joe

guided by beauty

[Ethan Kho @ethanrkho]

Victor Haghani helped build LTCM & watched it collapse — with winning trades still on the books. The lesson was never what to buy. It was how much.

Victor Haghani (Co-founder @ LTCM | Founder @ Elm Wealth | Author of The Missing Billionaires)

"It wasn't on the selection of the trades. It was on the sizing."

We cover:

- The two decisions every investor makes: what to own and how much, and why everyone fixates on the harder one
- The biased-coin game that bankrupted Wall Street PMs and finance grads: a 60/40 edge handed to them, and they still blew up
- Why the cost of risk is a fee you pay yourself, plus the napkin rule to price it (15% vol = 2.25% a year)
- The Elon problem: 50% vol on your net worth means a ~90% chance of little left in 10 years, before anyone's even bearish
- "The right answer to the wrong question," and why chasing billionaire money wrecks the plan
- The crystal-ball game: hand someone tomorrow's WSJ front page and watch 1 in 6 still go bust
- Claude, GPT, Gemini and Grok play the same game, and the two AIs that actually lost money
- His 92-year-old mother, who day-trades every day and won't hear a word of it

Highlights:
00:00 Right & ruined — the LTCM paradox
01:40 The two decisions: what to invest in vs. how much
02:50 The 60/40 coin & why max-EV bankrupts you
04:00 The experiment: PMs & PhDs sizing it all wrong
07:00 Kelly in plain English — a constant 10–20%
08:20 Why sizing isn't zero-sum, but beating the market is
10:30 Why even pros don't optimize sizing
12:50 The cost of risk is a fee — paid to yourself
15:20 Pricing your own risk: variance as the charge
16:30 Concentrated stock: 30% vol = a 9% toll
20:50 Elon, 50% vol & the log-normal trap
22:45 The right answer to the wrong question
23:35 The real objective: smooth lifetime spending & giving
27:35 The crystal-ball / WSJ front-page game
33:25 Claude, GPT, Gemini & Grok step up to trade
37:40 Claude's 66% hit rate — & the two AIs that lost money
40:35 Can anyone actually beat the market?
50:25 How much risk a young person should take
58:00 Estimating your human capital
1:02:40 The mom who won't stop day-trading
1:07:30 The one rule: if you don't save, nothing else matters

[The All-In Podcast @theallinpod]

POD UP! 🚨

Besties are back to discuss:

-- SpaceX's record IPO, Cursor deal, and the first trillionaire

-- The modern politburo and the new oligarchy (@friedberg cooks)

-- Behind the scenes of the Anthropic Fable ban

-- Iran War peace deal

(0:00) Bestie intros!

(2:41) The New Oligarchs, America's incoming politburo, and learned helplessness

(14:18) SpaceX's record breaking IPO, $60B Cursor acquisition, and the trillionaire reactions

(33:34) Behind the scenes of the Anthropic Fable ban

(1:01:18) Claude psychoanalyzes its creator, Dario Amodei

(1:14:31) Iran War MOU and the market impact

[Per Bylund @PerBylund]

#Poverty is the lack of wealth, which must be created. #Prosperity is the state of having created or otherwise acquired wealth. The former must have preceded the latter, both logically and historically. https://t.co/UpOCd9xAOH

[Per Bylund @PerBylund]

What causes #poverty? Nothing. It's the original state, the default and starting point. The real question is, What causes #prosperity?

[Paul Graham @paulg]

Something I told 14 yo: People are going to stop reading books. I wish this wasn't so, but I fear it is. The silver lining in this cloud is that if you're one of the few people who still read, you'll have a huge advantage over everyone else.

[Dwarkesh Patel @dwarkesh_sp]

Adam Brown (@A_G_I_Joe) is back!

General relativity is said to be the most beautiful idea the human mind has ever produced.

Most of us will never get to fully appreciate its elegance by taking the 20-lecture graduate course Adam taught on it at Stanford.

But in the video below, Adam distills the key idea at its heart so clearly and compellingly that even I could keep up lol.

At the core of general relativity, Einstein is trying to figure out the principle behind a particular coincidence: that the mass that resists acceleration and the mass that gravity pulls on just happen to be exactly the same. Adam then leads us through the path of insight which Einstein called his “happiest thought.”

Then Adam lectures on black holes. First, by showing how even under special relativity you could create a perpetual motion machine if black holes weren't truly black. And then, by explaining why the observations of an infalling observer and a distant bystander to the black hole would be so radically different

Adam leads Blueshift, the team at Google DeepMind cracking science and reasoning.

Which gave us the opportunity to discuss at the very end how close we are to AIs that could rediscover general relativity from scratch. Stay till the close for some philosophy of science.

0:00:00 – The coincidence that led Einstein to general relativity
0:16:42 – Gravity is a consequence of curved spacetime, not a force
0:31:46 – Why black holes prevent unlimited energy extraction
0:47:12 – Black holes are the ultimate power plants
1:13:50 – What falling into a black hole would actually feel like
1:18:51 – The three ways we know black holes are real
1:24:21 – The first time we saw gravity bend light
1:29:33 – How far can AI get without experimental evidence?

Look up Dwarkesh Podcast on YouTube/Spotify to watch. Enjoy!

[Claude @claudeai]

Introducing Claude Science, a new app designed with every stage of research in mind.

Artifacts traced to their code, environments managed on demand, and 60+ optional scientific databases that you can connect.

Available now in beta.

[joe @joseph16z]

Against the emptiness of ceremonies in the absence of sincere faith.

[Cobie @cobie]

People that mourn mistakes simply don’t believe in themselves. Everyone that wants to make it in 1 month is really saying “I need to get very lucky because I do not believe I am equipped to make it in a sustainable way over the next 5-10 years”. Those people would be much better off studying, trying again, failing, learning, etc until they do believe in themselves. And then it doesn’t matter.

[Paul Graham @paulg]

How to Earn a Billion Dollars: https://t.co/WeWBUkKym6

[joe @joseph16z]

it should be a loop where the value recurs to ALL in that ecosystem.

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[Alex Rives @alexrives]

Together with UC Berkeley we are announcing the laser phase plate - a breakthrough in atomic resolution imaging. This is the brightest continuous wave laser in the world, 100 million times the intensity of the surface of the sun.

Phase contrast plays an important role in microscopy, but it was thought close to impossible for electron microscopy, where it would require interfering with an electron beam. Holger Mueller and Robert Glaeser proposed exactly this using a standing wave laser. It has taken over 15 years to make this a reality. Biohub partnered with UC Berkeley and Mueller to support this work and to engineer and build the technology.

Contrast has been the critical barrier to achieving atomic resolution imaging of the cell. In cryo-electron tomography, a cellular imaging technology that uses electron microscopy, the low contrast makes it impossible to resolve anything but the largest proteins within their cellular context. The laser phase plate removes that barrier.

With advances in AI this breakthrough in contrast will start to open up a new frontier in structural biology, that will allow us to see the molecular machines of the cell, and how they assemble into far more complex and dynamic systems, and understand how they work.

[joe @joseph16z]

@colin_alex35207 Beautiful!!!! How many days of dedicated practice are we seeing here? And what are some of these quotes?

[Startup Archive @StartupArchive_]

Palmer Luckey’s advice for founder-led communications

“My advice to people would probably be to recognize that the value of your reputation is very high,” Anduril founder Palmer Luckey begins. “If people do not trust you; if they do not believe in what you’re saying; if they do not think that you’re a person worth listening to, they’re going to have a hard time working with you.”

Palmer also argues that founders don’t need to be neutral:

“You don’t need to be neutral. You can be a propagandist. You can advocate for a particular point of view . . . In general, people should recognize that if you say something where you caveat it and hedge it and basically end up saying something that most people would agree with, you might as well have said nothing at all.”

He continues:

“You are not going to build a following of people who say, ‘I just love Palmer’s right-down-the-middle, very-hedged takes that everyone agrees with.’ If you’re just restating common sentiment, it’s not going to get you anywhere . . . So one of the things I tell people is, ‘Make sure that when you’re saying something, you’re SAYING something. Make sure you’re trying to persuade and affect change.’ — maybe not in everybody, but in some people. If you make some people love what you’re saying and some people hate what you’re saying, that’s a lot better than having everybody lukewarm agree with you. Don’t waste your time communicating about the things everyone already agrees with you on. Focus on the things where you need to change their mind.”

Source: @lulumeservey (Sep 2025)

[Justin Drake @drakefjustin]

Today a crazy quantum story just got wilder.

On March 31, the Google Quantum AI team published a landmark result on Shor's algorithm for elliptic curve cryptography. Technically, the paper was a bombshell: a dramatic 10x improvement over the state-of-the-art. As a stunt and wakeup call to the blockchain space, those optimisations were illustrated on secp256k1, the elliptic curve underlying Bitcoin and Ethereum signatures.

But perhaps the most striking part of the paper was sociological, not technical. Instead of following standard academic process, the optimisations were kept secret, hidden behind a zero-knowledge (ZK) proof. Google's accompanying blog post mentions they "engaged with the U.S. government". The ZK proof demonstrates the existence of algorithmic improvements without leaking details. Academic censorship with ZK, a historic first!

As a co-author of the Google paper I witnessed some of the context surrounding this censorship. To be honest, multiple aspects of that context don't sit well with me. As much as I believe the general public ought to know more, I am limited in my ability to whistleblow. Though let me be clear about one thing: the Google team's professionalism has been absolutely exemplary, and they deserve nothing but praise.

Censorship has a way of backfiring. The Streisand effect, where an attempt to bury something only draws more attention to it, is exactly what's unfolding today. First, Google's key optimisation has been rediscovered by the French. And in a thrilling turn of events, a collaborative Shor-at-home challenge just launched. The initiative, available at ecdsa[.]fail, breached a new Shor world record in a matter of hours.

Let's start with the rediscovery. Just two months after Google's paper, French quantum expert André Schrottenloher cracks the main secret optimisation. His paper, titled "Optimized Point Addition Circuits for Elliptic Curve Discrete Logarithms", landed on the arXiv today. Big congrats to André, who beat several other nerdsnipped experts to it. In a blog post also published today, Craig Gidney, the world expert on Shor optimisations, revealed that he'd been sitting on this very optimisation for a whole year under censorship pressure.

Interestingly, André missed a handful of minor optimisations, both from Google's original publication and from improvements found since. It's plausible there's still plenty of juice left to squeeze out of Shor, and this is exactly what the ecdsa[.]fail challenge is about. The verifier program developed for the ZK proof does double duty, automatically filtering for valid submissions. Dozens of compounding small and micro improvements are rolling in. As of the time of writing there's an 8.4% improvement to Google's circuit, as measured by the product of logical qubit count and Toffoli gate count. Nice!

The nerdsnipping ran deeper than anyone expected. Over the last few weeks it became clear it extended well beyond André and other quantum experts. Behind the scenes, a small army of amateurs quietly got to work. Inspired by Karpathy-style autoresearch, they turned AI on Shor. Ironically, the verifier program for the ZK proof makes an ideal reward function for AIs. The barrier to entry for this modern style of research is refreshingly low, with several non-experts, even a teenager, finding nice optimisations. Get in touch if you'd like to join a Telegram group with fellow autoresearchers :)

Part 2: neutral atoms and qday

The story doesn't end with Google. On the same day Google went public, a stealthy startup called Oratomic published its own Shor paper in a coordinated release. It made a splash, ultimately becoming the most upvoted paper on scirate[.]com, a website ranking arXiv papers.

Oratomic's claim was wild. By building on Google's logical optimisations and applying custom physical optimisations for neutral atoms, they claimed just 10K physical qubits were sufficient to run Shor's algorithm on secp256k1. That number is mind-bogglingly low.

Knowing essentially nothing about neutral atoms when Oratomic's paper landed, I was intrigued and decided to learn more about the tech. I fell straight down the rabbit hole and spent a couple hundred hours on the topic. I got a little obsessed and watched every YouTube video I could find and spoke to a bunch of experts.

My conclusion? The tech is real, very real. Even Google recently decided to start a neutral atom lab, a notable pivot from their sole focus on superconducting qubits. If you care about qday, i.e. the day a quantum computer will break the first piece of cryptography in production, neutral atoms demand your attention. I shared some of my learnings on Shor and neutral atoms in a 30min talk at the ZKProof cryptography conference. You can find it on YouTube by searching "zkproof neutral atom".

Here's an interesting observation about this duo of breakthrough papers: neither Google nor Oratomic say a word about what their results mean for qday. No timelines. Zero. Nada. That is especially baffling given that the whole point of whitehat quantum cryptanalysis is to inform qday estimations and help the general public make good decisions.

So let me attempt to partially fill the silence, similarly to what Scott Aaronson did in his April 29 post. Given everything I know, including scary non-public information, I now put the odds of qday by 2032 at 50%. 10% by 2030.

Anecdotally, the US government has its own date: 2035. Originating at the NSA and later adopted by NIST, it's when branches of the US government will be disallowed from using quantum-vulnerable cryptography. In plain language: with hindsight, that date is a joke and should be discounted entirely. I don't see how NIST avoids being forced to pull it forward by years.

Part 3: post-quantum cryptography

There are good reasons to sound the alarm today, but please do not panic. Rushing carelessly towards immature post-quantum cryptography is a recipe for disaster. IMO a good target date for migration is 2029, roughly 3.5 years out. 2029 happens to be the date selected by Google, Cloudflare, and the Ethereum Foundation.

These days most of my time goes to safely migrating Ethereum towards post-quantum cryptography as part of the broader lean Ethereum effort. There's a lot to do. We need to rip out and replace BLS signatures at the consensus layer, KZG commitments at the data layer, and ECDSA signatures at the execution layer.

The plan to get there is compelling, and is based on hash-based cryptography. Within the Ethereum Foundation we've developed a Swiss army knife called leanVM (github[.]com/leanEthereum/leanVM) powered by the magic of hash-based SNARKs. Thanks to truly exceptional work by Emile, Thomas, and others, its performance is derisked. Regarding security, leanVM is a jewel, a minimal zkVM crafted for end-to-end formal verification and maximum security.

Want to help? There are two $1M initiatives. First, the Proximity Prize (proximityprize[.]org). Solve a long-standing mathematical conjecture in coding theory, improve hash-based SNARKs, and go home a millionaire. Second, the Poseidon Initiative (poseidon-initiative[.]info), offers $1M for breaking Poseidon, the SNARK-friendly hash function.

[jack @jack]

Encyclical Letter of His Holiness Leo XIV Magnifica Humanitas (15 May 2026) https://t.co/cv0FkCVeBt

[Ebo @EBoKnowss]

Luke Nichols from the Outdoor Boys was a guest speaker at George Mason's Law School commencement this year.

Here's his full speech, which I think is worth watching if you're a 2026 college graduate

[Zeb Evans @DJ_CURFEW]

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.

First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.

Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.

Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.

I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.

THE 100X ORGANIZATION
The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.

Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.

The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.

These roles will evolve. But waiting for that to happen naturally means falling behind now.

The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS
I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.

Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.

AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down.
Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed.
So who do you want orchestrating and reviewing code?

And how do you want your best engineers to spend their time?

If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.

The new world is about enabling your 10x engineers to become 100x.

The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.

I call this the great reckoning of AI coding, and every company will face this soon if not already.

More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.

— THE BUILDERS: 10X PRODUCT MANAGERS
Product management and design roles are merging.

Designers that have customer focus, become more like product managers.

And product managers that have intuition for UX become more like designers.

The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.

The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.

Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.

To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.

Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck.
That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.

— THE SYSTEM MANAGERS
Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.

The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.

You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.

— THE FRONT-LINERS
In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.

This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.

One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.

REWARDING 100X IMPACT
In a world where companies are able to do so much more with less, where does that excess money go?
In our case, much of the savings in this new operating model will flow directly back to those that enabled it.

We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.

You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.

Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.

THE FUTURE
Nearly every company will make changes like these. The ones that do it proactively will define what comes next.

The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.

ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

[Nassim Nicholas Taleb @nntaleb]

@Jaffer22915438 The Roman army rule: action removes fear.

[Ethan Kho @ethanrkho]

"I haven't seen a real new idea in trading in at least 15 years."

Tom Costello (@tcoste110) ran money at Tudor, Moore Capital, and Caxton. Built one of the first NLP-driven equity systems in 2003.

20 years managing capital, never had a down year.

"Comparing what a retail trader does to what a quantitative hedge fund does is like comparing driving a bus on the New Jersey Turnpike to winning a Formula One race."

We cover:
- His hot take: no genuinely new trading idea in 15 years — only better people doing the same things faster
- Why everyone in quant finance is a genius — and why that makes you ordinary, not special
- Crypto is "super smart guys cosplaying at finance" — built for retail, which is exactly why it's the easiest money in finance right now
- Why AGI won't beat the hedge fund industry — all the readily-capturable alpha is already captured
- The status trap: why the path that made Paul Tudor Jones a billionaire won't work for the kid trying to copy it in 2026
- His friend the investment banker who'd quit it all to run a 10-employee ambulance supply company worth $150M
- Why excitement is "wildly overbid" in finance — and why wanting an exciting trading job is itself a disqualifier
- The most honest end of the financial industry — and why the media has it exactly backwards

Thanks so much to Tom for coming on Odds on Open!

Highlights:
00:00 Intro
01:18 Building institutional credibility for early-stage managers
03:01 The Pareto distribution of hedge fund returns
04:25 Applying the Unified Field Theory of Finance to fair value
08:14 Trading against human incentives in a deterministic market
13:54 Why allocators don’t steal alpha from prospective PMs
25:16 Evaluating career edge in quantitative finance for 2026
30:48 Paul Tudor Jones and the art of game selection
33:42 Analyzing the economic viability of starting a new fund
35:16 Identifying common retail pitfalls: Mean reversion and arbitrage
38:55 Why there hasn't been a new trading idea in 15 years
50:33 Managing tail risk: Physics vs. deterministic financial distributions
59:10 Career pathing for PMs after a fund blow-up
1:07:53 SBF and FTX: Credibility vs. the "Founder-Genius" archetype
1:13:44 Establishing proof-of-concept through audited multi-year returns