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Episode: Simon Willison: Using LLMs for Python Development
Pub date: 2025-01-24
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powered by Listen411 - fast audio-to-text and summarizationWhat are the current large language model (LLM) tools you can use to develop Python? What prompting techniques and strategies produce better results? This week on the show, we speak with Simon Willison about his LLM research and his exploration of writing Python code with these rapidly evolving tools.
Simon has been researching LLMs over the past two and a half years and documenting the results on his blog. He shares which models work best for writing Python versus JavaScript and compares coding tools and environments.
We discuss prompt engineering techniques and the first steps to take. Simon shares his enthusiasm for the usefulness of LLMs but cautions about the potential pitfalls.
Simon also shares how he got involved in open-source development and Django. He’s a proponent of starting a blog and shares how it opened doors for his career.
This episode is sponsored by Postman.
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00:00:00 – Introduction00:02:38 – How did you get involved in open source?00:04:04 – Writing an XML-RPC library00:04:40 – Working on Django in Lawrence, Kansas00:05:31 – Started building open-source collection00:06:52 – shot-scraper: taking automated screenshots of websites00:08:09 – First experiences with LLMs00:10:08 – 22 years of simonwillison.net00:18:22 – Navigating the hype and criticism of LLMs00:22:14 – Where to start with Python code and LLMs?00:26:22 – Sponsor: Postman00:27:13 – ChatGPT Canvas vs Code Interpreter00:28:23 – Asking nicely, tricking the system, and tipping?00:30:35 – More Code Interpreter and building a C extension00:32:05 – More details on Canvas 00:36:55 – What is a workflow for developing using LLMs?00:39:43 – Creating pieces of code vs a system00:42:00 – Workout program for prompting and pitfalls00:53:54 – Video Course Spotlight00:55:14 – Why an SVG of a pelican riding a bicycle?00:57:48 – Repeating a query and refining01:03:00 – Working in an IDE or text editor01:05:45 – David Crawshaw on writing code with LLMs 01:08:33 – Running an LLM locally to write code 01:14:02 – Staying out of the AGI conversation01:16:07 – What are you excited about in the world of Python?01:18:34 – What do you want to learn next?01:19:53 – How can people follow your work online?01:20:51 – Thanks and goodbyeSimon Willison’s Weblogshot-scraperMatt’s Script Archive, Inc. - Free Perl CGI ScriptsXR - my XML-RPC library, now in WordPress - GitHubAdrian Holovaty advertises for someone to join him working in Lawrence (May 2003) - Holovaty.comDatasette: An open source multi-tool for exploring and publishing dataMy SQLite tag page - Simon WillisonChatbot Arena: Free AI Chat to Compare & Test Best AI ChatbotsDeepSeek v3 notes on Christmas dayDeepSeek_V3 - PDFSimon Willison on code-interpreterGemini - Google DeepMindClaudeChatGPT Canvas can make API requests now, but it’s complicatedWelcome to Click — Click DocumentationMy first experience with Llama in March 2023I can now run a GPT-4 class model on my laptopUsing LLMs and Cursor to become a finisherGitHub Copilot - Your AI pair programmerIn Finland, classes in recognizing fake news, disinformation - Sunday Morning CBS404Media Podcast: Why We Cover AI the Way We DoJason Koebler from 404Media - tags on simonwillison.netBuilding Python tools with a one-shot prompt using uv run and Claude ProjectsHow I program with LLMs - crawshaw - 2025-01-06pelican-riding-a-bicycle - tags on simonwillison.netThings we learned about LLMs in 2024PyodideSimon Willison on pyodideastral-sh/uv: An extremely fast Python package and project managerSimon Willison on uvSimon Willison’s Newsletter - SubstackSemi-automating a Substack newsletter with an Observable notebookSimon Willison (@simonwillison.net) — BlueskySimon Willison (@[email protected]) - MastodonSimon Willison (@simonw) - XLevel up your Python skills with our expert-led courses:
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