More financial infrastructure coming soon from @UChicagoPress

100%. DOGE successfully achieved exactly what it wanted to achieve

He doesn’t regret it because the entire point of DOGE was to hijack critical infrastructure and deliberately destroy the state’s capacity to deliver public goods and they succeeded at this so the fact that liberals still think this is a dunk is driving me up a fucking wall.

This great article explains how public discipline of utilities should include forcing shareholders to bear the costs of imprudent investments, along with capping returns on equity It also offers a useful history on nuclear plant construction going off the rails in the 1970s

my book 'What Can We Afford,' set to pub early '27, is now available on the Simon & Schuster website ( Amazon etc) for preorder what $ tradeoffs are real? and which are BS or overstated? this is the uncensored 40k mile roadtrip from Wall St to MT to West Texas of what I found:

Interesting but the analysis points (especially given the citation timing) not just to the rise of a methodology but also to the opportunistic search by judges for historical results they like, taking advantage of the prestige of the scholar to divert from this opportunism.

I gotta tell you folks. The Bill Simmons podcasts with Zach Lowe are awful. Zach is so terrified of getting on the wrong side of his sources that he won't "go with" Simmons bits and it's sort of defeats the purpose of Simmons Sunday podcasts.

"can you guarantee a knicks championship in your first term?" "inshallah" promises made, promises kept

What a great story. There is so much latent demand out there for very specific products/services. This demand hasn’t been met because the market is usually relatively small and the overhead cost of providing it through traditional firms is too high to meet it. AI changes this, @aidenjohnsonn_ is a perfect example of how: small team providing useful products to a market that would have otherwise been underserved. My prediction is that we’ll see a ton of this going forward. Markets/people who were underserved/ignored because overhead costs were too high will have their demand met. Small teams/firms, but also teams within larger organizations targeting unmet demand with bespoke products. This is what a welfare improvement looks like.

There’s a big, under-appreciated reason why people may have very different experiences and opinions about using AI for work — are they using it for tasks they’re already an expert at, or tasks they can’t do themselves? The former leads to a *growth cycle* and the latter leads to a *dependence spiral*. When I use AI to do something I’m an expert at, like coding, I treat it as a tool. I can build quickly, maintaining an understanding of the code, knowing that if necessary, I can fix the code myself. It feels empowering. It frees up my time to think about the complex, judgment-oriented parts of software engineering that I can’t or won’t delegate to AI. That means my own skills improve rapidly, and I get to climb the ladder of complexity and develop higher-level skills, much more so than when I write the code myself. I feel in control. I can lock in and achieve a flow state — when AI is working, I’m reviewing, building understanding, and planning the next steps. I never get the feeling that the tool is about to replace me. This is the growth cycle. (Of course, the growth cycle is not automatic. I still need to exercise agency to use AI responsibly. But it’s the same challenge with any productivity-enhancing technology, and those who’ve navigated such transitions before are well-equipped to navigate it with AI as well.) On the other hand, if I use it for tasks I don’t understand and haven’t learned to perform myself, I have no choice but to treat it as a superintelligence. If something breaks, the best I can do is ask AI to fix it and hope for the best. I generally can’t evaluate the quality of the output myself. The only way to find out if it's any good is if and when the work is ultimately reviewed by an actual expert. The experience is confusing, unsettling and disempowering. And forget about flow state. By over-relying on AI, I risk losing whatever skill I had at the task in the first place, even if it boosts productivity in the short term. This is the dependence spiral. It’s no wonder that entry-level workers and students preparing to enter the workforce find themselves in a bind. To compete with the AI-enabled productivity of more seasoned workers, they must adopt AI themselves, but doing so risks the dependence spiral. I have some thoughts on solutions that I will share in later posts, but I think having a clear diagnosis of the problem is a useful first step.

Modernity was in no small part about learning to live within and trust societies of strangers. Here in post-modernity we are finding out how fragile that achievement really was

ESPN currently broadcasting collegiate track, not Inside the NBA cc: @bryancurtis

David has taught me much about how lousy the word “technology” is and why we should avoid it, which I try to do whenever I can. “AI” is so, so much worse, as many have noted.

Very important point: SoftBank was pledging *all* of its OpenAI stock (worth $60bn on paper) to get a $6 billion margin loan. Banks turned it down due to concerns about the value of OpenAI stock. Banks clearly do not think OpenAI is worth $852 billion. tradingkey.com/analysis/stoc…

A strategy targeting those driving gun violence in Baltimore's hardest-hit district cut shootings and homicides by a third in 18 months, with no rise in overall arrests, from Max Kapustin, @aaronchalfin, Jeremy Biddle, Brian A. Wade, Natasha Khade, Cristina Layana, Ben Struhl, and Anthony A. Braga nber.org/papers/w35292

IPOs being advertised in grocery apps 1929 on steroids

It is always remarkable to me how historians spend so much blood, sweat, and tears, defending very recent disciplinary & institutional configurations, when our entire job is to understand that in fact these very things have never been stable and have constantly changed