Simon Willison’s Weblog

The A.I. Disruption We’ve Been Waiting for Has Arrived. New opinion piece from Paul Ford in the New York Times. Unsurprisingly for a piece by Paul it's packed with quoteworthy snippets, but a few stood out for me in particular.

Paul describes the November moment that so many other programmers have observed, and highlights Claude Code's ability to revive old side projects:

[Claude Code] was always a helpful coding assistant, but in November it suddenly got much better, and ever since I’ve been knocking off side projects that had sat in folders for a decade or longer. It’s fun to see old ideas come to life, so I keep a steady flow. Maybe it adds up to a half-hour a day of my time, and an hour of Claude’s.

November was, for me and many others in tech, a great surprise. Before, A.I. coding tools were often useful, but halting and clumsy. Now, the bot can run for a full hour and make whole, designed websites and apps that may be flawed, but credible. I spent an entire session of therapy talking about it.

And as the former CEO of a respected consultancy firm (Postlight) he's well positioned to evaluate the potential impact:

When you watch a large language model slice through some horrible, expensive problem — like migrating data from an old platform to a modern one — you feel the earth shifting. I was the chief executive of a software services firm, which made me a professional software cost estimator. When I rebooted my messy personal website a few weeks ago, I realized: I would have paid $25,000 for someone else to do this. When a friend asked me to convert a large, thorny data set, I downloaded it, cleaned it up and made it pretty and easy to explore. In the past I would have charged $350,000.

That last price is full 2021 retail — it implies a product manager, a designer, two engineers (one senior) and four to six months of design, coding and testing. Plus maintenance. Bespoke software is joltingly expensive. Today, though, when the stars align and my prompts work out, I can do hundreds of thousands of dollars worth of work for fun (fun for me) over weekends and evenings, for the price of the Claude $200-a-month plan.

He also neatly captures the inherent community tension involved in exploring this technology:

All of the people I love hate this stuff, and all the people I hate love it. And yet, likely because of the same personality flaws that drew me to technology in the first place, I am annoyingly excited.

# 5:07 pm / new-york-times, paul-ford, careers, ai, generative-ai, llms, ai-assisted-programming, ai-ethics, coding-agents, claude-code

Introducing Claude Sonnet 4.6 (via) Sonnet 4.6 is out today, and Anthropic claim it offers similar performance to November's Opus 4.5 while maintaining the Sonnet pricing of $3/million input and $15/million output tokens (the Opus models are $5/$25). Here's the system card PDF.

Sonnet 4.6 has a "reliable knowledge cutoff" of August 2025, compared to Opus 4.6's May 2025 and Haiku 4.5's February 2025. Both Opus and Sonnet default to 200,000 max input tokens but can stretch to 1 million in beta and at a higher cost.

I just released llm-anthropic 0.24 with support for both Sonnet 4.6 and Opus 4.6. Claude Code did most of the work - the new models had a fiddly amount of extra details around adaptive thinking and no longer supporting prefixes, as described in Anthropic's migration guide.

Here's what I got from:

uvx --with llm-anthropic llm 'Generate an SVG of a pelican riding a bicycle' -m claude-sonnet-4.6

The SVG comments include:

<!-- Hat (fun accessory) -->

I tried a second time and also got a top hat. Sonnet 4.6 apparently loves top hats!

For comparison, here's the pelican Opus 4.5 drew me in November:

And here's Anthropic's current best pelican, drawn by Opus 4.6 on February 5th:

Opus 4.6 produces the best pelican beak/pouch. I do think the top hat from Sonnet 4.6 is a nice touch though.

# 11:58 pm / ai, generative-ai, llms, llm, anthropic, claude, llm-pricing, pelican-riding-a-bicycle, llm-release, claude-code

Rodney v0.4.0. My Rodney CLI tool for browser automation attracted quite the flurry of PRs since I announced it last week. Here are the release notes for the just-released v0.4.0:

• Errors now use exit code 2, which means exit code 1 is just for for check failures. #15
• New rodney assert command for running JavaScript tests, exit code 1 if they fail. #19
• New directory-scoped sessions with --local/--global flags. #14
• New reload --hard and clear-cache commands. #17
• New rodney start --show option to make the browser window visible. Thanks, Antonio Cuni. #13
• New rodney connect PORT command to debug an already-running Chrome instance. Thanks, Peter Fraenkel. #12
• New RODNEY_HOME environment variable to support custom state directories. Thanks, Senko Rašić. #11
• New --insecure flag to ignore certificate errors. Thanks, Jakub Zgoliński. #10
• Windows support: avoid Setsid on Windows via build-tag helpers. Thanks, adm1neca. #18
• Tests now run on windows-latest and macos-latest in addition to Linux.

I've been using Showboat to create demos of new features - here those are for rodney assert, rodney reload --hard, rodney exit codes, and rodney start --local.

The rodney assert command is pretty neat: you can now Rodney to test a web app through multiple steps in a shell script that looks something like this (adapted from the README):

#!/bin/bash
set -euo pipefail

FAIL=0

check() {
    if ! "$@"; then
        echo "FAIL: $*"
        FAIL=1
    fi
}

rodney start
rodney open "https://example.com"
rodney waitstable

# Assert elements exist
check rodney exists "h1"

# Assert key elements are visible
check rodney visible "h1"
check rodney visible "#main-content"

# Assert JS expressions
check rodney assert 'document.title' 'Example Domain'
check rodney assert 'document.querySelectorAll("p").length' '2'

# Assert accessibility requirements
check rodney ax-find --role navigation

rodney stop

if [ "$FAIL" -ne 0 ]; then
    echo "Some checks failed"
    exit 1
fi
echo "All checks passed"

# 11:02 pm / browsers, projects, testing, annotated-release-notes, rodney

First kākāpō chick in four years hatches on Valentine’s Day (via) First chick of the 2026 breeding season!

Kākāpō Yasmine hatched an egg fostered from kākāpō Tīwhiri on Valentine's Day, bringing the total number of kākāpō to 237 – though it won’t be officially added to the population until it fledges.

Here's why the egg was fostered:

"Kākāpō mums typically have the best outcomes when raising a maximum of two chicks. Biological mum Tīwhiri has four fertile eggs this season already, while Yasmine, an experienced foster mum, had no fertile eggs."

And an update from conservation biologist Andrew Digby - a second chick hatched this morning!

The second #kakapo chick of the #kakapo2026 breeding season hatched this morning: Hine Taumai-A1-2026 on Ako's nest on Te Kākahu. We transferred the egg from Anchor two nights ago. This is Ako's first-ever chick, which is just a few hours old in this video.

That post has a video of mother and chick.

# 2:09 pm / kakapo

Qwen3.5: Towards Native Multimodal Agents. Alibaba's Qwen just released the first two models in the Qwen 3.5 series - one open weights, one proprietary. Both are multi-modal for vision input.

The open weight one is a Mixture of Experts model called Qwen3.5-397B-A17B. Interesting to see Qwen call out serving efficiency as a benefit of that architecture:

Built on an innovative hybrid architecture that fuses linear attention (via Gated Delta Networks) with a sparse mixture-of-experts, the model attains remarkable inference efficiency: although it comprises 397 billion total parameters, just 17 billion are activated per forward pass, optimizing both speed and cost without sacrificing capability.

It's 807GB on Hugging Face, and Unsloth have a collection of smaller GGUFs ranging in size from 94.2GB 1-bit to 462GB Q8_K_XL.

I got this pelican from the OpenRouter hosted model (transcript):

The proprietary hosted model is called Qwen3.5 Plus 2026-02-15, and is a little confusing. Qwen researcher Junyang Lin says:

Qwen3-Plus is a hosted API version of 397B. As the model natively supports 256K tokens, Qwen3.5-Plus supports 1M token context length. Additionally it supports search and code interpreter, which you can use on Qwen Chat with Auto mode.

Here's its pelican, which is similar in quality to the open weights model:

# 4:30 am / ai, generative-ai, llms, vision-llms, qwen, pelican-riding-a-bicycle, llm-release, openrouter, ai-in-china

The AI Vampire (via) Steve Yegge's take on agent fatigue, and its relationship to burnout.

Let's pretend you're the only person at your company using AI.

In Scenario A, you decide you're going to impress your employer, and work for 8 hours a day at 10x productivity. You knock it out of the park and make everyone else look terrible by comparison.

In that scenario, your employer captures 100% of the value from you adopting AI. You get nothing, or at any rate, it ain't gonna be 9x your salary. And everyone hates you now.

And you're exhausted. You're tired, Boss. You got nothing for it.

Congrats, you were just drained by a company. I've been drained to the point of burnout several times in my career, even at Google once or twice. But now with AI, it's oh, so much easier.

Steve reports needing more sleep due to the cognitive burden involved in agentic engineering, and notes that four hours of agent work a day is a more realistic pace:

I’ve argued that AI has turned us all into Jeff Bezos, by automating the easy work, and leaving us with all the difficult decisions, summaries, and problem-solving. I find that I am only really comfortable working at that pace for short bursts of a few hours once or occasionally twice a day, even with lots of practice.

# 11:59 pm / steve-yegge, ai, generative-ai, llms, ai-assisted-programming, ai-ethics, coding-agents, cognitive-debt

Gwtar: a static efficient single-file HTML format (via) Fascinating new project from Gwern Branwen and Said Achmiz that targets the challenge of combining large numbers of assets into a single archived HTML file without that file being inconvenient to view in a browser.

The key trick it uses is to fire window.stop() early in the page to prevent the browser from downloading the whole thing, then following that call with inline tar uncompressed content.

It can then make HTTP range requests to fetch content from that tar data on-demand when it is needed by the page.

The JavaScript that has already loaded rewrites asset URLs to point to https://localhost/ purely so that they will fail to load. Then it uses a PerformanceObserver to catch those attempted loads:

let perfObserver = new PerformanceObserver((entryList, observer) => {
    resourceURLStringsHandler(entryList.getEntries().map(entry => entry.name));
});
perfObserver.observe({ entryTypes: [ "resource" ] });

That resourceURLStringsHandler callback finds the resource if it is already loaded or fetches it with an HTTP range request otherwise and then inserts the resource in the right place using a blob: URL.

Here's what the window.stop() portion of the document looks like if you view the source:

Amusingly for an archive format it doesn't actually work if you open the file directly on your own computer. Here's what you see if you try to do that:

You are seeing this message, instead of the page you should be seeing, because gwtar files cannot be opened locally (due to web browser security restrictions).

To open this page on your computer, use the following shell command:

perl -ne'print $_ if $x; $x=1 if /<!-- GWTAR END/' < foo.gwtar.html | tar --extract

Then open the file foo.html in any web browser.

# 6:26 pm / archiving, html, javascript

How Generative and Agentic AI Shift Concern from Technical Debt to Cognitive Debt (via) This piece by Margaret-Anne Storey is the best explanation of the term cognitive debt I've seen so far.

Cognitive debt, a term gaining traction recently, instead communicates the notion that the debt compounded from going fast lives in the brains of the developers and affects their lived experiences and abilities to “go fast” or to make changes. Even if AI agents produce code that could be easy to understand, the humans involved may have simply lost the plot and may not understand what the program is supposed to do, how their intentions were implemented, or how to possibly change it.

Margaret-Anne expands on this further with an anecdote about a student team she coached:

But by weeks 7 or 8, one team hit a wall. They could no longer make even simple changes without breaking something unexpected. When I met with them, the team initially blamed technical debt: messy code, poor architecture, hurried implementations. But as we dug deeper, the real problem emerged: no one on the team could explain why certain design decisions had been made or how different parts of the system were supposed to work together. The code might have been messy, but the bigger issue was that the theory of the system, their shared understanding, had fragmented or disappeared entirely. They had accumulated cognitive debt faster than technical debt, and it paralyzed them.

I've experienced this myself on some of my more ambitious vibe-code-adjacent projects. I've been experimenting with prompting entire new features into existence without reviewing their implementations and, while it works surprisingly well, I've found myself getting lost in my own projects.

I no longer have a firm mental model of what they can do and how they work, which means each additional feature becomes harder to reason about, eventually leading me to lose the ability to make confident decisions about where to go next.

# 5:20 am / definitions, ai, generative-ai, llms, ai-assisted-programming, vibe-coding, cognitive-debt

Launching Interop 2026. Jake Archibald reports on Interop 2026, the initiative between Apple, Google, Igalia, Microsoft, and Mozilla to collaborate on ensuring a targeted set of web platform features reach cross-browser parity over the course of the year.

I hadn't realized how influential and successful the Interop series has been. It started back in 2021 as Compat 2021 before being rebranded to Interop in 2022.

The dashboards for each year can be seen here, and they demonstrate how wildly effective the program has been: 2021, 2022, 2023, 2024, 2025, 2026.

Here's the progress chart for 2025, which shows every browser vendor racing towards a 95%+ score by the end of the year:

The feature I'm most excited about in 2026 is Cross-document View Transitions, building on the successful 2025 target of Same-Document View Transitions. This will provide fancy SPA-style transitions between pages on websites with no JavaScript at all.

As a keen WebAssembly tinkerer I'm also intrigued by this one:

JavaScript Promise Integration for Wasm allows WebAssembly to asynchronously 'suspend', waiting on the result of an external promise. This simplifies the compilation of languages like C/C++ which expect APIs to run synchronously.

# 4:33 am / browsers, css, javascript, web-standards, webassembly, jake-archibald