Joseph Bou-Younes's Website

Tag: ai

  • Figuring out what to build is the hard part

    “For a while, I must admit, it looked as if software developer roles like mine were done for. How could we fight against tireless robots? But our industry is slowly realizing that making truly cutting-edge software still requires humans to think and work together, to maximize their skill sets and to practice their respective crafts. A.I. can write very good software, but it also makes it easy to do someone else’s job badly, which is part of why all those projects fail. Now that everyone can code, it’s become clearer why many shouldn’t.”

    -AI Slopware is everywhere now. Nobody is using it (NY Times)

  • American Oligarchs or the Chinese Communist Party

    In China, the pecking order is clearer. A founder who flies too high is grounded; a platform that forces monopolizing behavior and mistreats its workers gets punished; when the government rolls out “common prosperity,” tech companies rush to pledge in public.

    AI doomerism, and opposition to data centres, are usually manifestations of the fear of American oligarchy.

    In China, The Party is very much in charge, not the oligarchs (Bloomberg.com Gift Link via Techmeme).

  • It’s your work product

    I don’t care if you wrote something with Claude, ChatGPT or Ouija Board: it’s your work product. Comport yourself accordingly, and don’t waste my time. There are no lossless transformations of natural-language text.

  • This absolutely sends me

    https://gruhn.me/blog/2026-08-03/

    Too often I ask a question in Slack or leave feedback under a merge/pull request or argue with friends in a WhatsApp group and get back:

    > Claude said: [giant response verbatim]

    Please don’t do this. I mean, I’ve done this. But I’ve been on the receiving end too many times now. This is not adding value. I can talk to Claude myself. It’s going to be faster and I get to control the context. I don’t need a meat proxy in between.

    Honestly, if you do this I will 100% drag you. It might not be right away, but it will happen. Probably when you least expect it.

  • Understanding the amount of bullshit work

    AI is going to help humanity by revealing just much human time is spent on bullshit work.

    Consulting giant Accenture is trying to figure out how to stop non-technical workers from blowing through companies’ AI token budget on trivial tasks like converting PDFs to presentation slides, according to leaked audio obtained by 404 Media. Across the industry Accenture is seeing “soaring token spend,” according to the audio.

    – The Tokenpocalypse Is Here: Companies Are Scrambling To Stop Spending So Much on AI

  • Local journalism

    South Shore news: AI-generated newsletter has paying audience (Boston Globe)

    This feels like the future. AI agents, directed by assignment editors, gather local intelligence and context. Other agents draft and edit stories. Humans handle quality control and accountability. Meanwhile, separate software tracks traffic and prominence, feeding signals back to adjust agent behavior — optimizing for the business goals or cultural impact that publication leadership is after.

  • The new skill: task imagination

    With models that can run for days, NLW argues we’ll all have to up-level ambition — and become token-efficiency optimizers who match models to use cases. Nate B. Jones’s framing: most of us have nothing that’s ever taken even an hour on AI, so the scarce skill is imagining tasks worth handing to a model that works for days.

    — The AI Daily Brief · https://aidailybrief.ai/e/2026-06-10#task-imagination

  • Jevon’s Paradox and AI

    Jevons paradox is coming to knowledge work. By making it far cheaper to take on any type of task that we can possibly imagine, we’re ultimately going to be doing far more. The vast majority of AI tokens in the future will be used on things we don’t even do today as workers: they will be used on the software projects that wouldn’t have been started, the contracts that wouldn’t have been reviewed, the medical research that wouldn’t have been discovered, and the marketing campaign that wouldn’t have been launched otherwise.

    — Aaron Levie, Jevon’s Paradox for Knowledge Work

    Via Simon Willison’s Webblog.

  • The math behind an LLM

    The best, shortest and sweetest explanation of how an LLM works.

  • Be YouTube, not Qwest

    Today, no amount of model training is too much. No price for that training is too high. The builders bet is that inference will be orders of magnitude cheaper in 5 years. Build for that. Be Netflix or YouTube, not Qwest.

    This year, American tech companies will spend $300 billion to $400 billion on artificial intelligence, which is in nominal dollars more than any group of companies have ever spent to do anything. Notably, these companies are not remotely close to earning $400 billion on artificial intelligence.

    That’s why you’re starting to hear some people wonder whether the AI build-out is turning into the mother of all economic bubbles.

    The prospect of an AI bubble should scare us. Roughly half of last quarter’s GDP growth came from infrastructure spending on AI, and more than half of stock market appreciation in the last few years has come from companies associated with AI. If the AI spending project blows up in the next few years, as our next guest says it might, the implications for technology, the economy, and politics would be immense.

    – This Is How the AI Bubble Could Burst – Plain English with Derek Thompson