How can you improve your LLM agent systems through specification enrichment? What are the advantages of having an LLM act as a judge within an agent system? This week on the show, Senior IEEE Member and Quality Engineer Suneet Malhotra joins us to discuss building and evaluating agentic architecture.

Suneet Malhotra is an independent practitioner-researcher with 18 years of experience in Quality Engineering (QE) and test automation for consumer-scale platforms. He discusses building specification-enrichment loops, monitoring performance, and using Cohen’s kappa to measure agreement between LLM judgments.

Suneet is currently publishing multiple papers that are under peer review on these topics. He also provides links to his work and GitHub projects if you want to experiment with these concepts and methods yourself.

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Video Course Spotlight: Testing MCP Servers With a Python MCP Client

Learn how to build a Python MCP client that tests MCP servers from your terminal. List their tools, prompts, and resources, then call each one.

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How do you avoid the risk of running a Python application locally that could be malicious, break your code, or leak private data? How can you create a sandboxed local environment using WASM and MicroPython? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

We cover a recent article by previous guest Simon Willison titled “Running Python code in a sandbox with MicroPython and WASM.” Simon has been experimenting for years on how to run Python code in a sandbox to reduce the risk of trying out new software, untrusted libraries, and wild ideas. He’s developed a solution using WASM and MicroPython and is sharing it as an alpha package on PyPI.

We also share other articles and projects from the Python community, including new releases, community announcements, a roundup of recent Real Python tutorials and video courses, a plugin case study using Pluggy, a look at whether you’re expected to run five type-checkers now, wrapping programs using the subprocess module, a project for star charts and maps, and a tool for trend detection in Python.

This episode is sponsored by DataDriven.

Spotlight: Codex for Python Developers: Hands-On Agentic Coding Course

Most Python developers use AI as fancy autocomplete. This 2-day live course teaches you to build entire projects with Codex, an AI agent that works inside your codebase.

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Do you feel like your Python skills are atrophying after using LLM coding tools? How do you add the right kind of friction into your coding routine to keep your developer instincts sharp? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

We discuss a recent article by previous guest Bob Belderbos about developers keeping their instincts when AI is writing the code. He stresses the importance of the right kind of friction for maintaining skills and scheduling a deliberate coding practice routine.

We also share other articles and projects from the Python community, including new releases, a roundup of recent Real Python tutorials and video courses, sending emails with Python, libraries to enhance your Python Polars workflows, exploring Django Integrity-Policy, a next-generation HTTP client for Python, and a project to detect lazy imports incompatibilities.

This episode is sponsored by AURI by Endor Labs

Course Spotlight: Accessing Multiple AI Models With the OpenRouter API

Access models from popular AI providers in Python through OpenRouter’s unified API with smart routing, fallbacks, and cost controls.

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What’s happening at EuroPython 2026? The conference celebrates its 25th anniversary this year in Kraków, Poland. This week on the show, organizers Mia Bajić and Daria Linhart Grudzien join me to discuss this year’s conference.

Mia serves as the Vice Chair of the EuroPython Society, and Daria leads the EuroPython communications team. We dig into the details of the conference, including the wide variety of tracks, the reasoning for selecting the location, and the additional activities surrounding the event.

We talk about volunteering, organizing, and continuing support for conferences. Mia and Daria also share the talks they’re excited to check out and how they use Python currently.

Course Spotlight: Building Command Line Interfaces With argparse

In this step-by-step Python video course, you’ll learn how to take your command line Python scripts to the next level by adding a convenient command line interface that you can write with argparse.

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How can you easily reduce the size of a Python Docker container? What are the exceptions you should catch in your code? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

We cover a tutorial by Khuyen Tran at CodeCut about shrinking the size of a Python Docker container. The piece explores SlimToolKit, which analyzes a container at runtime, identifies what files are used, and then builds a minimal image with only those dependencies.

We dig into a recent piece by Trey Hunner about Python exceptions. When trying to determine a strategy to handle potential errors, which exceptions should you catch and which should you leave unhandled?

We also share other articles and projects from the Python community, including recent releases, two PEPs that have been deferred to 3.16, a critical vulnerability in an open-source ASGI framework, resolving a lazy import manually, a project to anonymize sensitive PII data, and a tool for loading Django settings from a TOML file.

This episode is sponsored by AURI by Endor Labs.

Course Spotlight: Raising and Handling Python Exceptions

In this course, you’ll learn what an exception is and how it differs from a syntax error. You’ll learn about raising exceptions, making assertions, and catching exceptions to change the control flow of your program using the try, except, else, and finally keywords.

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Have you ever been confused by the naming of modules you’re importing from a package? Is there a standard way to organize and name your Python virtual environments? This week on the show, Brett Cannon returns to discuss the Python Enhancement Proposals (PEPs) he’s been working on recently.

We start with PEP 794, which extends the metadata fields for Python packages to specify the import names a project provides. The metadata will help developers identify the correct project to install when they know the import name or the importable module names a project provides once installed.

We dive back into WebAssembly to discuss PEP 816, which specifies the WASI support in CPython releases. We also wade into the controversy around PEP 832, which proposes standards around naming and the discovery of virtual environments.

Brett shares his motivation for being a prolific author and supporter of PEPs. We discuss his promotion of standards and protocols to simplify the Python ecosystem for current and future developers.

Course Spotlight: Tapping Into the Zen of Python

Explore the Zen of Python and its 19 guiding principles for writing readable, practical code. Learn its history, jokes, and meaning.

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How can you avoid schema problems in your Polars data pipeline when adding new columns? How can you quickly examine a GitHub user’s profile to decide how much to invest in their contributions? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

Christopher shares a recent article about handling schema issues in Python Polars. The piece covers ways that a schema change can break your data pipeline. It provides strategies to avoid and resolve issues.

We cover a recent project from previous guest Eric Matthes to investigate GitHub profiles of a potential contributor. With the rise of AI-slop pull requests, the tool can provide valuable background on the user.

We also share other articles and projects from the Python community, including recent releases, exploring four different “get” special methods, what’s new in Pip 26.1, inverse Sapir-Whorf and programming languages, and a Python scripting framework for CAD.

This episode is sponsored by Six Feet Up.

Course Spotlight: Working With Python Polars

Welcome to the world of Polars, a powerful DataFrame library for Python. In this video course, you’ll get a hands-on introduction to Polars’ core features and see why this library is catching so much buzz.

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What are the limitations of using a file-based agent workflow? Why do massive context windows tend to collapse? This week on the show, Mikiko Bazeley from MongoDB joins us to discuss agentic architecture and context engineering.

Mikiko is an applied AI engineer. She helps developers and organizations build AI and ML applications using MongoDB. We dig into the debate of files versus a database. What are some of the limitations of building an agent with just a folder of files?

We explore the surprising limitations of massive context windows and strategies for fixing them. Mikiko also shares advice and resources to help you get up to speed on building your own agent skills. Our conversation touches on multiple topics in the current development landscape.

This episode is sponsored by SerpApi.

Video Course Spotlight: Building Type-Safe LLM Agents With Pydantic AI

Build type-safe LLM agents in Python with Pydantic AI using structured outputs, function calling, and dependency injection.

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What if you could build charts in Python by describing what your data means, instead of scripting every visual detail? Christopher Trudeau is back on the show this week with another batch of PyCoder’s Weekly articles and projects.

We cover a recent Real Python article about the data visualization library Altair. Most tools require you to write detailed boilerplate code to set up the axis and figure. Altair follows a declarative approach where you specify which columns go to which axis, the type of chart or plot, and what should be interactive.

We also share other articles and projects from the Python community, including recent releases, clarifying the differences between iterators and iterables, decoupling your business logic from the Django ORM, comparing an LLM-based tool for web scraping against Playwright, a neural network emulator for guitar amplifiers, and a CLI tool to generate ASCII art of the current moon phase.

This episode is sponsored by Build Your Own Coding Agent.

Video Course Spotlight: Use Codex CLI to Enhance Your Python Projects

Learn how to use Codex CLI to add features to Python projects directly from your terminal, without needing a browser or IDE plugins.

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How do you add agent skills to your data science workflow? How can a coding agent assist with data wrangling and research? This week on the show, Trevor Manz from marimo joins us to discuss marimo pair.

Trevor is a founding engineer at marimo, where he’s been working on integrating LLM tools with marimo. We discuss the balancing act of building a skill and determining how to give an agent access to all the variables in a notebook. He shares how they built a specialized reactive REPL that eliminates hidden state and allows the agent to continue constructing a reproducible Python program.

We dig into installing and getting started with marimo pair. Trevor also covers several of the tasks an agent can tackle in a data science workflow.

Video Course Spotlight: Getting Started With marimo Notebooks

Discover how marimo notebook simplifies coding with reactive updates, UI elements, and sandboxing for safe, sharable notebooks.

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