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simon.fedi.simonwillison.net.ap.brid.gy
Simon Willison
@simon.fedi.simonwillison.net.ap.brid.gy
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Open source developer building tools to help journalists, archivists, librarians and others analyze, explore and publish their data. https://datasette.io […]

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simon.fedi.simonwillison.net.ap.brid.gy
I joined the Oxide and Friends annual predictions podcast episode this week - here are my 1, 3 and 6 year predictions for AI and LLMs (and Kākāpō parrots) https://simonwillison.net/2026/Jan/8/llm-predictions-for-2026/
1 year: It will become undeniable that LLMs write good code 1 year: We’re finally going to solve sandboxing 1 year: A “Challenger disaster” for coding agent security 1 year: Kākāpō parrots will have an outstanding breeding season 3 years: the coding agents Jevons paradox for software engineering will resolve, one way or the other 3 years: Someone will build a new browser using mainly AI-assisted coding and it won’t even be a surprise 6 years: Typing code by hand will go the way of punch cards
January 8, 2026 at 7:52 PM
simon.fedi.simonwillison.net.ap.brid.gy
Made lemon pigs! 🍋 🐷
Two lemon pigs - a small one and a big one - lemons with toothpick feet and cloves for eyes and little ears and slit mouths with coins in them
January 1, 2026 at 5:37 AM
simon.fedi.simonwillison.net.ap.brid.gy
Here's my enormous round-up of everything we learned about LLMs in 2025 - the third in my annual series of reviews of the past twelve months
https://simonwillison.net/2025/Dec/31/the-year-in-llms/
This year it's divided into 26 sections! This is the table of contents
The year of “reasoning” The year of agents The year of coding agents and Claude Code The year of LLMs on the command-line The year of YOLO and the Normalization of Deviance The year of $200/month subscriptions The year of top-ranked Chinese open weight models The year of long tasks The year of prompt-driven image editing The year models won gold in academic competitions The year that Llama lost its way The year that OpenAI lost their lead The year of Gemini The year of pelicans riding bicycles The year I built 110 tools The year of the snitch! The year of vibe coding The (only?) year of MCP The year of alarmingly AI-enabled browsers The year of the lethal trifecta The year of programming on my phone The year of conformance suites The year local models got good, but cloud models got even better The year of slop The year that data centers got extremely unpopular My own words of the year That’s a wrap for 2025
December 31, 2025 at 11:54 PM
simon.fedi.simonwillison.net.ap.brid.gy
Just pushed a new release of my LLM Python library and CLI tool for interacting with Large Language Models, adding support for GPT 5.1 and GPT 5.2 plus a few smaller bug fixes https://llm.datasette.io/en/stable/changelog.html#v0-28
0.28 (2025-12-12) New OpenAI models: gpt-5.1, gpt-5.1-chat-latest, gpt-5.2 and gpt-5.2-chat-latest. #1300, #1317 LLM now requires Python 3.10 or higher. Python 3.14 is now covered by the tests. When fetching URLs as fragments using llm -f URL, the request now includes a custom user-agent header: llm/VERSION (https://llm.datasette.io/). #1309 Fixed a bug where fragments were not correctly registered with their source when using llm chat. Thanks, Giuseppe Rota. #1316 Fixed some file descriptor leak warnings. Thanks, Eric Bloch. #1313 Fixed a deprecation warning for asyncio.iscoroutinefunction. Type annotations for the OpenAI Chat, AsyncChat and Completion execute() methods. Thanks, Arjan Mossel. #1315 The project now uses uv and dependency groups for development. See the updated contributing documentation. #1318
December 12, 2025 at 8:45 PM
simon.fedi.simonwillison.net.ap.brid.gy
I made that because now if a Python package doesn't have good release notes I can click "copy diff" and paste into Claude/ChatGPT/Gemini and get genuinely useful release notes a few seconds later

No need to even add a prompt, the models guess that's what you want from the diff
That tool showing the diff between Anthropic 0.74.0 and 0.74.1 - with a copy diff button Pasting the diff into Claude Opus 4.5 returns: This diff shows a patch release of the Anthropic Python SDK (0.74.0 → 0.74.1). The key change is: Structured Outputs Beta Version Update The beta header for structured outputs was updated from structured-outputs-2025-09-17t0 structured-outputs-2025-11-13 in the messages. py file. This affects the parse method in both the sync and async message clients. Everything else is just standard version bumping across the metadata files (METADATA, RECORD, _version.py). Is there something specific you'd like help with regarding this update?
December 10, 2025 at 10:29 PM
simon.fedi.simonwillison.net.ap.brid.gy
My most recent HTML tool is this one for loading code from the Python packaging index and displaying a diff between two versions - all running entirely in the browser, created using this prompt (which remixed a previous project) […]

[Original post on fedi.simonwillison.net]
Screenshot of the PyPI Package Changelog tool, which lets you type in a name - here "LLM" - and then view the diff between different versions of that package Build a new tool pypi-changelog.html which uses the PyPI API to get the wheel URLs of all available versions of a package, then it displays them in a list where each pair has a "Show changes" clickable in between them - clicking on that fetches the full contents of the wheels and displays a nicely rendered diff representing the difference between the two, as close to a standard diff format as you can get with JS libraries from CDNs, and when that is displayed there is a "Copy" button which copies that diff to the clipboard
December 10, 2025 at 10:01 PM
simon.fedi.simonwillison.net.ap.brid.gy
Here's the table of contents, - by patterns I'm talking about things like hitting CORS-enabled APIs, using localStorage and URLs to store state, loading dependencies from CDNs and taking extensive advantage of rich copy and paste for both input and output to the tools you build
The anatomy of an HTML tool Prototype with Artifacts or Canvas Switch to a coding agent for more complex projects Load dependencies from CDNs Host them somewhere else Take advantage of copy and paste Build debugging tools Persist state in the URL Use localStorage for secrets or larger state Collect CORS-enabled APIs LLMs can be called directly via CORS Don’t be afraid of opening files You can offer downloadable files too Pyodide can run Python code in the browser WebAssembly opens more possibilities Remix your previous tools Record the prompt and transcript Go forth and build
December 10, 2025 at 9:13 PM
simon.fedi.simonwillison.net.ap.brid.gy
A tiny TIL: if you are seeing "Error 153: Video player configuration error" on YouTube iframes embedded on your site a likely culprit is sending the "Referrer-Policy: same-origin" HTTP header (Django SecurityMiddleware sends this by default)

Switching […]

[Original post on fedi.simonwillison.net]
YouTube embed with a big ugly black square and text Watch video on YouTube, Error 153 Video player configuration error
December 1, 2025 at 5:34 AM
simon.fedi.simonwillison.net.ap.brid.gy
Out of curiosity I decided to try and run the numbers on how much Netflix you can watch for the energy cost of a ChatGPT prompt

As far as I can tell it's between 5.1 and 10.2 seconds, depending on which end of the 2019 IEA Netflix energy usage […]

[Original post on fedi.simonwillison.net]
In June 2025 Sam Altman claimed about ChatGPT that "the average query uses about 0.34 watt-hours". In March 2020 George Kamiya of the International Energy Agency estimated that "streaming a Netflix video in 2019 typically consumed 0.12-0.24kWh of electricity per hour" - that's 240 watt-hours per hour at the higher end. Assuming that higher end, a ChatGPT prompt by Sam Altman's estimate uses: 0.34 Wh / (240 Wh / 3600 seconds) = 5.1 seconds of Netflix Or double that, 10.2 seconds, if you take the lower end of the Netflix estimate instead. I'm always interested in anything that can help contextualize a number like "0.34 watt-hours" - I think this comparison to Netflix is a neat way of doing that. This is evidently not the whole story with regards to AI energy usage - training costs, data center buildout costs and the ongoing fierce competition between the providers all add up to a very significant carbon footprint for the AI industry as a whole.
November 29, 2025 at 2:17 AM
simon.fedi.simonwillison.net.ap.brid.gy
Updated my post with this section about their improved protection against prompt injection attacks - definitely better, but the problem is that if an attacker gets 10 tries they'll still succeed 1/3rd of the time! […]

[Original post on fedi.simonwillison.net]
Still susceptible to prompt injection # From the safety section of Anthropic’s announcement post: With Opus 4.5, we’ve made substantial progress in robustness against prompt injection attacks, which smuggle in deceptive instructions to fool the model into harmful behavior. Opus 4.5 is harder to trick with prompt injection than any other frontier model in the industry: Bar chart titled "Susceptibility to prompt-injection style attacks" On the one hand this looks great, it’s a clear improvement over previous models and the competition. What does the chart actually tell us though? It tells us that single attempts at prompt injection still work 1/20 times, and if an attacker can try ten different attacks that success rate goes up to 1/3! I still don’t think training models not to fall for prompt injection is the way forward here. We continue to need to design our applications
November 24, 2025 at 9:00 PM
simon.fedi.simonwillison.net.ap.brid.gy
Also notable is the new SynthID feature of the Gemini app - you can upload a photo to it and ask if it was generated by AI and it will detect the invisible SynthID watermarks added by Nano Banana Pro
Screenshot of a mobile chat interface displaying a conversation about AI image detection. The user has uploaded a photo showing two raccoons on a porch; one raccoon reaches inside a paper bag a bench while the other stands on the ground looking up at it. The conversation title reads "AI Image Creation Confirmed". The user asks, "Was this image created with ai?" The AI response, labeled "Analysis & 1 more", states: "Yes, it appears that all or part of this image was created with Google AI. SynthID detected a watermark in 25-50% of the image."
November 20, 2025 at 4:39 PM
simon.fedi.simonwillison.net.ap.brid.gy
For reference, here's a photo I took myself of a California brown pelican in breeding plumage a couple of weeks ago
A glorious California brown pelican perched on a rock by the water. It has a yellow tint to its head and a red spot near its throat.
November 18, 2025 at 7:14 PM
simon.fedi.simonwillison.net.ap.brid.gy
Here's the upgraded SVG pelican riding a bicycle prompt - I've added stricter requirements around the bicycle and specified that the pelican should be a California brown pelican in full breeding plumage
Generate an SVG of a California brown pelican riding a bicycle. The bicycle must have spokes and a correctly shaped bicycle frame. The pelican must have its characteristic large pouch, and there should be a clear indication of feathers. The pelican must be clearly pedaling the bicycle. The image should show the full breeding plumage of the California brown pelican. Gemini 3 Pro: It's clearly a pelican. It has all of the requested features. It looks a bit abstract though. GPT-5.1 The pelican is very round - it's a dumpy little fellow. Its body overlaps much of the bicycle. It has a lot of dorky charisma. Claude Sonnet 4.5. Oh dear. It has all of the requested components, but the bicycle is a bit wrong and the pelican is arranged in a very awkward shape.
November 18, 2025 at 7:09 PM
simon.fedi.simonwillison.net.ap.brid.gy
New release of my llm-anthropic plugin adding support for structured outputs (via the new official API - previously I faked it with tool calls) and Anthropic's web search feature https://github.com/simonw/llm-anthropic/releases/tag/0.22
Support for Claude's new structured outputs feature for Sonnet 4.5 and Opus 4.1. #54 Support for the web search tool using -o web_search 1 - thanks Nick Powell and Ian Langworth. #30
November 15, 2025 at 8:52 PM
simon.fedi.simonwillison.net.ap.brid.gy
I've now reached the "six coding agents in six terminal windows at once" phase of parallel agent delirium
https://simonwillison.net/2025/Nov/11/six-coding-agents-at-once/
November 11, 2025 at 11:03 PM
simon.fedi.simonwillison.net.ap.brid.gy
For comparison, here are the pelicans riding bicycles drawn by GPT-5-Codex-Mini (the new model), GPT-5-Codex and full GPT-5 - all produced via the same hacked version of the Codex CLI tool
GPT-5-Codex-Mini. This is terrible. The pelican is an abstract collection of shapes, the bicycle is likewise very messed up GPT-5 Codex. It's a dumpy little pelican with a weird face, not particularly great but better than Mini. GPT-5: Much better bicycle, pelican is a bit line-drawing-ish but does have the necessary parts in the right places
November 9, 2025 at 3:48 AM
simon.fedi.simonwillison.net.ap.brid.gy
OpenAI partially released a new model yesterday called GPT-5-Codex-Mini

No API access yet, but I did some truly horrible things to their Codex CLI app to get it to spit out this SVG of a pelican riding a bicycle
This is pretty bad. The bicycle is just about recognizable - a collection o f abstract lines and two circles - but the pelican is a weird little snow goblin tangled in a bundle of random lines hovering over the rest of the bike
November 9, 2025 at 3:38 AM
simon.fedi.simonwillison.net.ap.brid.gy
And here's an example of one of my code research prompts
Create a performance benchmark and feature comparison report on PyPI cmarkgfm compared to other popular Python markdown libraries—check all of them out from github and read the source to get an idea for features, then design and run a benchmark including generating some charts, then create a report in a new python-markdown-comparison folder (do not create a _summary.md file or edit anywhere outside of that folder). Make sure the performance chart images are directly displayed in the README.md in the folder.
November 6, 2025 at 4:06 PM
simon.fedi.simonwillison.net.ap.brid.gy
Here's my research repo - each of the 13 folders is a different research project, and the README is automatically updated by an LLM to include summaries describing each one https://github.com/simonw/research?tab=readme-ov-file#research-projects-carried-out-by-ai-tools
Screenshot of a README document with a right-side navigation panel; navigation menu shows: Filter headings search box, heading "Research projects carried out by AI tools" followed by project list: sqlite-query-linter (2025-11-04), h3-library-benchmark (2025-11-04), h3o-python (2025-11-03), wazero-python-claude (2025-11-02), datasette-plugin-skill (2025-10-24), blog-tags-scikit-learn (2025-10-24), cmarkgfm-in-pyodide (2025-10-22), python-markdown-comparison (2025-10-22), datasette-plugin-alpha-versions (2025-10-20), deepseck-ocr-nvidia-spark (2025-10-20), sqlite-permissions-poc (2025-10-20), minijinja-vs-jinja2 (2025-10-19), node-pyodide (2025-10-19)
November 6, 2025 at 4:03 PM
simon.fedi.simonwillison.net.ap.brid.gy
And in case you don't make it as far as the "miscellaneous tips" section, here's a bunch of lessons I learned about working with coding agents that I picked up along the way https://simonwillison.net/2025/Nov/4/datasette-10a20/#miscellaneous-tips-i-picked-up-along-the-way
When working on anything relating to plugins it’s vital to have at least a few real plugins that you upgrade in lock-step with the core changes. The tadd and radd shortcuts were invaluable for productively working on those plugins while I made changes to core. Coding agents make experiments much cheaper. I threw away so much code on the way to the final implementation, which was psychologically easier because the cost to create that code in the first place was so low. Tests, tests, tests. This project would have been impossible without that existing test suite. The additional tests we built along the way give me confidence that the new system is as robust as I need it to be. Claude writes good commit messages now! I finally gave in and let it write these—previously I’ve been determined to write them myself. It’s a big time saver to be able to say “write a tasteful commit message for these changes”. Claude is also great at breaking up changes into smaller commits. It can also productively rewrite history to make it easier to follow, especially useful if you’re still working in a branch. A really great way to review Claude’s changes is with the GitHub PR interface. You can attach comments to individual lines of code and then later prompt Claude like this: Use gh CLI to fetch comments on URL-to-PR and make the requested changes. This is a very quick way to apply little nitpick changes—rename this function, refactor this repeated code, add types here etc. The code I write with LLMs is higher quality code. I usually find myself making constant trade-offs while coding: this function would be neater if I extracted this helper, it would be nice to have inline documentation here, this changing this would be good but would break a dozen tests... for each of those I have to determine if the additional time is worth the benefit. Claude can apply changes so much faster than me that these calculations have changed—almost any improvement is worth applying, no matter how trivial, because the time cost is so low. Internal tools are cheap now. The new debugging interfaces were mostly written by Claude and are significantly nicer to use and look at than the hacky versions I would have knocked out myself, if I had even taken the extra time to build them. That trick with a Markdown file full of upgrade instructions works astonishingly well—it’s the same basic idea as Claude Skills. I maintain over 100 Datasette plugins now and I expect I’ll be automating all sorts of minor upgrades in the future using this technique.
November 4, 2025 at 9:47 PM
simon.fedi.simonwillison.net.ap.brid.gy
Just sent out the October edition of my sponsors-only monthly newsletter - you can pay me $10/month to send you less!

Here's the table of contents
https://simonwillison.net/2025/Nov/1/sponsors-only-newsletter/
Coding agents and "vibe engineering" Claude Code for web NVIDIA DGX Spark Claude Skills OpenAI DevDay and GitHub Universe Python 3.14 October in Chinese Al model releases Miscellaneous extras Tools I'm using at the moment
November 1, 2025 at 10:15 PM
simon.fedi.simonwillison.net.ap.brid.gy
Prompt -> Result https://tools.simonwillison.net/terminal-to-html
Build a new tool called terminal-to-html which lets the user copy RTF directly from their terminal and paste it into a paste area, it then produces the HTML version of that in a textarea with a copy button, below is a button that says "Save this to a Gist", and below that is a full preview. It will be very similar to the existing rtf-to-html.html tool but it doesn't show the raw RTF and it has that Save this to a Gist button That button should do the same trick that openai-audio-output.html does, with the same use of localStorage and the same flow to get users signed in with a token if they are not already So click the button, it asks the user to sign in if necessary, then it saves that HTML to a Gist in a file called index.html, gets back the Gist ID and shows the user the URL https://gistpreview.github.io/?6d778a8f9c4c2c005a189ff308c3bc47 - but with their gist ID in it They can see the URL, they can click it (do not use target="_blank") and there is also a "Copy URL" button to copy it to their clipboard Make the UI mobile friendly but also have it be courier green-text-on-black themed to reflect what it does If the user pastes and the pasted data is available as HTML but not as RTF skip the RTF step and process the HTML directly If the user pastes and it's only available as plain text then generate HTML that is just an open <pre> tag and their text and a closing </pre> tag Terminal to HTML app. Green glowing text on black. Instructions: Paste terminal output below. Supports RTF, HTML or plain text. There's an HTML Code area with a Copy HTML button, Save this to a Gist and a bunch of HTML. Below is the result of save to a gist showing a URL and a Copy URL button. Below that a preview with the Claude Code heading in ASCII art.
October 23, 2025 at 4:40 AM
simon.fedi.simonwillison.net.ap.brid.gy
Asynchronous coding agents are the fastest and safest route to running coding agents in a sandbox without constant supervision
The best sandboxes run on someone else's computer Claude Code for Web OpenAl Codex Cloud Gemini Jules ChatGPT & Claude code Interpreter
October 22, 2025 at 12:41 PM
simon.fedi.simonwillison.net.ap.brid.gy
Just for fun, I had Claude Code figure out how to run the ~2001-era Perl and C SLOCCount program in WebAssembly in the browser, complete with a UI for counting source code lines from pasted text, a GitHub repository or a zip file […]

[Original post on fedi.simonwillison.net]
October 22, 2025 at 6:23 AM
simon.fedi.simonwillison.net.ap.brid.gy
It's neat to see them encourage developers to add ARIA tags to pages though, an "agent" can be thought of as effectively another form of assistive technology
There was one other detail in the announcement post that caught my eye: Website owners can also add ARIA tags to improve how ChatGPT agent works for their websites in Atlas. Which links to this: ChatGPT Atlas uses ARIA tags---the same labels and roles that support screen readers---to interpret page structure and interactive elements. To improve compatibility, follow WAI-ARIA best practices by adding descriptive roles, labels, and states to interactive elements like buttons, menus, and forms. This helps ChatGPT recognize what each element does and interact with your site more accurately. A neat reminder that AI "agents" share many of the characteristics of assistive technologies, and benefit from the same affordances.
October 21, 2025 at 6:50 PM