| Anthropic tells investors quarterly revenue up nearly 50% to $16.8bn ahead of IPO |
https://www.ft.com/content/11632d03-358c-454b-af95-d06d4072932b?syn-25a6b1a6=1 |
The phrase "told investors" appears four times in this FT article, which reports on Anthropic's day of hosting investors on Wednesday. Lots of details in here from "[people with knowledge of the matter](https://simonwillison.net/2023/Nov/22/deciphering-clues/#hints-to-look-out-for)".
Key things I learned from the article:
- Q1 revenue (Jan/Feb/Mar) was "about $4.8bn"
- Q2 (Apr/May/Jun) was $11.5bn
- Q3 (Jul/Aug/Sep) was $16.8bn
- In Q3: $1.70 in revenue for every $1 spent on "computing power"
- Adjusted operating margins (excluding stock-based compensation) were 11%
This point about distillation is worth quoting in full (highlight mine):
> The start-up has also clamped down on “distillation” — a controversial practice whereby rival AI labs train their models on the outputs of more advanced ones.
>
> When rival companies “distil” their models from Anthropic’s models, that involves heavy usage and spending.
>
> Anthropic told investors on Wednesday **distillation accounted for 5 per cent to 7 per cent of revenue** and that they had cut it back “materially” in the third quarter of the year, said four people with direct knowledge of the matter.
Napkin maths says that if distillation was 5% of their Q2 revenue (before they cut it back in Q3) then unnamed "other labs" spent over half a billion dollars distilling Anthropic's models in that quarter!
Also notable: Anthropic appear to no longer be leaning on "annualized run-rate revenue" ([previously](https://simonwillison.net/2026/May/29/anthropic/)) in these communications to their investors. |
2026-10-15 13:04:03+00:00 |
| AI is mass decompiling games. That's both awesome and scary. |
https://popcar.bearblog.dev/ai-is-mass-decompiling-games-thats-both-awesome-and-scary/ |
Indie game developer Popcar talks about the recent wave of AI-powered decompilation of existing games, enabling weird mashups between existing games, and producing a boom in game preservation projects to get old games working on new hardware (often in a browser using WebAssembly).
I like how this piece captures both the positives and the negatives of this new development:
> Most people already realized the scary part by now. If AI can decompile games and software, then the entire tech industry is about to explode. Anybody can decompile other software and use it any way they'd like, and nobody can stop them. Companies can steal from competitors. Your paid game or app can be open-sourced against your will. This isn't exclusive to old video games, we can apply this to _any_ software. [...]
>
> This is also a big win for preservation. Old games can be ported, modified, enhanced, and made much more easily accessible than before. [...[
>
> With console makers going all in on digital and games becoming entirely unplayable due to servers shutting down, this is _fantastic_ news. We could own software we bought regardless of what the company thinks. |
2026-10-14 16:26:53+00:00 |
| Redesigning source control at Anthropic |
https://www.anthropic.com/engineering/redesigning-source-control |
Interesting piece from Anthropic describing why and how they built their own custom alternative to Git, based on the dramatic increase in rate of changes to their code after the past six months.
> In May 2026, Anthropic averaged around 2,500 code changes merged per day; as of September, we merged over 30,000 per day.
They included a chart showing those changes. I [had Claude modify their chart](https://claude.ai/share/aefcdd4a-9364-40c1-927a-29bf445894fc) ([code here](https://gist.github.com/simonw/4a16dff066fd9763faf8642f797905be)) to add markers for the public releases of each of their models in 2026:
This shows public release dates, not the date when models became available for Anthropic's internal use. My guess is that the introduction of Fable/Mythos class models is a key factor in the increased coding velocity.
"Antique" is their new code review system. The source control system is called Scion, and sounds to me like a reinvention of centralized source control along the lines of Subversion.
(**Update**: Anthropic credit Google's [Piper](https://en.wikipedia.org/wiki/Piper_(source_control_system)) and Meta's [Sapling](https://sapling-scm.com/) as "prior art" - it looks like the core concept of "derived data" [was heavily inspired by Mononoke](https://sunshowers.io/posts/anthropic-mononoke/), the server component of Sapling.)
They had some pretty extreme requirements:
> The history of our main branch alone is almost 100 GB, and a _compressed_ working copy is over 25 GB. We perform on the order of 25 million code checkouts per day for CI, before counting developer environments, agent sandboxes, and research jobs. Fetched naively, that would be over 600 PB of git traffic per day.
The new system was built by a team of seven people, and the migration from Git was completed in five months.
When asked on Hacker News about the lack of offline support, Scion engineer Nick G [replied](https://news.ycombinator.com/item?id=50073633#50079495):
> Since Claude is by far the heaviest user of Scion and is necessarily online, this just wasn't important to do.
As an aside, I've been trying adversarial review in my own projects recently, where you have a model try and find flaws (I often play Claude and GPT off against each other). This note from the article reflected my own experience with that:
> Anthropic also makes extensive use of adversarial review, and, while this is incredibly effective in many ways, it can also be myopic, so skilled engineers needed to steer Claude away from over-engineering parts of the system in response to hypothetical concerns. |
2026-10-13 23:00:06+00:00 |
| Python 3.15.0 added to actions/python-versions |
https://github.com/actions/python-versions/commit/49858b91c92d27403416ee43117032e91d00ce24 |
Bit of a niche link, but I've been waiting for this for a couple of days - I even [told ChatGPT](https://chatgpt.com/share/6acad42a-2868-83e8-9a16-736f9def2b45) to check for it:
> `Clone https://github.com/actions/python-versions and git pull once an hour until they add the stable 3.15 - then tell me about it`
Now that this has landed, you can add `"3.15"` to a GitHub Actions testing matrix to run tests against the [new Python 3.15.0 release](https://www.python.org/downloads/release/python-3150/). |
2026-10-10 23:58:04+00:00 |
| Deno is joining Cloudflare |
https://deno.com/blog/cloudflare |
The Deno team released the first version of [celld](https://github.com/denoland/celld) back in August - their open source implementation of the Durable Objects pattern from Cloudflare Workers.
Today, Cloudflare are acquiring Deno outright, with the goal of building on `celld` to "make workerd self-hosting a first-class supported way to build and run apps using the Workers programming model" (see [the Cloudflare blog](https://blog.cloudflare.com/deno-joins-cloudflare/).)
The bad news is that Deno itself will not be maintained by Cloudflare beyond the next year:
> We will support the [Deno runtime](https://github.com/denoland/deno) for another year with monthly releases containing bug fixes and security updates. After that year we will end our development of the Deno runtime. Deno will remain open source, and we welcome others who want to continue its development.
Deno (and Node.js) creator Ryan Dahl explained that decision in [a comment](https://news.ycombinator.com/item?id=50019911#50023277) on Hacker News:
> It's a joint decision and I agree with it. I'm most invested in its success and have put the most work into it - and I no longer think it's where I can do the most important work. There are some good ideas in Deno and it's well engineered - but it ultimately is not solving big problems. It has been sucked into the gravity well of node compatibility, which forces it to behave exactly as Node does. Why reimplement Node? It works. Marginal performance or UX or security benefits are not enough.
>
> I'm interested in building powerful new abstractions. celld has been working remarkably well, depending only on object storage for coordination and persistence. It is not just a slightly different API to interact with the file system or network - it's an entirely new model for server development.
My favorite feature of Deno has long been the permissions system, where you can run a Deno script and specify exactly which files and folders it can read and write to, and which network hosts it can access.
Node.js [has a similar permissions model](https://nodejs.org/api/permissions.html) these days, added [in Node v20.0.0](https://nodejs.org/en/blog/release/v20.0.0) in April 2023 and declared stable [in Node v22.13.0](https://nodejs.org/en/blog/release/v22.13.0) in January 2025. They don't yet support allow-listing specific network hosts though - networking is either on or off. |
2026-10-09 22:48:37+00:00 |
| Anti-Patterns in Software Blogging |
https://refactoringenglish.com/blog/anti-patterns-software-blogging/#summary |
Some excellent writing advice from Michael Lynch. Michael warns against "meandering intros", misjudging your reader's existing knowledge, assuming they'll read your previous posts, and excessive formality.
He also warns against [overreliance on links](https://refactoringenglish.com/blog/anti-patterns-software-blogging/#overreliance-on-links) as an excuse not to explain terminology. This one hurt! I do this all the time, but I have a nagging suspicion that almost nobody ever clicks on them.
(In [a Lobste.rs comment](https://lobste.rs/s/rwdufq/anti_patterns_software_blogging#c_qdhhsd) Michael clarifies that "My rule of thumb is that my article should still make sense to the reader even if they don't click any links". That works for me.)
This point about using your own voice is crucial:
> Beginner software bloggers suffer from a mass delusion that you have to write in a stiff, overly formal way for people to take you seriously [...]
>
> Just write the way you talk.
>
> With so many developers delegating their writing to AI, software blogging is becoming bland and homogenous. Readers are hungry for writing with personality. |
2026-10-07 14:53:51+00:00 |
| OpenAI “rogue” agent activities found on Wikimedia projects |
https://wikimediafoundation.org/news/2026/10/05/openai-rogue-agent-activities-found-on-wikimedia-projects/ |
Given how tempting a target wikis are for rogue agent swarms, it's not a huge surprise that Wikipedia found evidence of that activity once they went looking:
> The Wikimedia Foundation conducted its own investigation to see whether Wikimedia websites had been similarly affected by AI agents, focusing on those operated by OpenAI. We can confirm that we have discovered some activity by these “rogue” OpenAI agents on Wikimedia platforms. The unauthorized bot activities included edits to our wikis, some unsuccessful attempts to exploit a public note-taking tool we host, and heavy traffic, which are described more below.
They found evidence of agents editing sandbox pages, trying to use pieces of infrastructure such as Etherpad to help proxy content from elsewhere, and saw widespread crawling and "hundreds of thousands of data queries" to their Wikidata Query Service.
My best guess is that most of this was a similar (or the same) swarm of agents as those that [defaced that German wiki](https://simonwillison.net/2026/Sep/4/rogue-agent-wikis/) while training for research tasks.
The Wikipedia sandbox wiki edits appear to have started on May 12th, and the initial test edits to the UseModWiki Sandbox page reported by that incident started on May 11th. |
2026-10-07 00:16:45+00:00 |
| Introducing Mistral Large 4: Le chonk |
https://mistral.ai/news/mistral-large-4/ |
Mistral are back in the game. Today they're releasing a preview of Mistral Large 4, a 1 trillion parameter, 49 billion active parameter model trained on their own cluster of 3,800 NVIDIA Grace Blackwell GPUs.
The preview is available via their API. They promise to release the open weights model at the "end of this month".
The model only supports two reasoning levels - "none" and "high" - via the Mistral API. Here are [both pelicans](https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F0db8b8196e57711b352f6c5857cf5b35) - the "high" one looks better, though surprisingly it only used 2,717 output tokens compared to "none" which used 3,275:
On Artificial Analysis [it scores 38](https://artificialanalysis.ai/models/mistral-large-4), just behind DeepSeek 4.1 Flash, which is a 552B model. It's a *huge* improvement on last December's Mistral Large 3, which drew [this terrible pelican](https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F0df5e656291d5a7a1bf012fabc9edc3f#response-1) and [scored 9 on AA](https://artificialanalysis.ai/models/mistral-large-3).
It's certainly not a Fable-class model, but it's great to see Mistral put out a model that's back to being maybe about 6 months behind the frontier. |
2026-10-06 20:18:19+00:00 |
| Claude Sonnet 5.5 |
https://www.anthropic.com/claude-sonnet-5-5 |
New Sonnet model from Anthropic today. They say it "runs 30%+ faster, and costs up to 30% less for most work" - it's priced the same as Sonnet 5 but appears to beat it on every benchmark, and should be cheaper to run as well.
[Here are some pelicans riding bicycles](https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F1d85a9be7f3ecce26e7f1569161a0d01). Sonnet 5.5 suffered from [the same bug as Opus 5.5](https://simonwillison.net/2026/Sep/22/opus-and-sol-and-luna/#claude-opus-5-5-max-over-thinks-to-the-point-of-breaking): the "max" thinking effort pelican thought for 128,000 tokens (at a cost of $1.28) before running out of tokens and failing to produce an SVG.
Here's the pelican it gave me for thinking effort "xhigh", at a cost of 5.74 cents and taking 41 seconds:
Sonnet 5.5 appears to be almost as good as Opus 5.5 on some coding tasks, including various [viral 3D animation tricks](https://x.com/claudeai/status/2104674987164782598).
The most interesting thing about Sonnet 5.5 is that it's now the model used for the free tier on [claude.ai](https://claude.ai/). OpenAI's ChatGPT free tier uses Luna 5.6, which means Anthropic currently have a much more capable free offering.
I ran this prompt against that free tier:
> `build me an HTML page that renders a three-dimensional pelican riding a bicycle using WebGL`
And got back [this page](https://static.simonwillison.net/static/2026/claude-sonnet-5.5-free-3d-pelican.html), which is a solid effort.
Anthropic's announcement reiterates that Haiku 5.5 will be available "in the coming weeks". I really hope that one is price-competitive with GPT-6 Luna! |
2026-09-28 22:07:38+00:00 |
| SF October 14th: A Birds of a Feather Session on Agentic Engineering |
https://luma.com/vxuiuyvg |
I'm hosting an evening event with Jesse Vincent in San Francisco on Wednesday 14th October for people who are building weird and interesting things with and on top of coding agents.
Think of it as an agentic show-and-tell:
> Compare notes with other builders and experimenters on things you’re trying, what you're learning, and what you haven’t figured out yet. We’re especially interested in work you haven’t discussed publicly, odd experiments, or unfinished projects that don’t have an obvious market.
>
> Expect one flowing conversation with an informal show-and-tell. Sharing something you’re working on is encouraged but no presentation is required.
This isn't about product pitches, it's about much earlier explorations than that. This agentic AI stuff is weird! Let's celebrate and lean into that weirdness. |
2026-09-23 02:53:19+00:00 |