iOS Software Engineer that loves to drink from fire hoses. Optimistic believer in humanity. Agnostic atheist for evidentialism and methodological naturalism
Austin, TX
Joined November 2011
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Decided to release a few songs on YouTube. I've had trouble finding enough music with messaging I find empowering and, thanks to modern technology, decided to adapt some amazing poems to orchestral performances. More to come!
youtu.be/6HpYdPyjvJM
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Eric Mentele retweeted
In 1979, a talk show host looked at one of the most influential economists alive and told him, on live television, that capitalism ran on greed.
Milton Friedman had won the Nobel Prize in Economics three years earlier, in 1976, for his work on monetary theory and consumption analysis.
Phil Donahue, host of the highest-rated daytime talk show in America, asked him directly whether the concentration of power and profit under capitalism had ever given him a moment of doubt.
Friedman didn't pause before answering. "Well, first of all, tell me, is there some society you know that doesn't run on greed? You think Russia doesn't run on greed? You think China doesn't run on greed?"
He kept going, arguing that only capitalist societies built on voluntary exchange had ever lifted large numbers of people out of poverty, while every attempt to replace self-interest with central planning had made things worse.
Donahue tried one more angle, asking who would organize a fairer society if not government. Friedman's answer to that question is still being clipped and argued over online more than four decades later.
Their exchange lasted less than two minutes inside a much longer interview about the Great Depression, auto bailouts, and price controls, and it's become one of the most replayed moments in the history of televised economics.
Was Friedman right that every system runs on self-interest whether we admit it or not, or did he dodge the real question about inequality? Say which side you land on in the comments, then watch the full exchange below.
Eric Mentele retweeted
Simple exercise to focus your mind and stop worrying:
– Draw a line down the middle of a piece of paper
– Left side: everything you're concerned about (world events, opinions, outcomes)
– Right side: everything you can directly influence
– The right side will almost always have just one thing: yourself
– Break "yourself" down: how you think, how you speak to yourself, how you plan your day
– Do this exercise once a month, or whenever sticky thoughts wake you up at 3am
Retired Navy SEAL @AndyStumpf77 on @hubermanlab
Eric Mentele retweeted
there are only a few thousand people left in america that know how to design an injection mold, even fewer for die casting and other molds/dies. a dying art that will cost the economy trillions of dollars over the next generation if we let it slip away.
Eric Mentele retweeted
We are back. After one year of quiet building.
Introducing GENE-26.5, our first robotic brain that takes a major step toward human-level capability.
For years, robotics has struggled to learn from the world’s largest and valuable data source: Humans.
Solving it means rethinking the whole stack from the ground up:
- A robotics-native foundation model.
- A 1:1 human-like robotic hand.
- A noninvasive data collection glove for motion, force, and touch.
- A simulator that turns weeks of experiments into minutes.
GENE-26.5 is trained across language, vision, proprioception, tactile, and action. We designed a set of tasks to test how far we can go with this new paradigm.
Fully autonomous, 1x speed, one model, same weights. (Enjoy with sound on)
We are approaching the endgame for robotics.
And this is just a beginning.
Eric Mentele retweeted
C'est exactement la phrase qui résume tout le débat. Et elle mérite d'être développée parce qu'elle pose le bon cadre, celui que la France a oublié depuis 40 ans.
Il y a deux façons de réduire les inégalités. Le nivellement par le haut, et le nivellement par le bas. Ce sont deux philosophies opposées, et le choix entre les deux détermine la trajectoire d'un pays sur un siècle.
Le nivellement par le haut, c'est tirer les pauvres vers le haut. On accepte que des gens deviennent très riches, parce que leur richesse est créée, pas extraite. Et en créant cette richesse, ils créent des emplois, des produits, des infrastructures, des innovations qui élèvent le niveau de vie de tout le monde. Le pauvre d'aujourd'hui vit mieux que le bourgeois de 1900. Il a un smartphone, l'eau courante, l'électricité, l'accès aux soins, l'espérance de vie de 82 ans. Tout ça a été produit par des entrepreneurs qui sont devenus riches en le produisant.
Le nivellement par le bas, c'est l'inverse. On refuse que des gens deviennent très riches, par principe moral. Donc on taxe, on régule, on confisque. Le résultat n'est jamais que les pauvres deviennent riches. Le résultat est toujours que les riches partent ou ne se créent pas, et les pauvres restent pauvres. Mais l'écart se réduit, donc politiquement on peut dire qu'on a "réduit les inégalités". L'égalité dans la médiocrité partagée.
Le test empirique est imparable. Les États-Unis ont produit Bezos, Musk, Zuckerberg, Gates. Ils ont aussi un SMIC effectif, une fois converti en pouvoir d'achat, supérieur au nôtre. Le pauvre américain a une voiture, un grand frigo, et accès à des biens qu'un cadre français ne peut plus se payer. La Suisse, qui a refusé de taxer ses riches, a un salaire médian deux fois supérieur au nôtre. La France, qui a méthodiquement chassé ses riches depuis Mitterrand, a vu son pouvoir d'achat médian stagner pendant que celui de l'Allemagne, de la Suisse et des US explosait.
C'est ça le drame français. On ne s'est pas appauvri en chassant les riches. On a appauvri les pauvres en chassant les riches. Parce que les riches ne sont pas des oisifs assis sur un tas d'or. Ce sont des gens qui dirigent des entreprises, créent des emplois, paient des salaires, lèvent des capitaux, prennent des risques. Quand ils partent ou ne se créent pas, ce sont les emplois, les salaires et les capitaux qui partent avec eux.
Il faut vraiment intégrer ça : la richesse n'est pas un gâteau fixe qu'on se partage. C'est un gâteau qui grossit ou qui rétrécit selon les règles du jeu qu'on impose. En France on a passé 40 ans à punir ceux qui font grossir le gâteau, en se disant que ça ferait des plus grosses parts pour les autres. Résultat, le gâteau a rétréci pour tout le monde, sauf pour la classe des fonctionnaires d'État protégés du marché.
Et la dernière chose, qui devrait être enseignée à l'école. Pour qu'il y ait des moins pauvres, il faut qu'il y ait des plus riches. Ce n'est pas un slogan, c'est une identité comptable. Si vous voulez que le SMIC monte, il faut que la productivité monte. Si vous voulez que la productivité monte, il faut des entreprises qui investissent. Si vous voulez des entreprises qui investissent, il faut du capital. Si vous voulez du capital, il faut des gens qui ont accumulé des fortunes et qui acceptent de les risquer plutôt que de les planquer.
Tous les pays qui ont sorti leurs populations de la misère, sans exception, ont d'abord laissé émerger des riches. Coréens, Taïwanais, Singapouriens, Polonais, Chinois post-1978. Aucun pays n'a jamais enrichi ses pauvres en empêchant l'enrichissement de ses entrepreneurs. Aucun. Zéro. C'est l'expérience la plus massive de l'histoire des sciences sociales, et elle est sans appel.
Donc oui, qu'il y ait des gens riches ne devrait poser de problème à personne. Ce qui devrait poser problème, c'est de vivre dans un pays où on n'arrive plus à en produire.
Eric Mentele retweeted
OpenClaw: The complete guide
@ClaireVo has just put together the definitive guide to getting started with and mastering OpenClaw.
Building on our podcast episode, this post covers everything you need to know, from first install to multi-agent setups, plus the real costs and security gotchas most people skip over.
Whether you’re brand new to OpenClaw or already running one, Claire’s guide will level you up.
Find it here 🦞: lennysnewsletter.com/p/openc…
Eric Mentele retweeted
🚨 WOW! Artemis II pilot Victor Glover gives the PERFECT response to a leftist reporter asking about skin color
"I hope we push that one day...it's about human history, humanity, NOT 'black history,' not 'women's history,' but that it becomes human history!"
RIGHT ON!
Victories for Americans and victory for humanity 🇺🇸🚀
Eric Mentele retweeted
We invented “teenagers”
Our society is rich enough to delay the true responsibilities of adult life, but many teenagers want to participate in society
We squander their interest in work by forbidding it (legally) and then wonder why they are withdrawn and frustrated
🙃
The concept of "teenager" is a modern invention.
For most of human history, a boy of 13 was already a man, apprenticed in a trade or fighting in a war.
George Washington was a professional surveyor at 16.
Alexander Hamilton managed a trading company at 14.
In medieval Europe, noble boys could be pages at 7 and squires by 14.
In Rome, a boy put on the "toga of manhood" at 14.
The idea that an 18 year-old is "still figuring things out" would have been incomprehensible to our ancestors.
I believe this is why we think teenagers are so troubled. They are men and women stuck in a society that treats them as children. Of course they are going to "rebel".
We should give them more responsibility and expect much more of them.
Eric Mentele retweeted
Panel discussions usually suck.
This one didn't (for the AI community).
It is of NVIDIA CEO/founder Jensen Huang interviewing 10 CEOs from frontier AI labs about what's happening in Open Models. In audience was thousands of the world's top AI thinkers.
CEOs on stage in the first part:
@hwchase17, CEO of Langchain.
@miramurati, CEO of Thinking Machines.
@AravSrinivas, CEO of Perplexity.
@mntruell, CEO of Cursor.
@MishaLaskin, CEO of Reflection Labs.
CEOs on stage in the second part:
@arthurmensch, CEO of Mistral.
Daniel Nadler, CEO of OpenEvidence.
@HannaHajishirzi, CEO of Ai2.
@robrombach, CEO of Black Forest Labs.
@AnjneyMidha, CEO of AMP.
It was funny how Jensen gave Arthur heck for his accent. But it was true, it was hard to understand what he was talking about for a while.
Here is the transcript and what Grok learned by watching this: grok.com/share/bGVnYWN5_9610…
Grok concludes: "If you're interested in where AI applications and infrastructure are heading in the next 1–3 years, this panel is a goldmine of unfiltered CEO-level insight."
Eric Mentele retweeted
74% of abducted children who are killed die within the first 3 hours. 44% within the first hour.
I have a 4-year-old. When I found that FBI stat, I stopped what I was doing and started teaching him four things that afternoon.
1. Phone number. Memorized, not stored in a device. A kid who can recite a parent’s number to any adult with a phone becomes findable in seconds.
2. Code word. Any adult who says “your mom sent me” gets tested. If they don’t know the word, he runs. A 4-year-old can learn this in one conversation.
3. Stop, stay, yell. This one overrides the freeze response. FBI data shows 80% of initial contact between an abductor and a victim happens within a quarter mile of the child’s home. The quiet, compliant kid is what predators count on. A kid trained to scream on reflex changes the math. Every decibel is a witness.
4. Find a mom with kids. A small child can’t judge whether a stranger is safe. But a woman already watching her own children in public is the closest thing to a guaranteed safe adult. She’s the person most likely to act in seconds.
460,000 children are reported missing in the U.S. every year. One every 69 seconds. Recovery rate is above 97%. What separates the 97% from the 3% is almost always what happened in the first few minutes.
In nearly 60% of abduction homicide cases, more than two hours passed between when someone realized the child was missing and when police were called. The reporting delay alone eats most of the survival window. Every one of these five skills attacks that gap.
Four rules a 4-year-old can memorize. Each one turns hours of panic into seconds of correct action.
I worked 20 years for a child sex trafficking rescue group. I want you to know this:
90% of Lost Children Are Found Within 30 Minutes.
That statistic should both comfort you and wake you up.
Most lost children are found quickly. But the ones who aren’t? They usually made one mistake.
And here’s the uncomfortable truth:
It’s often the exact thing most parents teach them.
We tell our kids:
“If you get lost, come find me.”
It sounds logical. It sounds empowering.
It’s WRONG!
The Mistake Most Lost Children Make:
When children realize they’re separated, they do three things almost automatically:
They panic.
They wander.
They try to find you.
Every step makes them harder to locate.
From a search standpoint, movement creates chaos.
Parents retrace their steps.
Security scans zones.
Staff lock down areas.
Search works best when movement stops.
When a child keeps walking, they move outside the original search radius. Helpers are looking where they were last seen — not where they’ve wandered.
Stillness increases probability.
Movement expands the problem.
The first lesson is not “go find me.”
It’s this:
Stop. Stay. Yell.
Why Stillness Wins:
Think like a search team.
If a child stays put:
Parents can retrace steps.
Security can scan systematically.
Helpers converge to one fixed location.
The search radius remains small.
If a child keeps moving:
The search area expands.
Adults pass each other.
Missed connections multiply.
Minutes stretch into hours.
Stillness keeps the math on your side.
Teach Them Who to Approach:
The second mistake we make as parents?
We say, “Find an adult.”
Not any adult. Not the nearest stranger. Children need a filter.
Teach them to look for, if at all possible:
A mother with children.
Caregivers who already have kids with them are statistically among the safest people to approach in public settings. They are visible, stationary, and more likely to engage quickly.
It’s a clear, concrete instruction.
Children don’t process vague categories like “safe adult.”
They process visuals.
“Find a mom with kids” is visual.
A Phone Only Helps If the Number Is Known:
We often assume phones solve everything.
They don’t — unless your child can use one. Even young children can memorize a 10-digit phone number with repetition.
But you must train it.
Practice it like a song.
Sing it in the car.
Chant it at bedtime.
Turn it into rhythm.
Repetition becomes recall.
In an emergency, recall matters more than theory.
The Code Word Rule:
One more layer of protection.
Choose a private family code word.
Something only your household knows.
If someone approaches and says:
“Your mom sent me.”
Your child asks:
“What’s the code word?”
No word.
No go.
This simple rule eliminates manipulation attempts instantly.
It gives your child agency without requiring them to evaluate character.
Real Safety Is Training — Not Luck!
We don’t get safer by hoping.
We get safer by practicing.
Teach:
• Phone number
• Code word
• Stop, stay, yell
• Find a mom with kids
Multiple skills.
Simple instructions.
Clear visuals.
Five minutes of training can replace hours of panic. This isn’t about fear. It’s about preparation.
Because when a child gets separated, the clock starts.
And what they do in the first minute determines what the next thirty look like.
That’s real protection.
Eric Mentele retweeted
Pay attention to this. One of the most important breakthroughs in LLM’s right now.
Can’t stress enough how impactful this will be.
We will start to see more and more optimizations at this level going forward and it seems like we are just getting started.
Eric Mentele retweeted
🤯BREAKING: Alibaba just proved that AI Coding isn't taking your job, it's just writing the legacy code that will keep you employed fixing it for the next decade. 🤣
Passing a coding test once is easy. Maintaining that code for 8 months without it exploding? Apparently, it’s nearly impossible for AI.
Alibaba tested 18 AI agents on 100 real codebases over 233-day cycles. They didn't just look for "quick fixes"—they looked for long-term survival.
The results were a bloodbath:
75% of models broke previously working code during maintenance.
Only Claude Opus 4.5/4.6 maintained a >50% zero-regression rate.
Every other model accumulated technical debt that compounded until the codebase collapsed.
We’ve been using "snapshot" benchmarks like HumanEval that only ask "Does it work right now?"
The new SWE-CI benchmark asks: "Does it still work after 8 months of evolution?"
Most AI agents are "Quick-Fix Artists." They write brittle code that passes tests today but becomes a maintenance nightmare tomorrow. They aren't building software; they're building a house of cards.
The narrative just got honest: Most models can write code. Almost none can maintain it.
Eric Mentele retweeted
A powerful scene in the Odyssey happens when Odysseus finally returns to Ithaca after twenty years of war and wandering.
You would expect the story to end with celebration, with the hero coming home, the family reunited, and order restored.
Homer does something far stranger.
Odysseus arrives disguised as a beggar, because Athena warns him that the palace has been taken over by more than a hundred suitors who have been living there for years, eating his food, drinking his wine, and pressuring his wife Penelope to marry one of them.
They believe Odysseus is dead and in their minds the kingdom is already theirs.
So the king of Ithaca walks through his own halls dressed in rags while the men stealing his house sit comfortably at his tables. They mock him, throw scraps at him, and one of them even strikes him, and Odysseus takes it. That is the remarkable part, because the same man who blinded the Cyclops and survived twenty years of disasters now stands quietly while strangers insult him in his own home. Homer tells us his heart burns inside his chest and that he wants to attack them immediately, yet he restrains himself and waits.
Instead of striking, Odysseus studies the room carefully. He counts the men, watches their habits, and quietly observes which servants remain loyal and which have betrayed him. The hero of the Odyssey does something most people cannot do, which is delay revenge until the moment is right.
Eventually Penelope announces a contest and brings out Odysseus’ great bow, declaring that she will marry the man who can string it and shoot an arrow through twelve axe heads lined up in a row. One by one the suitors try and fail, because none of them can even bend the bow. Then the beggar asks for a turn. The suitors laugh at first, but the bow is eventually handed to him.
Odysseus takes it in his hands and strings it effortlessly. Homer says the sound of the bowstring tightening rings through the hall like the note of a swallow. Then he places an arrow on the string and sends it cleanly through all twelve axe heads.
In that moment the beggar disappears. Odysseus turns the bow toward the suitors and reveals who he is.
What follows is one of the most brutal scenes in Greek literature. The doors are sealed and the suitors realize too late that they are trapped inside the hall. Odysseus, his son Telemachus, and two loyal servants begin killing them one by one. There is no escape, no mercy, and no negotiation. The men who spent years consuming another man’s house die inside it.
It is a violent ending, but Homer wants you to understand something important. The real danger to Odysseus was never just the monsters and storms on the long journey home. It was the possibility that someone else might take his place while he was gone. When Odysseus finally returns, he reminds everyone in Ithaca of a simple truth: a man’s home is not truly his unless he is willing to fight for it.
Eric Mentele retweeted
…after a dayyy of @openclaw hacking and building
Me: are we losing our minds???
Husband: yes, but we are also building new ones
Legend 👑
Eric Mentele retweeted
Bayes’ theorem is probably the single most important thing any rational person can learn.
So many of our debates and disagreements that we shout about are because we don’t understand Bayes’ theorem or how human rationality often works.
Bayes’ theorem is named after the 18th-century Thomas Bayes, and essentially it’s a formula that asks: when you are presented with all of the evidence for something, how much should you believe it?
Bayes’ theorem teaches us that our beliefs are not fixed; they are probabilities. Our beliefs change as we weigh new evidence against our assumptions, or our priors. In other words, we all carry certain ideas about how the world works, and new evidence can challenge them.
For example, somebody might believe that smoking is safe, that stress causes mouth ulcers, or that human activity is unrelated to climate change. These are their priors, their starting points. They can be formed by our culture, our biases, or even incomplete information.
Now imagine a new study comes along that challenges one of your priors. A single study might not carry enough weight to overturn your existing beliefs. But as studies accumulate, eventually the scales may tip. At some point, your prior will become less and less plausible.
Bayes’ theorem argues that being rational is not about black and white. It’s not even about true or false. It’s about what is most reasonable based on the best available evidence. But for this to work, we need to be presented with as much high-quality data as possible. Without evidence—without belief-forming data—we are left only with our priors and biases. And those aren’t all that rational.
Eric Mentele retweeted
Is this the fall of the American empire? Are we doomed, like Rome?
Some headlines suggest that.
But historian @johanknorberg says, “We can still save this Golden Age” if we learn the lessons from other golden ages:
