To think like a hacker, you must adopt a specific mindset that focuses on identifying and exploiting security flaws within a system. This thought process
The trap of tech that’s great in the small but not in the large
There are software technologies that work really well in-the-small, but they don’t scale up well. The challenge here is that the problem size grows incrementally, and migrating off of them re…
Age verification: what's the harm? | Girl on the Net explains
Age verification has hit the UK, people need to upload ID to see 'adult' content. What's the harm in laws like this, if they protect children? Let's see.
To protect the digital foundation of essential government services, governments should invest in Open Source as public infrastructure and shift from consumption to contribution.
Without taking a position on the whole issue:
Married to a professor of veterinary medicine, it seems to me comparing the results of AI coding to the results of evolution ought to make you nervous. https://wiki.oddly-influenced.dev/view/welcome-visitors/view/your-body-is-a-gross-kludge
The lesson of medicine is that bodies are not designed for understandability or non-planned-for maintenance. You're essentially conceding that humans working on AI code will be as expensive and failure-prone as physicians working on bodies.
It's worth considering how bad humans are at predicting nonlinear effects (Dörner's /The Logic of Failure/ is good at that, https://www.hachettebookgroup.com/titles/dietrich-dorner/the-logic-of-failure/9780201479485/?lens=basic-books) That's the root of the oft-quoted Hemingway bit:
“How did you go bankrupt?” Bill asked.
“Two ways,” Mike said. “Gradually and then suddenly.”
That's an effect of how profoundly bad we are at understanding exponential growth.
If it were my money at stake, I'd want a some assurance that if AI hits a wall, I won't be left with the equivalent of a nasty autoimmune disease. That is: what are the risks? how will you monitor them? what's your disaster recovery plan?
The problem with a ZIRP is that those questions are b-o-r-i-n-g and you can't compete with those who skip them. You're out of business before they crash. ("The market can remain irrational longer than you can remain solvent.")
Similarly, there's a collective action problem. Our society is structured such that when the optimists' predictions go wrong, they don't pay for their mistakes – rather society as a whole does. See housing derivatives in 2008, the Asian financial crisis of the late '90s, etc. ZIRP makes it cheaper to be an optimist, but someone else pays the bill for failure (Silicon Valley Bank, Savings and Loan crisis)
It's weird to see ZIRP touted as a model, given the incredible overspending that took place, which had to be clawed back once ZIRP went away. (Most notably in tech layoffs, but I'm more concerned about all the small companies that were crushed because of financials, not because of the merit of their products.)
Please extend your analogy to the end of the AI ZIRP environment. Or will line go up forever?
The best Stratechery content from the week of August 4, 2025 including what Nokia can teach us about the AI era, what the NFL wants from ESPN, and how Visa conquered debit cards.
Ari Paparo’s “Yield”: How Google (And AdTech) Went Bad
Ever wonder why online advertising is so convoluted? A new book by an industry insider helps explain why—and how Google put its giant hand on the scale.