Talk Python To Me Podcast Por Michael Kennedy arte de portada

Talk Python To Me

Talk Python To Me

De: Michael Kennedy
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Talk Python to Me is a weekly podcast hosted by developer and entrepreneur Michael Kennedy. We dive deep into the popular packages and software developers, data scientists, and incredible hobbyists doing amazing things with Python. If you're new to Python, you'll quickly learn the ins and outs of the community by hearing from the leaders. And if you've been Pythoning for years, you'll learn about your favorite packages and the hot new ones coming out of open source.Copyright 2015-2026
Episodios
  • #543: Deep Agents: LangChain's SDK for Agents That Plan and Delegate

    #543: Deep Agents: LangChain's SDK for Agents That Plan and Delegate
    Apr 1 2026
    When you type a question into ChatGPT, the model only has what you typed to work with. But tools like Claude Code can plan, iterate, test, and recover from mistakes. They work more like we do. The difference is the agent harness: Planning tools, file system access, sub-agents, and carefully crafted system prompts that turn a raw LLM into something genuinely capable. Sydney Runkle is back on Talk Python representing LangChain and their new open source library, Deep Agents: A framework for building your own deep agents with plain Python functions, middleware hooks, and MCP support. This is how the magic works under the hood. Episode sponsors Sentry Error Monitoring, Code talkpython26 Temporal Talk Python Courses Links from the show Guest Sydney Runkle: github.com Claude Code uses: x.com Deep Research: openai.com Manus: manus.im Blog post announcement: blog.langchain.com Claudes system prompt: github.com sub agents: docs.anthropic.com the quick start: docs.langchain.com CLIs: github.com Talk Python's CLI: talkpython.fm custom tools: docs.langchain.com DeepAgents Examples: github.com Custom Middleware: docs.langchain.com Built in middleware: docs.langchain.com Improving Deep Agents with harness engineering: blog.langchain.com Prebuilt middleware: docs.langchain.com Watch this episode on YouTube: youtube.com Episode #543 deep-dive: talkpython.fm/543 Episode transcripts: talkpython.fm Theme Song: Developer Rap 🥁 Served in a Flask 🎸: talkpython.fm/flasksong ---== Don't be a stranger ==--- YouTube: youtube.com/@talkpython Bluesky: @talkpython.fm Mastodon: @talkpython@fosstodon.org X.com: @talkpython Michael on Bluesky: @mkennedy.codes Michael on Mastodon: @mkennedy@fosstodon.org Michael on X.com: @mkennedy
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    1 h y 4 m
  • #542: Zensical - a modern static site generator

    #542: Zensical - a modern static site generator
    Mar 25 2026
    If you've built documentation in the Python ecosystem, chances are you've used Martin Donath's work. His Material for MKDocs powers docs for FastAPI, uv, AWS, OpenAI, and tens of thousands of other projects. But when MKDocs 2.0 took a direction that would break Material and 300 ecosystem plugins, Martin went back to the drawing board. The result is Zensical: A new static site generator with a Rust core, differential builds in milliseconds instead of minutes, and a migration path designed to bring the whole community along. Episode sponsors Sentry Error Monitoring, Code talkpython26 Talk Python Courses Links from the show Guest Martin Donath: github.com Zensical: zensical.org Material for MkDocs: squidfunk.github.io Getting Started: zensical.org Github pages: docs.github.com Cloudflare pages: pages.cloudflare.com Michaels Example: gist.github.com Material for MkDocs: zensical.org gohugo.io/content-management/shortcodes: gohugo.io a sense of size of the project: blobs.talkpython.fm Zensical Spark: zensical.org Watch this episode on YouTube: youtube.com Episode #542 deep-dive: talkpython.fm/542 Episode transcripts: talkpython.fm Theme Song: Developer Rap 🥁 Served in a Flask 🎸: talkpython.fm/flasksong ---== Don't be a stranger ==--- YouTube: youtube.com/@talkpython Bluesky: @talkpython.fm Mastodon: @talkpython@fosstodon.org X.com: @talkpython Michael on Bluesky: @mkennedy.codes Michael on Mastodon: @mkennedy@fosstodon.org Michael on X.com: @mkennedy
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    1 h y 4 m
  • #541: Monty - Python in Rust for AI

    #541: Monty - Python in Rust for AI
    Mar 19 2026
    When LLMs write code to accomplish a task, that code has to actually run somewhere. And right now, the options aren't great. Spin up a sandboxed container and you're paying a full second of cold start overhead plus the complexity of another service. Let the LLM loose on your actual machine and... well, you'd better be watching. On this episode, I sit down with Samuel Colvin, creator of Pydantic, now at 10 billion downloads, to explore Monty, a Python interpreter written from scratch in Rust, purpose-built to run LLM-generated code. It starts in microseconds, is completely sandboxed by design, and can even serialize its entire state to a database and resume later. We dig into why this deliberately limited interpreter might be exactly what the AI agent era needs. Episode sponsors Talk Python Courses Python in Production Links from the show Guest Samuel Colvin: github.com CPython: github.com IronPython: ironpython.net Jython: www.jython.org Pyodide: pyodide.com monty: github.com Pydantic AI: pydantic.dev Python AI conference: pyai.events bashkit: github.com just-bash: github.com Narwhals: narwhals-dev.github.io Polars: pola.rs Strands Agents: aws.amazon.com Subscribe Running Pydantic’s Monty Rust sandboxed Python subset in WebAssembly: simonwillison.net Rust Python: github.com Valgrind: valgrind.org Cod Speed: codspeed.io Watch this episode on YouTube: youtube.com Episode #541 deep-dive: talkpython.fm/541 Episode transcripts: talkpython.fm Theme Song: Developer Rap 🥁 Served in a Flask 🎸: talkpython.fm/flasksong ---== Don't be a stranger ==--- YouTube: youtube.com/@talkpython Bluesky: @talkpython.fm Mastodon: @talkpython@fosstodon.org X.com: @talkpython Michael on Bluesky: @mkennedy.codes Michael on Mastodon: @mkennedy@fosstodon.org Michael on X.com: @mkennedy
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    1 h y 6 m
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