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Google released Gemini 3.8 Live and 3.8 Live Extended Thinking today - two new speech-to-speech models that are a similar shape to OpenAI's GPT-Live family.
I pointed GPT-6 Astra Extra High at the documentation and had it build me this web UI for trying out the new models. You can select a model and voice preset, enter an optional system prompt and then start a voice conversation through your browser, including the ability to interrupt the model while it is talking.
The implementation uses no libraries. It connects to the wss://generativelanguage.googleapis.com/ws/google.ai.generativelanguage.v1alpha.GenerativeService.BidiGenerateContent?key=... WebSocket endpoint and uses a Web Audio API AudioContext for both capture and playback.
Here's the Gemini Live tutorial for getting started with that WebSockets API.
I built this little web app the other day to help edit the commit messages for the Datasette security releases. The initial commits were full of coding agent cruft and references to issue IDs from our private repository, so they weren't fit for publication.
If you want to edit the commit messages for a repository you can run it like this:
uvx commit-rewriter path/to/repo
Omit the path if you are already in the directory for that repo.
When you submit your edits the tool creates a timestamped branch of your current repo state - to allow you to revert if you need to - and then rewrites every commit from the first one you edited to the most recent.
I've added WebP support to my shot-scraper screenshot automation tool. You can now take a WebP screenshot of a web page like this:
shot-scraper https://simonwillison.net -o screenshot.webp --quality 80
The --quality option sets the quality - without that option the WebP file will be lossless.
In my experience WebP screenshots are almost always significantly smaller in file size than their JPEG or PNG equivalents. See the PR for some examples.
I shipped this feature so I could use it to generate the screenshot for my new commit-rewriter tool.
The Pacifica Pier shut down at the start of June after a crack in the concrete walkway made access to the pier unsafe.
It has since been entirely taken over by pelicans!
Comment My comment on Feeling sad about AI — Hacker News
I'm not sure how useful it is to say this, but I think a lot of people (myself included, a few years ago now) have been through this moment of existential crisis and come out the other side.
The initial reaction, when some coding agent does a piece of work that would have taken you a week in an hour and does it well, is to be very disheartened by it.
Once you come to terms with the idea that translating an exact specification into decent code isn't a unique skill any more, you can start looking at the larger set of problems that you face as a software engineer and realize that there is so much left, and your existing skill and experience mean you can master these new tools, provide value, and execute at a level far greater than anyone who is just getting started building software using agents without any of your depth.
If you don't want your profession to change at all then you're going to have a tough time with this - but that's surely been true for the history of software engineering? Has there ever been any stability to the tools and language we use beyond about a five year time horizon?
These changes are happening a bit faster, but if you chose software development as a passion you've opted into pretty frequent radical change from the start.
- Fix for compatibility with sqlite-utils 4.x. #85
See Datasette 1.0a39 and 0.65.4 security releases on the Datasette blog.
See Datasette 1.0a39 and 0.65.4 security releases on the Datasette blog.
I'm continuing to have a lot of fun with GPT-6 Astra and Blender (see my TIL).
As a big fan of the Imperial Fabergé Easter eggs, I've always thought it would be fun to make some new ones that celebrate popular culture.
Yesterday I decided to try out the new ChatGPT Images 2.5 by running this prompt:
Generate a photo of a faberge egg that's themed after the TV show Pluribus - research first
It gave me this - honestly not bad for a first attempt!
Then, just to see what would happen, I pasted that image into Codex running GPT-6 Astra (high) and prompted:
Use your blender local skill to create a blender model of this faverge egg
(Here's the skill file, which I created like this.)
It churned away for 17m51s and built me several .blend files. I already had this vibe-coded Blender viewing experiment lying around, so I added that to my tools collection and now you can use it to see my Pluribus blender model in your browser:
- New OpenAI model:
gpt-6-astrafor GPT-6 Astra.
I recorded a short demo video of my Equal Earth animation on my phone and wanted to publish an optimized version of that video (using FFMPEG) on my blog, so I had Claude Fable 5.1 in Claude Code for web build me this tool using the WebAssembly build of FFMPEG.
I got curious about the Equal Earth map projection that was recently voted on at the UN so I had GPT-6 Astra (medium) in ChatGPT Work build me this animated transition between Mercator and Equal Earth using D3.
Comment My comment on There's No Limit to How Bad Code Can Get — Lobste.rs
[In reply to a comment about burning it down to start from scratch when technical debt becomes overwhelming]
In my experience it's so rare for that to work.
You announce the old thing is irrecoverably drowning in tech debt. You spin up a team to rewrite it from scratch. Work begins.
Meanwhile the old thing remains a moving target: it's running the core business, so changes are still necessary. The developers working on it know that it's going to be made obsolete by the new thing soon, so they don't have any incentive to go beyond the smallest effort possible to add the new features. Technical debt continues to mount.
Meanwhile, the team working on the new thing are ambitious and probably a little naive. They start out at a great pace - it's greenfield after all - but as time progresses it becomes apparent that nobody fully understands the behavior and scope of the thing they are replacing. If it was well documented and tested it wouldn't need to be replaced, after all...
After months (or even years) without delivering value, the pressure is on to "ship it", so the new system is launched to handle a subset of what the old system handled - or often for some new feature that was too hard to build with the now mostly unmaintained old system.
... so now you have TWO systems in production - the janky old system that nobody wants to touch, and a new system which handles just a few production features and is 80% inactive code that is meant to replace the old system, eventually.
If you're really lucky the company won't have lost patience with the new system and will allow that work to continue. The longer this all takes, and the longer the old system stays in production and stubbornly continues to work, the higher the risk that "priorities have changed" and the new system total replacement work is abandoned, leaving you with two systems where you used to have one.
The best article I've read about completing this process responsibly is Migrations: the sole scalable fix to tech debt by Will Larson.
If I run into a situation like this in the future, my strong recommendation will be to shore up the old system with as much automated testing as possible and then seeing if targeted refactors can get it to the desired shape. My hunch is that in many cases that will have a much higher chance of success than the siren call of a greenfield replacement.
I've been having fun with Blender in ChatGPT Codex on my Mac recently. Getting it to work with coding agents is really easy: install the full Mac application from blender.org and run a prompt like this:
Use the already install /Applications/Blender to render a scene of a pelican riding a bicycle
In this case I followed that up with these two prompts:
OK add a background and a lot of flair
Then:
OK make it a whole lot better
And got this image, generated using Blender's Python API:
This was covered by my existing Codex subscription, but according to AgentsView it would have cost $4.24 at API prices for gpt-6-astra.
One new feature:
llm logs --usageMarkdown output now includes the response duration in milliseconds and as a human-readable duration.llm logs --shortincludes a newduration_msfield. #1653
Plus several contributed bug fixes, and a significant performance improvement to llm logs thanks to waveplate on GitHub, see also llm-openrouter 0.7.1.
Claude Fable 5.1, reasoning traces are now displayed by default for models that support them, plus a new llm_anthropic.ClaudeRefusal exception for when Claude throws a refusal.
- New model
gemini-3.8-flashfor Gemini 3.8 Flash, with low, medium and high thinking levels. #146- Fixed async responses failing to record the resolved model version. Thanks, Charlie Tonneslan. #137
Google released Gemini 3.8 Flash (and 3.8 Flash Cyber, but that's available to "trusted defenders" only) today.
Here are the pelicans for high, medium, and low. This is high:
For comparison, here are the same pelicans generated using Gemini 3.7 Flash.
Something I appreciate about Gemini Flash is that it's fast, cheap, and competent at things like HTML and JavaScript. I was messing around with it and prompted "make me a cool thing in html" and it built this, which is certainly a cool thing in HTML! Took 13 seconds, cost 1.8 cents.
If you click through to the demo you'll see one more thing I built with Gemini 3.8 Flash.
My markdown-svg-renderer tool lets me feed in the URL to a Gist with Markdown in and renders that markdown with fenced code blocks for SVG correctly rendered.
I used Gemini 3.8 Flash (with my very basic llm-coding-agent coding agent plugin) to add support for HTML as well, so now any HTML blocks in the Markdown are rendered using a sandboxed iframe. Here's the transcript.
I was helping Natalie gather some maps of local political boundaries (for the Granada Community Services District and the Midcoast Community Council) and found a need to display some GeoJSON files on a map and export that as a PNG. I asked GPT-5.6-Sol for suggestions of tools and it proactively built one. After some iterations using Claude Code for web and Fable 5.1 we got to this finished tool.
As for the GeoJSON.. it turns out if you ask ChatGPT Work to provide boundaries for almost anything it will churn away extracting and combining files from different Government data sources and build exactly what you need.
I got this polygon from:
I want a polygon that represents the exact boundary of the El Granada GCSD
And this one from:
Get me a GeoJSON file for the boundary (or boundaries if that makes sense) for the MCC - Midcoast Community Council - that operates near Half Moon Bay CA
Here's a link that displays both of them at the same time on the new GeoJSON map viewing tool.
"rows"fromexecute_sqlis now an array of objects. Previously it was an array of arrays. This should help weaker models avoid losing track of which positional array element maps to which column. #1- Now depends on
mcp>=2.1.1.
This is the first non-alpha release of the plugin. I'm confident it's ready as I've been using it quite a bit myself.
This release of the Anthropic plugin for LLM mainly provides compatibility with the recently released anthropic v1.0.0 Python library, which switches from httpx to httpx2. OpenAI made the same change in their v3.0.0 release two weeks ago.
Anthropic provide this migration guide for upgrading to 1.0, so I prompted Fable 5 in Claude Code with:
Upgrade to anthropic>=1 - read https://raw.githubusercontent.com/anthropics/anthropic-sdk-python/refs/heads/main/MIGRATION.md and get the tests passing
Here's the resulting PR.
Comment
My comment on What blog posts influenced your thinking the most? — Lobste.rs
An early Joel Spolsky one for me was The Law of Leaky Abstractions. I read that near the start of my career and it's encouraged me to always be looking for improved understanding of the layers under where I'm working, just in case one of those abstractions leaks.
A more recent one, from 2018, is Migrations: the sole scalable fix to tech debt by Will Larson. I absolutely love his idea that migrations (e.g. replacing one service with a new one, or switching database engines, or whatever) are part and parcel of software engineering and are a skill that you should invest in and get good at, not avoid or treat as special one-offs.
The Engineer/Manager Pendulum by Charity Majors was hugely influential for me. I was stuck in engineering management and worried that if I switched back to being an "Individual Contributor" (ugh I hate that term) I'd damage my career. Charity gave me permission to make the switch by pointing out that many of the most successful software developers pendulum from one track to the other multiple times over their career, and doing so makes you better at both sides.
# 14th September 2026, 8:21 pm / joel-spolsky, software-engineering, will-larson, charity-majors