michael #2: Codeberg’s AI-code ban tests its role as a GitHub alternative

Sponsor: Logfire from Pydantic

Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack.
Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts.
It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language.
Every prompt, token count, and cost, right next to your vector searches and API calls.
You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server.
Stop guessing. Read the trace.
Pydantic Logfire. AI, it's still just engineering.
Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app.
Thanks to Pydantic for supporting the show.

Calvin #3: Brett Cannon: what's missing for reproducible builds on PyPI

Michael #4: Extra extra extra, hear all about it

Extras

Calvin:

Joke: Beware of dog