Talk Python To Me

Every company has one. The little internal tool that Jane built back in 2021, and then Jane left. Nobody understands it, nobody will touch it. There are two unwritten rules around it: don't change it, it's working. And if you break it, you bought it. That's dark-matter enterprise software.



For every app you can actually see, there are ten of these sitting in the shadows, frozen. Michael Booth thinks that just changed. He read my article on hyper-personal software and ran with it, writing about hyper-team software: small teams inside big companies finally building the tools that were never going to get built.



We cover where this works, where it quietly goes wrong, and the guardrails that keep it from turning into a mess. Let's get into it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Python in Production

Talk Python Courses

Links from the show

Guest

Michael Booth: github.com

Talk Python AI Integrations: talkpython.fm/blog

From Hyper-Personal to Hyper-Team Software: Small Team-Built, AI-Assisted Tools Inside the Enterprise: www.databooth.com.au

What hyper-personal software looks like (MK's article): mkennedy.codes

Databooth Site: www.databooth.com.au

Wall Street just lost $285 billion because of 13 markdown files: martinalderson.com

SaaSpocalypse is real but everyone is panicking about the wrong thing: www.reddit.com

Warp Terminal: www.warp.dev

Watch this episode on YouTube: youtube.com

Episode #558 deep-dive: talkpython.fm/558

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

Security has always been the vegetables of software. Everyone agrees it matters, and somehow it never quite makes it onto the plate. At PyCon US this year, that changed. For the first time ever, security got its own dedicated, day-long track, one of just two at the whole conference, sitting right next to AI. And the room was packed to the back wall.



On this episode, I'm joined by the three people at the center of it. Seth Larson, Security Developer in Residence at the Python Software Foundation and, very recently, a CPython core developer. Juanita Gomez, a PhD researcher at UC Santa Cruz in open source security, who co-chaired the track. And Mike Fiedler, PyPI's Safety and Security Engineer, one of the very few people paid full-time to keep the packages you install safe.



We use the arc of the track's talks to take the temperature of Python security right now: supply chain attacks, dependency cooldowns, zero trust, SBOMs, and the push to bring Rust into CPython. And why not one of us thinks security is anywhere close to solved. Turns out that's the good news. It's why the room was full.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Talk Python Courses

Links from the show

Guests

Juanita Gomez: linkedin.com

Mike Fiedler: miketheman.dev

Seth Michael Larson: sethmlarson.dev

Trailblazing Python Security: us.pycon.org

Everything Security at PyCon US 2026 (PSF blog): pyfound.blogspot.com

Dependency Cooldowns: cooldowns.dev

Anatomy of a Phishing Campaign (Mike Fiedler) Recording: www.youtube.com

FedRAMP: www.gsa.gov

Zero Trust in 200ms: Implementing Identity-Per-Transaction with Python & Serverless-Tristan McKinnon: www.youtube.com

Rust for CPython project: blog.python.org

pre-PEP: discuss.python.org

Rust for CPython: Making Python Safer and More Robust for Everyone - Emma Smith: www.youtube.com

SBOMit: github.com

Asleep at the Wheel: Getting your SBOMs to pay attention... - Sanchit Sahay, Abhishek Reddypalle: www.youtube.com

Volatility: volatilityfoundation.org

Post Incident Runtime SBOM Generation from Python Memory - Hala Ali: www.youtube.com

zizmor: docs.zizmor.sh

GitHub Actions security in Python packages (Andrew Nesbitt write-up): nesbitt.io

andrew/pycon: data & analysis for the GitHub Actions security talk: github.com

GitHub Actions Security in Python Packages - Andrew Nesbitt: www.youtube.com

gh-profiler: examine a GitHub user's profile to gauge their contributions: github.com

PyCon US YouTube channel: www.youtube.com

SBOMit: adding verification to SBOMs (OpenSSF): openssf.org

Ecosystems: ecosyste.ms

Watch this episode on YouTube: youtube.com

Episode #557 deep-dive: talkpython.fm/557

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

For years, "Django and async" came with an asterisk. The docs themselves warned you off it. Scary performance notes, a story that felt half-finished. Well, that story just got rewritten, literally, and the person who rewrote it is here to tell you why the old framing was wrong.



Carlton Gibson is a former Django Fellow, sat on the security team for eight years, and he's on the steering council. On this episode we get into the async topic doc rewrite, what actually remains versus what was just fear, the new Tasks framework in 6.0, DB-level cascades and fetch modes landing in 6.1, and why free-threading is the bet that's about to pay off big for Django. If you've been told Django's async story isn't ready, this is the episode that puts that myth to bed.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Python in Production

Talk Python Courses

Links from the show

DjangoCon Europe: djangocon.eu

PyCon Italia: pycon.it

Django on the Med: djangomed.eu

Django Mantle: noumenal.es

PyPI: pypi.org

release notes: docs.djangoproject.com

on_delete: docs.djangoproject.com

Fetch modes: docs.djangoproject.com

HttpRequest.multipart_parser_class: docs.djangoproject.com

async topic doc: docs.djangoproject.com

docs: docs.djangoproject.com

DEP 14: github.com

django-tasks: github.com

django-tasks-local: github.com

Celery: docs.celeryq.dev

PEP 703: peps.python.org

free-threading HOWTO: docs.python.org

PEP 779: peps.python.org

ASGI: docs.djangoproject.com

PGBouncer: www.pgbouncer.org

Channels: channels.readthedocs.io

sync_to_async / async_to_sync: docs.djangoproject.com

noumenal.es: noumenal.es

Django Chat: djangochat.com

@carlton@fosstodon.org: fosstodon.org

Article: Cutting Python Web App Memory Over 31%: mkennedy.codes

Watch this episode on YouTube: youtube.com

Episode #556 deep-dive: talkpython.fm/556

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

Coding agents have gotten really good at one kind of work. You scope a feature, edit some files, run the tests, ship it. It all happens on disk. But that is not how data work feels. You load something, you look at it, you run a cell, you watch how it responds, and you decide the next move from whatever is sitting in memory. And until now, your agent couldn't see any of that. It only saw the files. Never the live state.



This episode, that wall comes down. marimo pair drops a coding agent right inside a running notebook, with full access to every variable Python is holding in memory. The notebook becomes a shared canvas. You point, it runs the code. You tell it to zoom in on the Picasso paintings, and the chart just updates. No MCP tools to wire up, no schema to describe. Just Python, and an agent that can finally see what you see. Trevor Manz is back to walk us through it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26

Talk Python Courses

Links from the show

marimo pair: marimo.io/pair

Course transcripts announcement: talkpython.fm/blog

anywidget: Jupyter Widgets made easy: talkpython.fm

marimo: marimo.io

blog: marimo.io

GitHub: github.com

given this: martinalderson.com

llms.txt: talkpython.fm

mcp: talkpython.fm

cli: talkpython.fm

open issues: github.com

Discord: marimo.io

Marimo Pair: marimo.io

OpenCode: opencode.ai

AI Tooling for Software Engineers in 2026: newsletter.pragmaticengineer.com

Watch this episode on YouTube: youtube.com

Episode #555 deep-dive: talkpython.fm/555

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

You ask an AI a question and it answers with total confidence. Most of the time, a confidently wrong answer is just an annoyance. But what if the question is medical, and there's a real patient on the other end? In that world, a hallucination isn't a bug, it's a patient-safety event. Sumit Gundawar is a London-based software engineer who builds the clinical platform for a UK longevity and aesthetic-medicine clinic, and his whole argument is that in high-stakes AI, the model is the easy part. Earning trust is the real engineering. We dig into grounding, refusal logic, human-in-the-loop design, and the messy frontier of longevity and biohacking, plus a live demo of an assistant that refuses to answer when it can't back up the claim. Let's get into it.

Episode sponsors

Six Feet Up

Talk Python Courses

Links from the show

Guest

Sumit Gundawar: linkedin.com

Course transcripts announcement: talkpython.fm/blog

Sumit Gundawar - JAX London Speaker: jaxlondon.com

Anthropic: anthropic.com

OpenAI Platform: platform.openai.com

Anthropic: anthropic.com

LangChain: langchain.com

OWASP: owasp.org

Pydantic: pydantic.dev

EU AI Act - Regulatory Framework: digital-strategy.ec.europa.eu

HIPAA - HHS: www.hhs.gov

NHS: www.nhs.uk

Llama: llama.com

Qwen - QwenLM on GitHub: github.com

OpenAI Platform: platform.openai.com

Hugging Face: huggingface.co

Llama: llama.com

Granola: www.granola.ai

HIPAA - HHS: www.hhs.gov

CodeRabbit: www.coderabbit.ai

Cursor Origin: cursor.com

GitHub Status: www.githubstatus.com

Midjourney Medical: www.midjourney.com

Neko Health: www.nekohealth.com

CERN: home.cern

ATLAS Experiment: atlas.cern

Watch this episode on YouTube: youtube.com

Episode #554 deep-dive: talkpython.fm/554

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