Simon WillisonModify

2026-02-16 05:06:44

We coined a new term on the Oxide and Friends podcast last month (primary credit to Adam Leventhal) covering the sense of psychological ennui leading into existential dread that many software developers are feeling thanks to the encroachment of generative AI into their field of work.

We're calling it Deep Blue.

You can listen to it being coined in real time from 47:15 in the episode. I've included a transcript below.

Deep Blue is a very real issue.

Becoming a professional software engineer is hard. Getting good enough for people to pay you money to write software takes years of dedicated work. The rewards are significant: this is a well compensated career which opens up a lot of great opportunities.

It's also a career that's mostly free from gatekeepers and expensive prerequisites. You don't need an expensive degree or accreditation. A laptop, an internet connection and a lot of time and curiosity is enough to get you started.

And it rewards the nerds! Spending your teenage years tinkering with computers turned out to be a very smart investment in your future.

The idea that this could all be stripped away by a chatbot is deeply upsetting.

I've seen signs of Deep Blue in most of the online communities I spend time in. I've even faced accusations from my peers that I am actively harming their future careers through my work helping people understand how well AI-assisted programming can work.

I think this is an issue which is causing genuine mental anguish for a lot of people in our community. Giving it a name makes it easier for us to have conversations about it.

My experiences of Deep Blue

I distinctly remember my first experience of Deep Blue. For me it was triggered by ChatGPT Code Interpreter back in early 2023.

My primary project is Datasette, an ecosystem of open source tools for telling stories with data. I had dedicated myself to the challenge of helping people (initially focusing on journalists) clean up, analyze and find meaning in data, in all sorts of shapes and sizes.

I expected I would need to build a lot of software for this! It felt like a challenge that could keep me happily engaged for many years to come.

Then I tried uploading a CSV file of San Francisco Police Department Incident Reports - hundreds of thousands of rows - to ChatGPT Code Interpreter and... it did every piece of data cleanup and analysis I had on my napkin roadmap for the next few years with a couple of prompts.

It even converted the data into a neatly normalized SQLite database and let me download the result!

I remember having two competing thoughts in parallel.

On the one hand, as somebody who wants journalists to be able to do more with data, this felt like a huge breakthrough. Imagine giving every journalist in the world an on-demand analyst who could help them tackle any data question they could think of!

But on the other hand... what was I even for? My confidence in the value of my own projects took a painful hit. Was the path I'd chosen for myself suddenly a dead end?

I've had some further pangs of Deep Blue just in the past few weeks, thanks to the Claude Opus 4.5/4.6 and GPT-5.2/5.3 coding agent effect. As many other people are also observing, the latest generation of coding agents, given the right prompts, really can churn away for a few minutes to several hours and produce working, documented and fully tested software that exactly matches the criteria they were given.

"The code they write isn't any good" doesn't really cut it any more.

A lightly edited transcript

Bryan: I think that we're going to see a real problem with AI induced ennui where software engineers in particular get listless because the AI can do anything. Simon, what do you think about that?

Simon: Definitely. Anyone who's paying close attention to coding agents is feeling some of that already. There's an extent where you sort of get over it when you realize that you're still useful, even though your ability to memorize the syntax of program languages is completely irrelevant now.

Something I see a lot of is people out there who are having existential crises and are very, very unhappy because they're like, "I dedicated my career to learning this thing and now it just does it. What am I even for?". I will very happily try and convince those people that they are for a whole bunch of things and that none of that experience they've accumulated has gone to waste, but psychologically it's a difficult time for software engineers.

[...]

Bryan: Okay, so I'm going to predict that we name that. Whatever that is, we have a name for that kind of feeling and that kind of, whether you want to call it a blueness or a loss of purpose, and that we're kind of trying to address it collectively in a directed way.

Adam: Okay, this is your big moment. Pick the name. If you call your shot from here, this is you pointing to the stands. You know, I – Like deep blue, you know.

Bryan: Yeah, deep blue. I like that. I like deep blue. Deep blue. Oh, did you walk me into that, you bastard? You just blew out the candles on my birthday cake.

It wasn't my big moment at all. That was your big moment. No, that is, Adam, that is very good. That is deep blue.

Simon: All of the chess players and the Go players went through this a decade ago and they have come out stronger.

Turns out it was more than a decade ago: Deep Blue defeated Garry Kasparov in 1997.

Tags: definitions, careers, ai, generative-ai, llms, ai-assisted-programming, oxide, bryan-cantrill, ai-ethics, coding-agents

2026-02-16 02:26:08

Gwtar: a static efficient single-file HTML format

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.

Via Hacker News

Tags: archiving, html, javascript

2026-02-16 01:23:28

It's wild that the first commit to OpenClaw was on November 25th 2025, and less than three months later it's hit 10,000 commits from 600 contributors, attracted 196,000 GitHub stars and sort-of been featured in an extremely vague Super Bowl commercial for AI.com.

Quoting AI.com founder Kris Marszalek, purchaser of the most expensive domain in history for $70m:

ai.com is the world’s first easy-to-use and secure implementation of OpenClaw, the open source agent framework that went viral two weeks ago; we made it easy to use without any technical skills, while hardening security to keep your data safe.

Looks like vaporware to me - all you can do right now is reserve a handle - but it's still remarkable to see an open source project get to that level of hype in such a short space of time.

Tags: ai-agents, openclaw, ai, open-source, domains

2026-02-15 21:36:20

I saw yet another “CSS is a massively bloated mess” whine and I’m like. My dude. My brother in Chromium. It is trying as hard as it can to express the totality of visual presentation and layout design and typography and animation and digital interactivity and a few other things in a human-readable text format. It’s not bloated, it’s fantastically ambitious. Its reach is greater than most of us can hope to grasp. Put some respect on its name.

— Eric Meyer

Tags: css, web-standards, eric-meyer

2026-02-15 13:20:11

How Generative and Agentic AI Shift Concern from Technical Debt to Cognitive Debt

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.

Via Martin Fowler

Tags: definitions, ai, generative-ai, llms, ai-assisted-programming, vibe-coding

2026-02-15 12:33:22

Launching Interop 2026

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.

Tags: browsers, css, javascript, web-standards, webassembly, jake-archibald