Longreads + Open Thread

Longreads

• Erik Hoel on early reading, specifically the question of whether or not children under six are neurologically capable of reading. He notes that back before we had education experts who could cite other education experts' vague understandings of half-century-old neurology studies, we had no idea insufficient myelination would prevent kids from reading, so late 18th century Americans bought reading primers explicitly intended to teach two-year-olds to read. But one note on this is that there's a selection effect: the people doing this were Puritans, whose religious practices are also pretty oriented towards carefully parsing complex texts. That probably leads to differences in who goes Puritan and who doesn't, so it's a cohort that's probably full of early readers as well.
• Adam Gopnik reviews two books that question the concept of "the renaissance" as a distinct historical period. Some of it seems a little shaky, like the claim that "Renaissance cities, far from being principalities of prosperity and enlightened rule, were desperately poor, violent, and anarchic." (This is Gopnik's paraphrase of Palmer, and while these cities were violent and sometimes anarchic, Bruges and Florence were two of the richest cities on earth. And it would be very unusual for relatively poor cities to have a thriving banking industry.) It is sometimes helpful to try to blur the boundaries of a historical period, like treating the First and Second World Wars as one extended conflict, or treating the big milestones in US history as the discovery of oil, the development of the Model T, the oil shock, and the rise of fracking. You can get some mileage out of this, but it's also useful to have these somewhat arbitrary cutoffs, where we say Rome fell in 476 instead of 1453 or 1806 or whatever. Maybe if more of our knowledge acquisition starts with prompting LLMs rather than scanning titles on bookshelves, this will be less of a concern, though.
• Dan Wang reflects on writing his book (which I very much look forward to reading—we're getting his wonderful annual letters series back, with interest!) It's also a great look at writing, and at the craft of research: "I’ve learned to detect when writers attempt the difficult and when they succumb to laziness. There are parts of every book where writers cover a topic they have little interest in (out of some obligation), at which point I try to figure out how many pages I need to flip before getting to the parts they care about."
• Alexey Guzey on learning to believe in AGI again. Many thoughts on AI as a concept, product, and industry. One fun point is that, while alignment is a thorny problem, the capital-intensity of the industry has led to a sort of fuzzy alignment where the researchers who can implement their ideas are the ones whose ideas lead to products people will actually pay for. This isn't what people who worried about existential risk thought the dynamic would be, though it's not clear if the current setup is better or worse for their concerns.
• Andrew Batson on attending a conference about India as a China expert. As it turns out, there's a lot of China Envy in these circles, which makes sense; Japan Envy arguably brought more people out of poverty than any other emotion, so there's some meta-pattern-matching at work in this kind of pattern-matching. This piece ends up being a sort of postmodern one, where someone with a strong sense of what China's economy is like looks at a country that's trying to be more like what China seems to be like—India has a target for growing manufacturing's share of GDP, but as it turns out China has never set explicit targets at that high a level, though they set plenty of granular ones that have that as an output.
• In this week's Capital Gains, we consider why summer is crash season: less news, more uncertainty, but mostly more people on vacation. (Note that yesterday's VIX spike is a little high, but not crazy, for a 1.5% drop in the S&P. August is a good time to be nervous!).
• I was on the Yet Another Value Blog podcast with Andrew Walker to talk about Softwar and Larry Ellison. Highlights include: would we have shorted Oracle at the time that the book came out? Isn't it kind of obnoxious to keep firing people right before their options vest? And why aren't there more conspiracy theories about Oracle being an intelligence front?
• On the Read Haus Diff chatbot this week, one of the interesting interactions one user shared was asking about the Vision Pro. The Diff hasn't written a ton about it, but it's probably a good illustration of why the iPhone worked so well: there was pent-up demand to create native applications for the phone form-factor, and you could approximate what those would look like by just taking the desktop app, reducing the pixels, making the buttons bigger to compensate, and then iterating a little bit until it didn't look actively hideous. But the cost of building and iteration on a VR headset is much higher, and the question of what an app should look like in three dimensions is harder to ask.

Open Thread

• Drop in any links or comments of interest to Diff readers.
• Generative AI is an interesting technology in that some of the applications are discovered by users, who don't actually need a different product to have a different experience. You can use them for tutoring, role-playing, etc. What are some of the varieties of LLM-based entertainment that will end up being standalone products in the future?

Diff Jobs

Companies in the Diff network are actively looking for talent. See a sampling of current open roles below:

• Thiel fellow founder (series A) building full-stack software, hardware, and chemistry to end water scarcity, is looking for an ambitious robotics engineer to help build sophisticated drone nest systems that can deploy, maintain, and coordinate fleets of UAVs for precision atmospheric intervention. If you spend nights and weekends in the shop tinkering on hardware projects, have built and deployed robotic automation systems, and understand ROS (Robot Operating System) well, please reach out. 
• A company that was using ML/AI to improve software development/systems engineering before it was cool—and is now inflecting fast—is looking for a product marketing manager to articulate their value proposition and drive developer adoption. If you started your career in backend engineering or technical product management, but have since transitioned (or want to transition) into a product marketing seat, this is for you. (Washington DC area)
• A leading AI transformation & PE investment firm (think private equity meets Palantir) that’s been focused on investing in and transforming businesses with AI long before ChatGPT (100+ successful portfolio company AI transformations since 2019) is hiring Associates, VPs, and Principals to lead AI transformations at portfolio companies starting from investment underwriting through AI deployment. If you’re a generalist with a technical degree (e.g., CS/EE/Engineering/Math) or comparable experience and deal/client-facing experience in top-tier consulting, product management, PE, IB, etc. this is for you. (Remote)
• Ex-Citadel/D.E. Shaw team building AI-native infrastructure to turn lots of insurance data—structured and unstructured—into decision-grade plumbing that helps casualty risk and insurance liabilities move is looking for a data scientist with classical and generative/agentic ML experience. You will develop, refine, and productionize the company’s core models. (NYC, Boston)
• Well funded, Ex-Stripe founders are building the agentic back-office automation platform that turns business processes into self-directed, self-improving workflows which know when to ask humans for input. They are initially focused on making ERP workflows (invoice management, accounting, financial close, etc.) in the enterprise more accurate/complete and are looking for FDEs and Platform Engineers. If you enjoy working with the C-suite at some of the largest enterprises to drive operational efficiency with AI and have 3+ YOE as a SWE, this is for you. (Remote)
• A Series B startup building regulatory AI agents to help automate compliance for companies in highly regulated industries is looking for legal engineers with financial regulatory experience (SEC, FINRA marketing review, Reg Z, UDAAP). JD required; top law firm experience preferred. (NYC)

Even if you don't see an exact match for your skills and interests right now, we're happy to talk early so we can let you know if a good opportunity comes up.

If you’re at a company that's looking for talent, we should talk! Diff Jobs works with companies across fintech, hard tech, consumer software, enterprise software, and other areas—any company where finding unusually effective people is a top priority.