Ryan Tansom retweeted
Play stupid games (Keynesian), win stupid prizes. Deck chairs on the Titanic….
The Nobel Prize for economics has been awarded to Robert E Hall and Michael Woodford, for their work on the 'microeconomic foundations of macroeconomic stabilisation'. Follow our live blog for more: ft.trib.al/sZ0k4IA
Ryan Tansom retweeted
I never understood people who are perpetually pessimistic about everything.
It must be such an unhappy approach to life.
Ryan Tansom retweeted
Private equity is creating a price umbrella for new small business entrepreneurs
Already seeing this w/my sons & their friends in skilled trades & skilled service biz's
Start biz's that pvt equity has hiked prices on, make bank.
"Your margin is my opportunity" - Jeff Bezos
@soclose2me
My sister's longtime dentist practice got bought out by a private equity-backed dental group four months ago.
Same office. Same hygienists. Same chairs. Zero new equipment.
Last week they sent the new fee schedule for anyone with insurance.
A routine cleaning that used to run $120 is now billed at $310, with the group quietly dropping several insurance plans they used to accept.
When patients asked why, the new regional manager gave a scripted line about "aligning with market standards."
Private equity figured out the same trick everywhere.
They're buying up the things you can't opt out of: dental, veterinary care, urgent care, hospice, because they know you can't just skip your kid's cavity or your dog's surgery.
This isn't inflation. It's leveraged debt getting loaded onto places you have no choice but to keep paying.
Ryan Tansom retweeted
To offend a strong man, tell him a lie, To offend a weak man, tell him the truth
— Marcus Aurelius
Readers added context they thought people might want to know
This quote is falsely attributed to Marcus Aurelius and does not appear in the Meditations or his verified writings.
classics.mit.edu/Antoninus/medi…
stoicshelf.com/posts/fake-mar…
stoichandbook.co/marcus-aureliu…
Ryan Tansom retweeted
A follow-up to last Friday's post.
Last weekend, a few friends came back to me with similar questions, mostly boiling down to this:
Why would Washington keep leaning on the banks to fund this buildout, with long yields at their highest since the early 2000s and AI bubble talk everywhere?
I suspect some of you might be wondering the same thing. The short answer is that there's a much larger game at play here. Let me explain…
The game is called the Red Queen.
In Lewis Carroll's Through the Looking-Glass, the Red Queen tells Alice that in her world you have to run as fast as you can just to stay in the same place. Evolutionary biologists borrowed the idea to describe species locked in an arms race, where nobody gets ahead for long, but whoever stops adapting doesn't survive.
What sent me down this rabbit hole was a paper published in January by two researchers at the Chinese University of Hong Kong and the University of Macau, called The Economics of Digital Intelligence Capital.
Their insight was that AI capital doesn't lose value the same way a factory or a truck does. It loses value every time a competitor pushes the frontier forward. Stop spending for a quarter and everything you've already built is suddenly worth less, just because the other guy didn't stop.
Think of it as two Formula 1 teams. Every race weekend, each team brings new upgrades that make the car a little faster. As long as both keep developing, the race stays close. But if one decides the upgrades are too expensive and skips a few, the gap opens... and skip enough and it's a gap that's almost impossible to close, because the other team is compounding the advantage every single race.
That's Microsoft and Google, OpenAI and Anthropic. Now zoom out and swap the two teams for the US and China. The US was happy to let China become the world's largest factory, because cheap goods made the US consumer economy work.
Letting China become the world's source of intelligence is a completely different proposition, because whoever leads there leads everything downstream of it: productivity, military capability and eventually financial power. Every great power rivalry before this one was fought over land, oil or arsenals. This time the prize is intelligence itself.
That's why the leverage rules were rewritten and why the banks are being positioned to finance the buildout alongside the hyperscalers' own cash flow. And it's why nobody in Washington is going to tighten the taps significantly because asset prices look stretched, not while Beijing is backing its own race just as hard.
When both sides are funding a race neither can quit, liquidity stops being a policy choice and becomes a strategic necessity. Think of it as the defense budget of the 21st century. Win the intelligence race and national security comes with it.
The pushback I hear most often is that every great infrastructure boom ends in a bust, usually with the railroads and the dot-com fiber buildout as exhibit A.
I wrote a much longer piece on exactly this back in May, but here's the short version...
Look at why those busts happened. Both built capacity for demand that didn't exist yet. The track was laid long before there was enough traffic to pay for it, and the fiber went in when only a few hundred million people were online, mostly on dial-up. When demand arrived more slowly than the debt came due, the bet broke.
AI is the inverse. The distribution already exists, with more than 5 billion people carrying a connected device that can reach these models the day they go live. The demand is already here too, with more than $2 trillion of contracted backlog across the big cloud providers and capacity expected to stay tight through 2027. And that's before the largest wave of immigration in all recorded history, except none of the new arrivals are human.
As agents come online, the biggest users of compute won't even be people. They'll be software working on our behalf, consuming compute long after we've put our phones down at night. This isn't capacity in search of customers. It's customers waiting on capacity. There will be a speculative bubble eventually, there always is... but it comes at the end of the cycle, not here.
When people ask what slows this race down, my answer is nothing. That doesn't mean there are no speed bumps. Higher rates make it more expensive. Power shortages delay projects. Financing problems will take out individual players... but even then, the compute doesn't disappear.
If one of the big names went under tomorrow, every rival would be fighting over its data centers, because that's capacity you simply can't buy anywhere else. None of it removes the incentive for everyone else to keep going.
Eventually, I think the two sides reach some kind of truce over compute, because their supply chains are still too intertwined: the US designs most of the leading chips, Taiwan makes them and China processes most of the critical minerals that the whole buildout depends on. Each side holds something the other can't do without. But not yet. Right now, neither side is anywhere near ready to back down.
Just look at Tuesday's White House meeting. Dario Amodei, whose company has been one of the loudest voices calling for the industry to slow down, stood next to Trump and told reporters: "As the president said, whoever wins AI wins." His only caveat was that the US should win safely. Even the people who want to slow AI down aren't prepared to lose the race.
So back to Gundlach's dilemma. Hike or cut is the wrong question, because it assumes someone gets to ease off.
Nobody does. Washington, Beijing, the hyperscalers, the banks... every major player in this race has the same job right now. Keep upgrading the car.
Ryan Tansom retweeted
This video is about the lived experience of Broken Money.
My team and I worked for over a month on this one, I hope you will check it out and share it.
Ryan Tansom retweeted
The most unstoppable combination is fit, skilled, positive, and action-oriented.
Ryan Tansom retweeted
The older I get, the more ridiculous it seems to sacrifice your health to make more money.
Ryan Tansom retweeted
Everything big starts small and focused.
1,000 true fans is step #1, whether you want a $100K per year business or the next Uber.
I’ve seen this with all of my fastest-growing and most successful startups. They start laser-focused on 100 to 1,000 people, niche-ing down as necessary with their messaging and targeting (demographically, geographically, etc.) to get to a manageable and cost-effectively reachable number.
So, you may ask yourself, “Why aim for a mere $100K when I can try to build a billion-dollar business?” Two reasons:
1) Aiming for the latter from the outset often leads to neglecting the high-touch 1,000 true fans who act as your most powerful unpaid marketing force for “crossing the chasm” into the mainstream.
If you don’t build that initial army, you’re likely to fail.
2) Do you really want to build and manage a big company? For most people, it’s not a fun experience; it’s an all-consuming taskmaster. There are certainly ace CEOs who thread the needle and enjoy this roller coaster, but they are outliers.
Read Small Giants by Bo Burlingham for some fantastic examples of companies that choose to be the best rather than the biggest.
Ryan Tansom retweeted
Replying to @RonDeSantis
Ryan Tansom retweeted
Me: buys a house in 2020
Fed: prints $9 trillion more dollars
Also me: “I’m a real estate genius”
Claude can’t create a new spreadsheet without lying. Interested to see how it would make a human if it could edit genes. 🧬
Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out.
It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend.
The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans).
More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains.
In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries.
Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology.
I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.
Ryan Tansom retweeted
Bitcoin derangement syndrome
Imagine publicly talking about Bitcoin when it was $5 in 2011…
and still talking 💩 about it at $80,000, 15 years later.
H/t @AlexesNakamoto
Ryan Tansom retweeted
Replying to @APompliano
US did not grow electricity generation from 2004-2024
Just starting to again
Imagine how high copper, silver, & electrical infrastructure equities will be when we actually get back to where we should be today had we not flatlined for 20 years:
Ryan Tansom retweeted
So 30-50% of your income goes to taxes
and 20-50% of your investment profits,
they're also going to steal 30% of your money saved, and that's only in 6 years.
Ryan Tansom retweeted
JPMORGAN CEO JAMIE DIMON ONCE SAID "IN 10 YEARS, #BITCOIN WILL BE CLOSED DOWN"
THIS WEEK, HIS BANK SAID BTC WILL OUTPERFORM GOLD 🤡




























