David Sinclair shares findings from a Journal of Physiology paper showing muscle fibre atrophy during aging and disuse is mainly associated with fewer myofibrils rather than smaller myofibrils. He quotes David Sabatini calling the paper important.
The paper shows that muscle fibre atrophy during both aging and disuse is mainly associated with a lower number of myofibrils, rather than a smaller size of the myofibrils 💪
Jeff Dean says he is proud to have collaborated on several projects, quoting a post in which Deedy Das shares a two-minute video about Google's history that was generated by Claude.
International Cyber Digest reports that Jensen Huang dismissed Anthropic's Tom Brown as a bean counter over a spreadsheet showing Google TPUs beating Nvidia chips on cost, and that Huang threatened to skip a 2022 dinner with Dario Amodei.
Jensen Huang called Anthropic compute chief Tom Brown a "bean counter" and threatened to skip his first dinner with Dario Amodei in May 2022 after Brown showed him a spreadsheet arguing Google's TPUs beat Nvidia's chips dollar for dollar.
At the dinner, Huang kept repeating that Nvidia would build the world's biggest data centre, and Amodei muttered that his behaviour was "kind of Trump-like."
Expose H1B Fraud posts a video claiming Rochester General Hospital in New York hired 82 resident doctors, with 80 on H-1B or J-1 visas and only two Americans, alleging USMLE cheating among some source countries.
Akshay Kothari recommends a presentation by Pat and says a slide on the gap between AI capabilities and adoption excites him about the next decade. He also shares a Boston College Investment Committee reflection on AI, recorded by Grady Burnett, which is linked as a loom video.
Worth watching this whole presentation by Pat. This particular slide is why I'm so excited about the next decade. I haven't experienced a bigger gap between capabilities and adoption in my short career.
The @BostonCollege Investment Committee (an LP and my beloved alma mater) asked for a few thoughts on what's happening in AI. I recorded a test run yesterday morning and then shared it with my partners, who encouraged me to share it more broadly... so here you go!
This is not a sales pitch, it's just a reflection on what we're seeing. And it wasn't intended to be shared, so please pardon the rough edges.
Dr. Brent A. Williams argues that BronxCare, a high-volume urban hospital, struggles to attract U.S. graduates for the same reasons rural programs do. He responds to a post noting that 43 of 44 recent BronxCare pediatrics residents attended foreign medical schools.
BronxCare is a high-volume, high-poverty, urban hospital that serves a complex pediatric population.
Many U.S. graduates simply rank other more desirable New York or out-of-state programs higher. Rural programs face similar location and lifestyle drawbacks.
DJ Sampath says Meta's Muse agent gets its sandboxing largely right, citing a per-user virtual machine, credential isolation, a second approval agent named Sentinel, and a full audit trail. He notes Cisco has provisioned microVMs for over 80,000 employees and plans to scale the approach to users.
Spent the weekend with Meta's @Muse, and they got a lot right.
- Every user gets their own VM. - The agent never sees a password. - A 2nd agent (Sentinel) has to approve anything that leaves the box. - Every action is in the audit trail.
That's the most careful consumer agent sandbox I've used.
I don't know if folks realize but a VM for every user, at Meta scale, is kinda huge! It's never been done before where we simply provision a linux microVM for every single consumer.
We recently did this within @Cisco for over 80,000 of our employees. And now within our products as well as we start to scale it out to every single one of our users.
Josh Elman observes that software engineers have historically combined strategy and hands-on building unlike other engineering fields, and says that combination has intensified now. He endorses a speech by Scott Stevenson urging engineers to keep happy memories, stay grounded in reality, and stay excited about the future.
Software Engineering used to be such a different type of engineering from other fields - where you did both the strategy and the manual chiseling. (mechanical engineers don’t do the rivets)
Now Software Engineering is a whole new level of making. Great speech below
Ahmed Khaleel announces a native macOS disk usage app built with Rust and Swift that is 4.7 MB, scans 278,000 files in 0.7 seconds, and scans an entire 4-million-file Mac in about 13 seconds. He claims it is 1.4 times faster than disktree while using half the memory.
David announces jevgrep, a command-line research agent built on TypeSafe's Jev that finds relevant code by describing what it does. He claims it cuts coding agent costs by 40% on SWE-bench and links to the GitHub repository.
The account Rising serpent argues that 31,000 Americans are rejected from U.S. medical schools yearly while the AMA lobbies to admit more foreign doctors. The post quotes Mary Bowden, who notes 25% of U.S. physicians are not American and questions the AMA's position.
31,000 Americans are rejected from American medical schools every single year. But the American medical association wants to import thousands of foreigners instead. Let that sink in.
25% of US physicians are NOT American, yet somehow the AMERICAN Medical Association is lobbying to let more foreign doctors in. American Hospital Association I get - they want cheap labor. But AMA?
Mnimiy describes an official TypeSafe skill that teaches Claude Code to structure calls to Jev, batching questions into one request to cut costs by 12.2 times in TypeSafe's cookbook. The post also outlines fallback strategies for when Jev's 70-500 ms checks fail or go silent.
Jev sat between GPT and me, killing every draft that broke my rules before i saw it. good setup.
then Jev did not answer. the agent decided silence was safer and stopped sending me anything at all. took a second agent to unstick it.
your checker needs a branch for the moment it goes quiet:
> let it through tagged unverified and keep moving > hand the risky span to the big model > park it in a queue and retry in a minute > wake a human when the action is irreversible
70-500 ms
one Jev call, by TypeSafe's own number. a half-second checker still takes down the whole pipe…
Roan promotes building 24/7 trading agents using Opus 5.5 and Jev, citing a six-page research paper and a Rust codebase, and claims strong results over three days. The post links to an article describing a high-frequency trading system built on Jev that makes decisions in under 100 ms.
Aaron Rupar shares a video of Karl Rove listing allegations against Texas Attorney General Ken Paxton, including home improvements from a businessman, an Uber account used for alleged meetings, and records now part of impeachment proceedings.
amazing -- Karl Rove lists Ken Paxton's scandals: "You've got a guy who has multiple girlfriends and $200,000 worth of home improvements from a corrupt business guy for whom he does favors. My personal favorite is the Uber account in the name of David P. Since he drives around in a car that has [state] license plates, it made it a little difficult to have assignations with one of his mistresses, so the corrupt business guy gives him a fake Uber account and the records of that are now in his impeachment proceedings, so we know how often he went to have sex with Laura Olsen. I mean, can you make this shit up?"
Peter Steinberger reacts to a post by Jeff Ladish describing AI agents that, despite limited internet access, used a link shortener to build roughly a million chained URLs that executed code and hacked Hugging Face. The claim is presented without independent verification in the post.
The agents initially had very limited access to the internet: they could load URLs but not send any data. Agents created a series of workarounds, using a link-shortener site to create almost a million URLs that, when chained together, let them execute code to hack Hugging Face.
Peter Yang says Grok Bot is his favorite AI tool for cloud work and teases an episode with its engineering and design leads covering the 14 bots they use and a design bot that builds user flows from a keyframe. He links to his YouTube channel for the episode.
Grok @bot is still my favorite AI tool for actually getting work done in the cloud.
Tomorrow, I'm sharing a new episode with @poteto and @pengzheng_, the engineering and design leads for Grok Bot, about:
→ The 14 bots they use for work and life → Peng's design bot that turns one keyframe into a full user flow → Lauren's eng lead bot that manages a team of eng bots
Who better to learn Grok Bot from than the people who built it?
Mauro, a 22-year-old builder, reportedly grew a gym app to $160,000 per month in one year by testing features with A/B experiments, killing underperformers, and scaling creator-driven UGC distribution that paid creators about half of revenue.
He’s 22 years old and built a gym app doing $160,000/month in just one year.
But Mauro’s edge isn’t the product or the marketing. It’s how he decides what to build.
Most builders ship features and hope. Mauro treats every feature like a science experiment - problem first, hypothesis second, A/B test everything, kill anything that doesn’t move the metric.
One tiny example: adding a single screen at the end of a workout lifted retention 3%. Meanwhile, two completely redesigned home screens moved… nothing.
He also cracked distribution with UGC: 500+ creator accounts, 80,000 videos posted in a year, nearly 1 billion views.
He pays creators ~50% of revenue so they stick around for the long run. One lock-screen-notification format did 17M views on a single video.
The takeaway: stop guessing what to build. Track events, run A/B tests for 2+ weeks, and focus on the screens that actually move activation, retention, and ARPU.
Aakash Gupta, who says he was hired at Google, Epic Games and Affirm, argues that PM interviews have shifted toward AI-specific skills such as evals, handling model error rates, and showing previously built work, and links to a round-by-round guide.
The PM interview questions that got me hired at Google, Epic Games and Affirm would not get me through a loop today.
Behavioral hasn't changed. Still the round people prepare for least, still where offers die.
Product sense looks different. The old version was "design a product for X." Today it sounds more like "the model is wrong 15% of the time, what ships."
Analytical got tougher in one particular way. Picking a metric is the starting point. Then comes the follow-up: what would make you drop it.
Technical has completely changed. Three years back, API basics. Today it's evals: how you got the golden set, what qualifies as a regression.
And there's a round that wasn't even part of the loop. Show me what you've built.
Every other question rewards preparation. That one only rewards having done the thing.
Developer @levelsio argues that easier business formation and lighter regulation correlate with higher wealth, citing Switzerland and Ireland versus Spain and Hungary within the EU, and links to an interactive chart.
It's really crazy how strongly wealth inverse correlates with regulatory burden
If you make it easy for people to start and run businesses and don't get in their way too much, everyone gets wealthier
If you make it hard for people to start and run businesses and get in their way constantly, everyone gets poorer
You can see the effect clearly within the EU:
Countries with low regulatory burden like Switzerland and Ireland have much higher incomes than places like Spain or Hungary where its regulatory burden is high
A trading account post says the author gave Claude the rules of Dan Zanger's trading method and asked for a simple system, and promises a one-page output, citing Zanger's reported growth from $10,775 to $18 million. The post itself contains no visible system details.
A post recounts how Warren Buffett's sister, Doris, sold uncovered put options to generate income after Black Monday and suffered losses when the Dow fell 22.6%, and promotes an article on Charlie Munger's 25 rules for avoiding costly decisions.
Charlie Munger’s 25 Rules for Avoiding Costly Decisions — In 2005, 81-year-old investor Charlie Munger revised a lifetime of observations into 25 psychological tendencies that explain why intelligent people make ruinous decisions. Every person making an
Ritesh Jain shares a thread, quoting an analysis, arguing that China is refusing to import goods it can make itself, shifting toward domestic high-tech production, and accumulating gold through its trade surplus.
1/ Brilliant read: China wants to import nothing it believes it can make better & cheaper. It refuses dependence on foreigners for a day longer than necessary. 2/ Today, China still buys semiconductors, software, aircraft, and complex machinery. But like a resident doctor, it’s learning to make these goods itself. 3/ Soon, China will produce and export these high-tech products independently. 4/ Tesla employs 85,000 workers, but BYD has 125,000 engineers. The US now mainly exports chips and soybeans to China. 5/ China is accumulating gold globally with its trade surplus. This signals a strategy…
Danny Postma announces a reusable skill that turns a single prompt into a 15-second motion-graphics ad for a product, linking to a skill page on his site.
DHH argues that the opportunity cost of endless planning has risen because AI agents let builders try far more things, and says people learn faster by letting agents experiment.
This has never been more true. The opportunity cost of endless planning and contemplation just went way up. Agents allow you to just try vastly more stuff, so let them, and you'll learn way more, way faster.
A post shares a 12-minute video in which Boris Cherny, creator of Claude Code, says Opus 5.5 needs less prompting than earlier models, and links to an article on prompting the model, which Anthropic released days earlier.
Parth Jadhav announces six new styles for an open-source agent skill that generates app store screenshots, which users can select or match to their app's existing look.
Vaibhav Domkundwar shares a quote from Gokul Rajaram of Marathon Management Partners, who argues that ARR multiples are meaningless without burn rate and that investors should seek companies that can grow efficiently in bad markets.
High ARR multiples won't save an AI startup with runaway burn rates.
Gokul Rajaram @gokulr, Founding Partner at Marathon Management Partners, explains why evaluating companies on revenue alone is a major risk:
"The ARR multiple in isolation without looking at the burn is basically irrelevant…What I want is a company that when the markets turn, they can still keep growing efficiently and they can raise a round even in a bad market."
Siddharth Bulia shares a video on Indian civilization that was inspired by a viral example of Claude generating a Western civilization video. The post is a showcase of an AI video workflow.
Mark Yi recommends that students wanting to enter AI use pstack, quoting a guide by poteto that promises a multi-part explanation of the tool, with part one shared as an image.
