if you're trying to lose weight, you shouldn't carry cookies around in your pockets. And my phone is the bag of cookies in this metaphor.
if you're trying to lose weight, you shouldn't carry cookies around in your pockets. And my phone is the bag of cookies in this metaphor.
OpenAI's inflated valuation, as I understand it
[The only way for labs to capture enough value would be to either invent superintlelligence or have a monopoly.]
[this study claims] that the length of tasks LLMs can complete is doubling every 7 months
[Models are currently commodified, but their labs are not priced as such.]
[If all 163 million working Americans bought a ChatGPT subscription at $20/month, it would provide 40 billion in annual revenue, which is only about 10% of what would justify the current valuation based on more the traditional method using price to earnings ratio.]
AI Is the Market, and the Market Is the Government
The stock market has never been the economy - it’s really a reflection of what the economy dreams it could be in a world where share buybacks translate to meaningful productivity.
as AI swallows up more and more capital, it is both the economy and the stock market - and the government.
As long as portfolios are green, the electorate stays somewhat calm. The administration is effectively borrowing confidence from the AI bubble. Speculation has become governance.
The equity market believes the AI story overrides everything else. The gold market believes something is fundamentally breaking. They’re both reacting to the same underlying reality, but they just have different theories about what happens next.
Both gold and equities are surging because they’re hedging different kinds of collapse. Gold trades on fear of the system. AI trades on faith in the story. That both are rallying tells you something about where we are.
This is what it means to live in the United States of AI. Democracy as an asset class or something. For now, the line keeps going up. But speculation isn’t stability, and the permission government borrows from investors is never really its own.
Look at any modern software application: buttons are verbs, boxes with drop-shadows are nouns, API requests are grammatical structures. We’re not “using” interfaces so much as speaking them. When you pick up a new piece of software you can usually operate it but you lack fluency, you’re still learning the dialect.
Fallacies of distributed computing
- The network is reliable;
- Latency is zero;
- Bandwidth is infinite;
- The network is secure;
- Topology doesn't change;
- There is one administrator;
- Transport cost is zero;
- The network is homogeneous;
There are 9 circles shaping the rocket. The circle count can be further reduced to seven or even four, but this yields shapes that are too simple and not very interesting.
It is easy to simplify things, the trick is to know when to stop.
Rethinking the Future of Bluesky: Challenges and Possibilities of a Decentralized Social Network
The fact that a banned account in one unit can simply join another underlines both the promise and the difficulty of decentralization. What one person sees as resilience, another may see as irresponsibility.
in theory, there is no difference between theory and practice, but in practice there is.
['Social aggregation' features like global search, notifications, feeds, and shared moderation are what] blows the “personal sites” paradigm out of the water. People are social creatures, and we want to congregate in shared spaces. We don’t just want to visit each other’s sites—we want to hang out together, and social apps provide the shared infrastructure.
The web Alice created—who she follows, what she likes, what she has posted—is trapped in a box that’s owned by somebody else. To leave it is to leave it behind.
Those megabytes of JSON you got on your way out are dead data. It’s like a branch torn apart from its tree. It doesn’t belong anywhere. To give a new life to our data, we’d have to collectively export it and then collectively import it into some next agreed-upon social app—a near-impossible feat of coordination. Even then, the network effects are so strong that most people would soon find their way back.
Open social frees up our data like open source freed up our code. Open social ensures that products can get a new life, that people can’t be locked out of what they have created, and that products can be forked and remixed. You don’t need an “everything app” when data from different apps circulates in the open web.
Observations on 6 years of journaling
["Rubber-ducking" is a programming term referring to people solving their own block by explaining it to another person; the lister can be replaced with a rubber duck.]
my journal is my rubber duck.
the current form of social media is bastardised, and not social at all. Instead of improving relationships and fostering connection, they're advertisement-funded content mills which are explicitly designed and continually refined to keep you engaged, lonely, and unhappy. And once TikTok figured out that short-form video with a recommendation engine is digital crack, all other social media platforms quickly sprang into action to copy their secret sauce.
pagination is more humane than infinite-scroll since it gives users a natural breathing point where they can decide whether they want to keep going
How I coined the term 'open source'
I am the originator of the term "open source software" and came up with it while executive director at Foresight Institute. Not a software developer like the rest, I thank Linux programmer Todd Anderson for supporting the term and proposing it to the group.
I said little, but was looking for an opportunity to introduce the proposed term. I felt that it wouldn't work for me to just blurt out, "All you technical people should start using my new term." Most of those attending didn't know me, and for all I knew, they might not even agree that a new term was greatly needed, or even somewhat desirable.
Instead of making an assertion that the community should use this specific new term, he did something less directive—a smart thing to do with this community of strong-willed individuals. He simply used the term in a sentence on another topic—just dropped it into the conversation to see what happened.
Home-Cooked Software and Barefoot Developers
[The term "barefoot developers" is a riff on the Mao government's 1960s "barefoot doctors" initiative to train people from rural villages so they can serve as healthcare providers in their undeserved communities.]
[Barefoot developers] are technically savvy and interested in solving problems for themselves and people around them, but don’t want to become fully-fledged programmers. They still live within the world of end-user-facing applications.
they rely on low and no-code tools. And they do wildly complex things within them, pushing these apps to their limits.
This describes my technical capacities well. Though sometimes I can surmount the "command line wall", I almost always prefer other ways.
[If the thought of him dying pleases you] because you think it will end our present horror, you are the problem.
Have you heard the expression self-defeating prophecy? It's a prediction that prevents what it predicts by predicting it.
CSS can do nesting now!
How We Encourage Self-Improvement at Buffer
Unlimited books
Every teammate receives a free Kindle when they join Buffer and can expense any digital or audiobooks they choose. No approvals needed. No need to tie it directly to work.
Winning, for bloggers, means writing the reference take on a good topic. My favourite example of this is how Byrne Hobart broke out with his piece on the 30-year mortgage. It’s kind of surprising that this kind of post had such influence - it’s wonky, it’s not written for a general audience whatsoever. But it turns out that people think and talk about their mortgages a lot, and like to feel competent when they do. Reading that piece equips them with a kind of legitimacy to speak on the topic.
One lesson hiding in plain sight here is that most of the audience of any successful post does not actually read it. They are told it by someone who did read it. There’s a primary audience who carefully reads the piece and does the cognitive work of “restructuring their consciousness” (see Walter Ong, Orality and Literacy) around good writing. And then there’s a secondary audience, who are re-told the content, either verbally (including group chats, podcasts, Youtube) or in other oral formats like Twitter.
This is why, paradoxically, to reach the widest audience, you write to the narrow audience. Your objective as a writer is to give your primary audience material they’ll want to re-tell. They do the work of translating it to wider audiences in specific contexts; you do the general articulation in rich detail.
My first open source psyop - postmortem
[Information asymmetry is not only about lies, but whether someone can hear the correction or feedback.]
For many people, terms like ActivityPub, Fediverse, bridge, protocol, server, toot, boost, and Webfinger are alienating and confusing. They subtly imply that unless you understand what all these words mean, this might not be the place for you; in the same way crypto terms—blockchain, web3, wallet, keypair, nonce—are a wall of jargon that scream "you don't belong here" to normal people.
To send an email, you don't need to know what SMTP, IMAP, POP, DKIM, SPF, or DMARC are. To browse the web, there's no requirement to understand HTTP, DNS, servers, SSL, TTL, load balancing, or caches. The most significant impact these protocols have is perhaps that users never have to think about them.
Over time, you start repeating yourself, rewriting the same paragraph for different people, reposting the same message in different groups, reframing the same problem with different jargon. And when something finally connects, it often feels like luck. Like you just happened to be visible at the right moment.
This is the system we pretend works: discovery as noise, identity as content, and visibility as a full-time job.
Zero-sum Thinking and the Labor Market
Boomers could trade 4 years of college for 40 years of middle-class security (more or less). Today's 25-year-old faces a negative net-present-value on that same deal. When the fundamental economic bargain breaks down, it flips everything - your discount rate, your risk tolerance, your entire worldview, again, leading to zero-sum beliefs.
Back in 2019, I applied to over 150 jobs when I graduated Western Kentucky University. LinkedIn had their little QuickApply feature, but I wrote so many essays, did many projects, and endless interviews. The entire process made me better, but I was rejected from most of the jobs.
I had a 4.0 GPA, was valedictorian with three majors, worked three jobs for most of my time at university, sold cars, ran D1 Track and Field for a year, and yet, I only got into my first job because the recruiter and some people at the company took a big chance on me (and I only got there because they had a blind resume process where they hid the school. Says a lot about a lot).
The only reason I got my chance - a truly lucky break - was because people bet on me. A computer would have instantly rejected me because I didn’t meet some arbitrary qualification. AI has spurred us right into the depths of what David Brooks calls the rejected generation - endless nos from platforms that are meant to serve as human interfaces (slot machine grabs across dating, investing, and now jobs), but really end up dehumanizing the whole process.
This is the casino economy in action. Again, just like dating apps and meme stock trading, the job market has created the illusion of abundance by replacing meaningful friction with meaningless volume. It has become a dopamonster, to borrow Scott Galloway’s word. More applications, more swipes, more trades - but every extra option raises the noise-to-signal ratio, making the median outcome worse for everyone.