Kevin W. Sexton, MD

Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

Today we released our new AI Fluency Rubric. We use it for every hire, focusing on what they’ve actually built. Last May we open-sourced V1. Hundreds of companies used it to screen candidates and develop teams. It worked. But the floor moved fast. An updated look at the 3 levels of AI fluency at @Zapier: 1. Capable: "I use AI to operate at a meaningfully higher level." 2. Adoptive: "I orchestrate AI and build systems that elevate how I work." 3. Transformative: "I re-engineer how work happens." We evaluate theses across 4 dimensions: Mindset, Strategy, Building, and Accountability. We're sharing V2 publicly for the same reason we shared V1: every company needs a framework for this, and most don't have one yet. Don’t see your role? See all departments / learn more here: zpr.io/xQq5PHMDChrL

Same! There is a hidden gift in not matching -> prelim year -> repeat intern year… I just didn’t realize it that way until much, much later. #Match2025

@cardiojaydoc02 On average, I work less than residency. What attending-hood doesn’t have is any kind of protection. Someone’s out? You have to cover. Something comes up? You have to stay sometimes. The attendings have to kick in, as there is no Program Director to fix your problem.

Yesterday Mark Cuban reposted my work, DM'd me, and told me to keep telling my story. So here it is. I'm a Master Electrician. IBEW Local 369. 15 years pulling wire in Kentucky. Zero coding background. I didn't go to Stanford. I went to trade school. Every week I'd show up to a home where someone just bought a Tesla or a Rivian. And every time, someone had already told them they needed a $3,000-$5,000 panel upgrade to install a charger. 70% of the time? They didn't need it. The math is in the NEC — Section 220.82. Load calculations. But nobody was doing them for homeowners. Electricians upsell. Dealers don't know. And the homeowner just pays. I got angry enough to build something about it. I found @claudeai. No coding experience. I just started talking to it like I'd explain a job to an apprentice. "Here's how load calcs work. Here's the NEC code. Now help me build a tool that does this." 6 months later — @ChargeRight is live. Real software. Stripe payments. PDF reports. NEC 220.82 calculations automated. $12.99 instead of a $500 truck roll. I'm still pulling wire. I still take service calls. I wake up at 5:05 AM for work. But something shifted. Yesterday @vivilinsv published my story as Claude Builder Spotlight #1. Mark Cuban saw it. The Claude community showed up. And for the first time, I felt like this thing I built in my kitchen might actually matter. I'm not a tech founder. I'm a dad who wants to coach little league and be home for dinner. I just happened to build something that helps people. If you're in the trades and thinking about using AI — do it. The barrier isn't technical skill. It's believing you're allowed to try. EVchargeright.com

Dear Residents, Thank you for waking early and working hard all day and sometimes all night caring for patients while also learning, teaching, and researching with passion and humanity. Our future is bright because of you! Sincerely yours, A grateful attending

How AI can transform precision-education for physicians "When data from many users are aggregated, these tools can generate performance ranges, revealing learning curves that could predict trajectories leading to the best possible performance for individual trainees." @sanjayvdesai @KimLomisMD @khanacademy nejm.org/doi/full/10.10…

Cardiologist wins 3rd place at Anthropic's hackathon. Out of 13,000 applications. Built in 7 days by Michał Nedoszytko MD. Coded day and night - in the hospital, in the cloud, while flying from Brussels to San Francisco. A few years ago, it would have been impossible for a doctor to build this alone in just a couple of days. AI changed that. The project is called postvisit.ai. It is an AI agentic care platform for patients. Including reverse AI scribe it is a companion that guides the patient from the moment they leave the doctor's office. Powered by the massive context window of Opus 4.6, it allows patients to explore their full medical history, connected devices, Evidence Based resources and external data sources — all in one place. Today, the barrier to entry has vanished; even a practicing physician can build an application from scratch.

My biggest takeaways from @bcherny: 1. Coding is now “solved” for most use cases. Boris hasn’t written a single line of code by hand since November, with 100% of his work now authored by Claude Code. At the same time, he remains one of the most productive engineers at Anthropic, shipping 10 to 30 pull requests daily while leading the team. 2. Anthropic has seen a 200% increase in engineer productivity since adopting Claude Code. As Boris notes, “Back at Meta, with hundreds of engineers working on productivity, we’d see gains of a few percentage points in a year. Now we’re seeing hundreds of percentage points.” 3. AI is moving beyond writing code to generating ideas. “Claude is starting to come up with ideas. It’s looking through feedback, bug reports, and telemetry, then suggesting features to ship.” 4. The next roles to be transformed are those adjacent to engineering. Product managers, designers, and data scientists will see similar transformations as agentic AI expands beyond coding. “Any kind of job where you use computer tools will be next.” 5. Build for the model six months from now, not today. One of Boris’s key principles is to design products for future AI capabilities, not current ones. “It’s going to be uncomfortable because your product-market fit won’t be very good for the first six months. But when that model comes out, you’ll hit the ground running.” 6. Watch for “latent demand.” Claude Code was built by observing what people were already trying to do, and then making it easier. Cowork emerged when they noticed people using Claude Code for non-coding tasks like analyzing MRIs or recovering wedding photos from corrupted drives. 7. Don’t optimize for token cost. Boris advises companies to give engineers unlimited tokens during experimentation phases. “At small scale, the token cost is still relatively low compared to their salary. If an idea works and scales, that’s when you optimize it.” 8. Underfund headcount on purpose. When Boris puts one engineer on a project, they’re forced to let AI do more of the work. Constraint drives creative use of AI tooling, not just faster typing. 9. The most successful people in the future will be generalists. “Try to be a generalist more than you have in the past. Some of the most effective engineers cross over disciplines. The people who will be rewarded most won’t just be AI-native—they’ll be curious generalists who can think about the broader problem they’re solving.” 10. Always use the most capable model, not the cheapest. A less intelligent model often burns more tokens correcting mistakes than a smarter one spends getting it right the first time. Boris runs maximum effort on Opus 4.6 for everything. Here's the full conversation: youtube.com/watch?v=We7BZV…

@bcherny @readwise save thread

I'm Boris and I created Claude Code. Lots of people have asked how I use Claude Code, so I wanted to show off my setup a bit. My setup might be surprisingly vanilla! Claude Code works great out of the box, so I personally don't customize it much. There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it, and hack it however you like. Each person on the Claude Code team uses it very differently. So, here goes.

What is the value of LLMs for clinical & operational tasks? While their predictive abilities may be slightly better than other models, their flexibility across diverse data models & tasks could be a bigger advantage. Excited to have collaborated w @_TylerLoftus on this comment.

@CoachGeoffReed @readwise save thread

Knees Over Toes-Style Workout in a Regular Gym How to build a stronger posterior chain with no special equipment:

@trq212 @Readwiseio save thread

Claude Code is All You Need When I first joined Anthropic I was surprised to learn that lots of the team used Claude Code as a general agent, not just for code. I’ve since become a convert! I use Claude Code to help me with almost all the work I do now, here’s how:

A teacher in Thailand invites her students to pick their greeting. Can we do this in every classroom in every country?

@johnrushx @Readwiseio save thread

I've tried all (46 😵‍💫) AI Coding Agents & IDEs [Factory, Cursor, Heyboss, Windsurf, Emergent, Wrapifai, Copilot, Lovable, Bolt, v0, Replit, MarsX, Canva, Devin, Github Spark, IDX, Stitch & more] The most complete list ever made (with demos & notes):

Congratulations @Nate_Verhagen! Well done. And you have a super mentor in @anaikothari!

First up from DoC-IT at #AMIA2025: @RamanKhannaSF joins @EllenKimMD, @kev_ai, @jdhron & Edna Shenvi to tackle a critical topic—how to increase diversity in clinical informatics. It will be an illuminating workshop to kick off the week! 🔗Details: docit.ucsf.edu/events/amia-cl…

@Codie_Sanchez @Readwiseio save thread

This is Bill Perkins. He's worth 100s of millions, a hedge fund manager, poker player, asymmetric thinker... And my smartest mentor. Steal his 7 principles on how the rich think differently:

@craigbrockie @Readwiseio save thread

She’s reinventing the science of aging. Meet Julie Clark: the 56-year-old whose biological age clocks in at 36. She’s outpacing Bryan Johnson, the $2M-a-year biohacker, on a mere $4/day. Here's her simple anti-aging routine for peak health and lasting longevity: 🧵

@testomaxing @readwise save thread

Six years in the gym taught me some brutal truths about fitness: 1. Eat all the damn fruits you want.- It’s almost impossible to overeat it.