I recently spent some time with former colleagues from academia. All of them brilliant, peak human capital. Almost all of them fundamentally unable to plug into the economy, inoculated against productivity by a youth spent experimenting in laboratories instead of building wealth for society. Dealing with real people in the real world. 90% of them have left academia in the last 10-15 years, and 90% of those are functionally unemployed. Grad school does a lousy job of training scientists to be professors (since most of them don't get the good postdoc or tenure track position) and an even worse job of preparing people for real life. We complain that our societal infrastructure is collapsing, our state capacity is low, our incumbent industries are faltering. Where are the next generation of leaders that can push us forward? A huge fraction of them were conveyor-belted into academia by schooling systems that have no mechanism to channel ambition and 99+%ile competence, and our universities are mostly hedge funds with glorified psych wards/academic departments on the side, running an insane pyramid scheme that exists only to prove, over and over again, the Shirky Principle: Institutions will try to preserve the problem to which they are the solution. We literally poured trillions of dollars into state-funded research and effectively neutered our elite civilian technical leadership development programs. I recently asked a few academic friends if they were finding AI useful in accelerating their programs of research. You know, to solve the Big Problem their entire field exists to solve? Some were. But most were complaining about how it created pedagogical issues, explaining how their department decided to ban the use of AI, or how it took 18 months to approve an enterprise account, or how they tried Gemini 2 on a puzzle a year ago and it wasn't very helpful, or repeating nonsense about datacenters and water consumption, or supposed IP theft by model companies, as though that has any bearing on their ability to, eg, accelerate a cure for cancer. Elon sometimes calls AI a supersonic tsunami - a huge wave you don't see coming. I see it coming. But even the people who you'd think have been waiting for this their entire careers are steadfastly looking in the other direction.

So many people are going to get one-shotted by super persuasive super intelligences and I might be one of them

Filling the massive AI drug discovery data gap nature.com/articles/d41573-0… Charlotte Deane, co-leader of the OpenBind initiative, discusses the need for more protein–small molecule binding data

Do a kickflip!

try pstack! it’s my personal set of skills for rigorous and autonomous engineering with agents. it’s updated frequently as I continue to tune and simplify them 10 second tutorial: 1. run /setup-pstack and choose your budget 2. add /poteto-mode in front of any prompt you want done rigorously 3. ask /poteto-help whenever you’re unsure what pstack skills to use 4. that’s it! Grok Bot: x.ai/bot/plugin/9717366 Cursor: cursor.com/marketplace/curso… Source: github.com/cursor/plugins/tr…

Yesterday, the FDA approved the $IBRX drug Anktiva to treat the more common "papillary" type of non-muscle invasive bladder cancer. The approval was based on a single arm study, reversing the agency's prior regulatory standard. A victory for ImmunityBio and @DrPatrick ? Maybe half. The new FDA standard for papillary NMIBC will now be broadly applied. Did anyone listen to the $JNJ earnings call on Tuesday? Here's R&D chief John Reed, speaking about its bladder cancer drug, Inlexzo: "The FDA has invited us to submit for an expansion of our label into that population." Inlexzo sales in Q3 were "north of $90 million," J&J said.

Compute scarcity, in one chart Old GPUs are turning into appreciating assets

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!

Timing is everything

First encounter - turned out to be a family reunion

People haven’t yet realized it yet But driving is, in fact, “solved”

We’ve continued to receive many very sweet notes from parent, grandparents, aunts, uncles and even some great grandparents 🥹🥰🇺🇸

This is a perfect example of DEI in the wild. Women gets Harvard PhD, Princeton postdoc, NY Fed job. Impeccable credentials - on paper. Writes post demonstrating that she doesn't under the basics of causality & statistics. There's also a very strong urban class component 1/

Google Deepmind (FNV3) CRUSHED the forecast for #Isaias up to 11 days in advance. It picked up some appreciable signal on September 23, locked in on the exact landfall location4 days before it happened, and nailed the peak intensity consistently 3 days before it happened. A new age of forecasting is upon us. First video: Track density using 1000 member ensemble Second Video: Individual tracks and mean using 50 member ensemble

Introducing Anatomy Describe a machine in one line. Claude brings it to life. - Interactive isometric wireframes you can rotate, inspect and explore - WebGL shaders for fire, water, plasma and more - Real 3D motion, with individual parts that rotate and move Install it as an agent skill. Fully open source.

Besides very nice interactive visuals *in* Codex, you can also have Codex send your molecules over to a VR headset like Meta's Quest or Apple's Vision Pro to view and interact with them in 3D. It feels very 'Jarvis-like' to talk to Codex in voice mode and see it update the view, pull up structures, and perform analyses in near real time. Here's an example of Codex sending structures to a Quest 2 using Stereofold, an open-source plugin I put together. It builds on the Mol* molecular viewer and its WebXR support, adding tools and skills that let Codex share structures with the headset and keep editing them while you wear it. I tested this on a Quest 2 headset over Wi-Fi, but it should also work for other headsets like Apple's Vision Pro.

The Trump Administration is working across the government — from the White House to HHS to HUD — to address the homelessness epidemic by putting Treatment First. Tom Wolf, an American with lived experience, shares his message to vulnerable Americans who may be struggling on the streets:

LADIES THERE IS NO SECRET WHEN THE BOYS ARE INTO BORING SHIT AND STICKING WITH IT MUCH LONGER THAN YOU THINK IS REASONABLE THERE IS NO SECRET THEY ARE NOT FINDING ANYTHING SPECIAL IN THE TWENTIETH ITERATION OF WHATEVER BULLSHIT THEY'RE ON ABOUT. IT'S THE SAME AS THE PREVIOUS NINETEEN TIMES. AND THEY'RE HAPPY DOING IT. IF YOU'RE NOT IT'S FINE NO NEED FOR FOMO THEY'RE REALLY REALLY JUST DOING THE SAME THING AGAIN WAR. PROGRAMMING. BOATS. THEY WILL DO THE SAME THING THEY WERE JUST DOING, AGAIN, LONG LONG AFTER I WOULD HAVE SNAPPED AND KILLED THAT JACKASS THEY'RE ALL LISTENING TO FOR SOME REASON. FOR THE FIRST TIME IN MY LIFE I AM NOT ENVIOUS OF MEN. I WOULD KILL A BITCH AND BE DONE. THAT MOVIE WOULD HAVE BEEN 45 MINUTES LONG IF I'D BEEN ON THE BOAT. I DO NOT WANT THE ENDOCRINOLOGICAL MAKEUP THAT WOULD MAKE ME INCLINED TO PUT UP WITH RUSSELL CROWE'S BULLSHIT ONE SECOND LONGER THAN ABSOLUTELY NECESSARY AND DON'T EVEN GET ME STARTED ON NAPOLEON "WE HAVE TO GO TO WAR BC NAPOLEON MADE HIMSELF KING OF EUROPE" WELL WHY DID HE GO DO A RETARDED THING LIKE THAT. WHAT COULD HE POSSIBLY GAIN. NOT THAT I WANT WOMEN IN CHARGE. MY GOD. IT'S NOT THAT WE AREN'T CAPABLE IT'S JUST THAT WE HAVE A TENDENCY TO GET A LITTLE CREEPY BEING ONE HALF OF A MARRIED COUPLE AND HAVING GIVEN BIRTH TO SONS AND A DAUGHTER, I FEEL I AM CLOSER TO A NEUTRAL GENDER EXPERIENCE THAN I EVER HAVE BEEN BEFORE AND YOU KNOW WHAT. BOTH SIDES ARE RETARDED. THAT'S IT THATS THE SECRET IF YOU LET MEN DO THEIR THING TOO LONG YOU GET MONKEYPOX AND NAPOLEON. YOU LET WOMEN GO TOO LONG SOLO AND YOU GET THE FUCKING. WHAT WAS IT. SECULAR HIJABI COVID FRIENDLY BAR. PSYCHOLOGICAL TORTURE. AND NO SEX. IN THE LONG RUN. I'M TOLD.

Fate loves irony. Si is silicon on the periodic table.