Why we should expect AI capabilities to keep being extremely uneven, and why that matters
Taking Jaggedness Seriously
Why we should expect AI capabilities to keep being extremely uneven, and why that matters
The Bitter Lesson: Rethinking How We Build AI Systems
The Race for AI Progress In 2019, Richard Sutton, wrote his groundbreaking essay titled ‘The Bitter Lesson’. Simply put, the essay concludes that systems which get better with higher compute beat the systems that do not. Or specifically in AI: raw computing power consistently wins over intricate human-designed solutions. I used to believe that clever orchestrations and sophisticated rules were the key to building better AI systems. That was a typical sofware dev mentality. You build a system, look for edgecases, cover them and you are good to go. Boy, was I wrong.
Good Taste the Only Real Moat Left
AI makes competent output cheap. That makes taste more valuable, but also more incomplete. The real edge comes from pairing judgment with context, stakes, and the willingness to build.
I love AI, but it still can't design for shit
Without a critical human eye, AI produces slop. The quality bar is yours to maintain.
Why AI Sucks at Front End | Hacker News
Yes ai can’t see, it only understands numbers. So tell it to use image magick to compare the screenshot to the actual mockup, tell it to get less than 5% difference and don’t use more than 20% blur. Thank me later.
Less is more, more or less
In the age of AI, knowing what not to build might be the most important skill of all.
Why it’s getting harder to measure AI performance
The most famous chart in AI might be obsolete soon.
AI makes weak engineers less harmful
Like other kinds of puzzle-solving, software engineering ability is strongly heavy-tailed. The strongest engineers produce way more useful output than the average, and the weakest engineers often are actively net-negative: instead of moving projects along, they create problems that their colleagues have to spend time solving. That’s why many tech companies try to build a small, ludicrously well-paid team instead of a large team of more average engineers, and why so far this seems to be a winning strategy.
Using AI to write better code more slowly
A lot of people seem convinced that the point of AI coding is to write low-quality code as fast as possible. Spew out barely-passable slop, open massive PRs, and merge them unvetted. Ship it! But t…
Why AI Sucks At Front End · April 12, 2026
How can it generate 3D worlds, videos, images and entire web pages, but still suck at front-end?
TurboQuant: Redefining AI efficiency with extreme compression
Amir Zandieh, Research Scientist, and Vahab Mirrokni, VP and Google Fellow, Google Research
The Economics of Using AI to Churn Out Code Are Looking Worse Than Ever
Anthropic updated an estimate for how much developers will spend on its AI coding tool, signaling that the tech is only going to get costlier.
why I am AI sober
on walking away from AI and how you can mirror similar boundaries with big tech.
why I am AI sober
on walking away from AI and how you can mirror similar boundaries with big tech.
The Jagged AI Frontier
The nonintuitive strengths and weaknesses of AI performance relative to human performance, and how it is changing over time.
AI 2027
What will be left for us to work on?
OpenAI and Hugging Face partner to address security incident during model evaluation
Taking more seriously the claim that recent ML models do not "reason", it still is quite odd the particular ways that superhuman game-playin…
General-purpose large language models outperform specialized clinical AI tools on medical benchmarks
StoryScope: Investigating idiosyncrasies in AI fiction