CSS Modules work well for smaller MPAs, but as an app starts growing in size, atomic CSS in general, and StyleX in particular, starts to make more sense. 🧵

wow. i just got a fallback chain all the way from fable 5 -> opus 5 -> opus 4.8 -> fucking sonnet 4.6. crazy stuff

Very hot take: you should not be building a software factory

A short story about deferring tech choices to thought leaders: Early days at Disqus (~2010-2012), we made several frontend choices based largely on what thought leaders were promoting at the time. One example: there was a big movement toward "micro-frameworks." Instead of larger, well-tested libraries like jQuery, you'd stitch together tiny interoperable micro libraries (Ender.js was one). Disqus was an embeddable JavaScript app, so file size mattered. It fit our use case, so we went with it. Then it went live, and we were serving millions of users. The reality of those choices became clear. Micro libraries meant that instead of one good semi-bloated library, you ran 6-7 smaller, less-tested, crappier ones. We burned a ton of cycles fixing bugs and covering corner cases when we could've been shipping product. We made a few choices like this. At conferences, I'd track down those same thought leaders and ask for advice. "I'm hitting problem X, Y, Z. How did you solve this?" That's when I learned my lesson: they rarely had answers, because they'd never reached our scale. Their energy went into promoting new stuff, not running it. You should know this has never stopped. It's happening right now with AI. It'll happen again with whatever comes next. Do your own homework. Test a lot. Don't just go with what somebody tells you.

Why Remote Work is White Collar Fraud. "I have a three-year-old and a five-year-old. The idea that I could do any work at my house is like a total fantasy. The kids come home at 3pm, your work day needs to keep going. I'm highly against it." @typesfast

Massive output uptick due to agentic AI. Complete flat adoption.

🦔Uber's COO Andrew Macdonald said on Saturday that the company is having a harder time justifying its AI spend. After CTO Praveen Neppalli Naga went viral in April for admitting Uber burned through its 2026 Claude Code budget in four months, senior engineering leaders concluded higher token usage was not translating into proportionally more useful product. Macdonald said the link between AI consumption and shipped features is "not there yet." CEO Dara Khosrowshahi confirmed on the earnings call that Uber is slowing hiring to fund its AI spend. Duolingo also walked back its decision to include AI usage in performance reviews last month. My Take Uber is the first major enterprise where the C-suite has publicly admitted, on the record, that the AI productivity story is not closing for them. That matters because Uber is not a skeptic. The company went all-in on AI tooling, set internal targets, and burned through its annual research and development budget in four months trying to make it work. The conclusion from the people running the experiment is that tokens consumed and value shipped are not the same number, and management is finally noticing. Duolingo's reversal lands in the same week for a reason. CEO Luis von Ahn said employees were asking whether they needed to use AI just to use AI, which is Goodhart's Law showing up in a performance review system. When usage becomes the metric, employees optimize for usage, not output. Microsoft canceled internal Claude Code licenses, Google AI Pro stripped credits from paid subscribers, and now Uber is admitting the ROI does not close at scale. The narrative has shifted in the last 30 days from "AI productivity is here" to "AI productivity is harder to measure than we thought." The companies pushing tokenmaxxing internally are now the same companies signaling cost pressure externally. The IPO calendar for OpenAI and Anthropic is going to get a lot more complicated if the largest enterprise customers keep saying this out loud. Hedgie🤗