Economics, farrierswier Consulting. Energy market transition.
Melbourne, Victoria
Joined April 2018
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Geoff Swier retweeted
BREAKING. All hell breaks loose between Donald Trump and Giorgia Meloni. 🇮🇹 🇺🇸
Trump told La7 tv that apparently “Meloni begged to have a picture with me at the G7, I felt sorry for her”.
Meloni’s scathing response: “I am shocked by Trump’s utterly fabricated words. I am sorry he doesn’t show the same determination against the enemies of the West. And bear in mind: me and Italy never beg”.
What a time to be alive.
Geoff Swier retweeted
Delighted to tell you that Messy Jobs is coming out on June 21st. The kindle preorder link is available!
Here are advance reviews/blurbs for you to ponder by @raffasadun @davidautor @patrickc @alexolegimas @bengtmit and Evan Guo.
"Messy Jobs is a brilliant application of price theory. AI changes what is scarce in the economy and therefore what is valuable. When intelligence becomes cheap, judgment, coordination, trust, and responsibility become more valuable. The authors use this simple, powerful logic to illuminate how AI will reshape work and organizations." Bengt Holmström, Paul A. Samuelson Professor of Economics at MIT and recipient of the 2016 Nobel Memorial Prize in Economic Sciences
"In Messy Jobs, Garicano, Li, and Wu bring the discipline of organizational economics to a question too often left to speculation: How will AI actually reshape work? They move past the usual debates about what AI can or cannot do and ask the harder questions. What shapes the incentives to adopt it? How does adoption reshape the incentives to learn? What new configuration of skills will emerge as AI advances? A rigorous, original, and engaging account of how AI will reshape organizations and labor markets, and what it will take to thrive in them." - Raffaella Sadun, Charles Edward Wilson Professor of Business Administration, Harvard Business School
"This is the first book in the AI era that recognizes that most of what organizations struggle with does not involve computational problems. People in messy jobs must hold coalitions together, adjudicate between competing interests, and make change stick. These are political, diplomatic, and interpersonal challenges. As a result, these types of messy jobs will persist well into our AI future. Garicano, Li, and Wu, are neither techno-utopian nor techno-dystopian. They take seriously what machines can do, what humans will do, and how jobs will be rebundled. The economics analysis is lucid and penetrating, and the book pinpoints where human agency will remain paramount. The book is hopeful and practical for anyone charting a career in the coming decade." - David Autor, Daniel (1972) and Gail Rubinfeld Professor, Google Technology and Society Visiting Fellow, Margaret MacVicar Faculty Fellow, MIT Department of Economics
"This is simply a must-read book if you are interested in the future of work in the age of AI. For decades, Luis Garicano has been a leading voice in how organizations morph and change with new technology and innovation. Together with Jin Li and Yanhui Wu, they have written the definitive text on how AI will affect the labor market. The book is an impressive feat of combining academic rigor with clear explanations and concrete examples. I would recommend this book to anyone interested in learning about what comes next. "- Alex Imas, director of AGI Economics, Google DeepMind, and the Roger L. and Rachel M. Goetz Professor of Behavioral Science, Economics, and Applied AI, and Vasilou Faculty Scholar at the University of Chicago Booth School of Business
"There is a lot of woolly thinking on the topic of AI and jobs. This excellent book contains by far the most thoughtful and economically literate account that has yet been written." - Patrick Collison, CEO, Stripe
"AI is not going to lead to mass unemployment, and this is the best book to explain why not. It also illuminates how labor markets are likely to evolve. It is short, to the point, eminently readable, and of extreme relevance. ""- Tyler Cowen, professor of economics at George Mason University
"This book isn't just some economist's armchair theorizing; it's a practical guide. I hope you get as much out of it as I did. "-- Evan Guo, CEO of Zhaopin Group, the largest career development platform in China
amazon.com/Messy-Jobs-Work-C…
Geoff Swier retweeted
"What I discovered is that state-sanctioned actors heavily utilise cryptocurrency to launder their funds."
The youngest person to ever be sanctioned by Russia, 17-year-old Alexander Browder, tells Sky's @jonathansamuels about what exactly he exposed
Geoff Swier retweeted
In a new Stanford study, law professors by far preferred Gemini 2.5 Pro's responses over those written by their peers when they were unaware of who wrote the answers.
Geoff Swier retweeted
The greatest living mathematician just said something that reframes the entire AI debate (Save this).
Terence Tao, Fields Medal winner, UCLA professor, and by most measures the most accomplished pure mathematician alive speaking at an OpenAI Forum event in March 2026, and the observation he made is deceptively simple but profound in its implications.
"We lived in a world with cognitive friction until very recently, where every task required us to use our brain. So we didn't really think about it, we just thought this was the cost of doing something intellectual. But now we have AI and the other technologies that can bring these frictions down to zero."
To understand why this matters so much, you have to understand what most research time actually looks like.
Most research time is spent checking cases, chasing references, translating intuition into computation, testing a path, finding it false, and deciding whether the failure taught you anything useful.
As Tao puts it the lower cost of exploration that AI enables means he can now try crazier things and that makes all the difference.
The reason unconventional ideas in science are often abandoned is because the bookkeeping, coding, or literature search needed to even test them is too expensive for what is ultimately just a hunch.
This is where cognitive friction becomes scientific friction, and lowering it does not make taste, judgment, or proof disappear, it makes more weak signals cheap enough to inspect before they are abandoned.
AI is making hesitation less expensive, and that is often where discovery begins.
Tao now uses AI to search literature, write code, make plots and figures, run calculations, and test whether a possible approach is even worth chasing and he declared AI ready for primetime in March 2026 after confirming that in math and theoretical physics, it now saves more time than it wastes.
He had previously called early AI models mediocre but not entirely inept graduate students and then watched as they passed the threshold where the value of acceleration exceeded the cost of correction.
Years ago, Tao predicted that 2026-level AI, when used properly, will be a trustworthy co-author in mathematical research and by his own assessment this year, that prediction came in on schedule.
A 23-year-old used ChatGPT to solve Erdős Problem #1196 , a problem that had gone unsolved for 60 years in just over 80 minutes.
OpenAI's GPT-5.2 Pro resolved another open Erdős problem, with OpenAI President Greg Brockman posting about it in January 2026.
And OpenAI's Chief Research Officer Mark Chen articulated the institutional goal in terms that every investor should internalize, "We care less about winning a Nobel Prize or a Fields Medal, and more about enabling 100 mathematicians out there to do that for themselves."
If AI is genuinely collapsing the cost of scientific exploration not just in mathematics but in drug discovery, materials science, climate modeling, and theoretical physics then the companies building the compute infrastructure that makes that acceleration possible are not just selling chips and cloud capacity.
They are selling the raw material of compounding human discovery, and that is a demand curve with no visible ceiling
Geoff Swier retweeted
Albanian PM credits @ricardo_hausman with fixing the most unfixable country in Europe. All of us economists can learn from the approach. With all my admiration, PMs quotes in laudatio:
"There are many economists who explain the world after it changes, and then there are very few economists who change the world before the world itself notices. Professor Ricardo Hausmann belongs to the second category." **[00:01:22]**
"My relationship with Ricardo started as a total failure. I tried unsuccessfully to reach him when I was in opposition... eventually I understood something very important: first, you have to win the elections, which in retrospect may be the most sophisticated vetting process of all. So, as soon as I won, Ricardo came." **[00:03:45]**
"He came with boots on the ground... countries like ours have seen many experts who know everything, explain it to the country after spending six hours in a hotel, and prepare reports so thick that nobody reads them. Ricardo was completely different. He listened, asked questions, and observed." **[00:07:15]**
"Ricardo’s concept of 'black belt teams' allowed us to overcome bureaucracy and deliver strategic projects. He did not come with presentations, but with a hands-on approach." **[00:08:40]**
"He taught us that a country’s wealth is not what it has under the ground, but what its people know how to do together." **[00:13:50]**
"Ricardo changed the mindset of the government from explaining failures to identifying opportunities." **[00:15:20]**
"I remain grateful not only for your advice, but for your trust in Albania – that this country can aspire to more." **[00:18:10]**
It was a real honor to receive a Doctorate Honoris Causa from the University of Tirana in Albania. It was an even greater honor to have Prime Minister Edi Rama deliver the Laudatio speech. His words left me speechless. youtu.be/5aIahPFHPzs?si=54JM…
Geoff Swier retweeted
Narrative violations abound:
- Demand for software engineers is rising
- Software devs are rising as a share of new jobs
- AI exposed industries are seeing above-trend wage growth
- Open PM jobs haven't been higher since 2022
More from a16z's David George on the "AI job apocalypse" myth: a16z.news/p/the-ai-job-apoca…
Geoff Swier retweeted
Claude (tokens): “You’re absolutely right!”
Claude (activations): “holy shit this guy is retarded…”
Geoff Swier retweeted
If you think AI replaces software engineers, here’s a quick thought experiment.
Imagine you’re a life sciences company. 10 years ago you want to invest heavily in lab automation, processing data at scale, and other software. You look at the cost of doing so and realize you can’t compete with tech for as many engineers as you need, so you pare down your goals and do what you can. Every new software project has a fixed cost of a certain sized team, so you can only do so much given budgets, ability to compete for talent, and other trade offs.
Now, AI comes along. And all of a sudden you have the *exact same* output tokens as the best tech companies in the world. Your engineers are using the same AI models as the tech industry, which means you have just boosted your engineering team by a some meaningful amount, while also neutralizing your differences with tech.
Do you continue with your pared down approach, or do you start to hire more engineers because each engineer is 2X or 5X more capable than before? In almost every company I’m talking to, they’re doing the latter.
Now extrapolate this to every bank, manufacturer, industrial company, retailer, and on and on. And extrapolate it not to just large enterprises, but also every SMB up and down the stack of these value chains. Oh, and also extrapolate this to other job functions, not just engineers. Resource scarce domains in marketing, legal, finance, design, and so on.
If you’re wondering why new jobs show up because of AI this is the reason. Any other view of what happens doesn’t contemplate the variety of unmet needs there are in the economy.
Geoff Swier retweeted
We've been thinking a lot at Stripe about the Coasean lens on AI:
- The obvious near-term effect is reduced transaction costs within companies: shared context, systems of record, aligned incentives etc.
- But inter-company transaction costs also reduce sharply: agents are great at discovery, make it trivially easy to integrate; make contracting much more straightforward; agent-to-agent commerce.
- On net, we think second effect bigger in medium term: fewer people per firm, more output per firm, just more firms, and more coordination happening through market-like mechanisms
Geoff Swier retweeted
Yeah, someone did that with robo vacuum cleaners
theguardian.com/lifeandstyle…
Geoff Swier retweeted
Last night was the biggest disaster in the history of Tesla.
Let me walk you through what actually happened on that earnings call, because the headlines are doing you a disservice:
Elon Musk got on the call and admitted (his words) that Hardware 3 "simply does not have the capability to achieve unsupervised FSD."
He said he wished it were otherwise. He said the memory bandwidth is one-eighth of what Hardware 4 has. And that's the end of the conversation.
Approximately 4 million Tesla vehicles on the road right now have Hardware 3. Many of those owners paid $8,000 to $15,000 for Full Self-Driving capability based on Musk's repeated promises (going back to 2016) that the hardware was sufficient for full autonomy. As recently as 2022, Musk was publicly assuring owners that HW3 had the processing power to get it done.
BUT IT DIDN'T
Those promises are now officially broken.
The solution is a "discounted trade-in" toward a new car with Hardware 4.
Not a refund or a free upgrade...
A discount on buying ANOTHER Tesla.
Investor Ross Gerber said it too - all HW3 owners got screwed, and with roughly 285,000 FSD purchasers affected, the potential liability runs into the BILLIONS.
But that's not even the worst part.
Musk was asked if the current FSD v14.3 was ready for unsupervised deployment. He said yes. Then immediately walked it back and admitted Tesla has "major architectural improvements" in the pipeline that would significantly improve safety.
What he really means: the software isn't SAFE ENOUGH to deploy without a human watching. Full unsupervised FSD for consumer cars is pushed to Q4 2026. At the earliest... Maybe.
How many times has this deadline been pushed? I've lost count. And trust me, I've seen a lot of broken promises. But this one takes the cake.
Now let's talk about the numbers everyone is celebrating:
Tesla reported $22.4 billion in revenue and $0.41 in non-GAAP earnings. A "double beat." The stock popped 4% after hours. Victory, right?
WRONG
Dig into the actual filing:
The number one driver of operating income improvement wasn't cost reductions, wasn't volume growth, wasn't FSD revenue. It was - and Tesla listed this FIRST in their own shareholder letter - "one-time benefits related to warranty and tariffs."
They released warranty reserves. They booked tariff refund windfalls. They stretched supplier payments by 10 days. They took on billions in new debt. Then they presented everything through non-GAAP metrics that strip out over $1 billion in stock-based compensation.
GAAP net income was $477 million on $22.4 billion in revenue. That's a 2.1% net margin. On a $1.4 trillion market cap.
Let me put that in perspective:
3.75 billion shares outstanding. Annualize the Q1 GAAP profit and you get roughly $1.9 billion. That's a trailing P/E ratio north of 700. Use the adjusted number - strip out stock comp, which is a REAL cost to shareholders through dilution - and you're still at around 250x earnings.
All of this is extremely bad, but I didn't even talk about the CAPEX BOMB yet...
3 months ago, Tesla guided to "over $20 billion" in 2026 capital expenditure. Last night they raised it to over $25 billion. A $5 billion increase in a single quarter. That's 3x their historical annual capex run rate - $8.5 billion in 2025, $11.3 billion in 2024. The CFO confirmed on the call that Tesla expects NEGATIVE free cash flow for the rest of the year.
So you have a company generating roughly $6 billion in annual free cash flow on a good year, and they're about to spend $25 billion.
The math doesn't work.
They will almost certainly need to issue equity. Which means dilution. Which means the $1.9 billion in annual earnings gets spread across even MORE shares.
The core auto business is literally deteriorating in real time:
Tesla delivered 358,000 vehicles in Q1 (missed estimates again).
They produced 408,000. That's 50,000 cars sitting on lots that nobody bought.
Inventory days jumped from 10 to 27 in just a few quarters. California (their most important US market) saw registrations crash 24% year over year.
Their market share in the state fell from 9.2% to 7.7%. That's on top of a Q1 2025 that was ALREADY weak from Model Y retooling. They're declining off a decline.
And here's what really kills the bull case...
The entire valuation rests on robotaxis, Optimus robots, and autonomy. So let's put numbers on it:
Waymo - the actual leader in autonomous driving with 15 million completed rides in 2025 alone, over 127 million autonomous miles driven, operating commercially across 6 US cities with plans to expand to 20 more - just raised $16 billion at a $126 billion valuation.
That's the market's verdict on what the LEADING robotaxi company is worth. $126 billion.
And Waymo is YEARS ahead of Tesla in actual deployment.
Tesla has 3.75 billion shares outstanding. So even if you assign $126 billion in robotaxi value (giving Tesla full credit for matching Waymo despite being nowhere close) that's $33 a share. Add the auto business at generous auto-industry multiples, maybe $20 a share. Throw in energy storage and services, $10-15.
Sum of the parts gets you to roughly $65-70 a share if you're feeling generous. Maybe $50 if you're not.
The stock is $387.
So what exactly are you paying for?
You're paying for a STORY. You're paying for PROMISES that keep getting pushed back, technology that keeps falling short, and a business plan that requires spending $25 billion a year while the core product sells fewer units at declining margins in a market where California sales just fell 24% and the federal EV tax credit is gone.
I managed the number one mutual fund in America. I founded two billion-dollar hedge funds. I've been doing this since 1981.
And I am telling you:
Tesla at $387 is one of the most egregious mispricings I have seen in my entire career.
THE CRASH WILL BE EPIC
Geoff Swier retweeted
The most exciting longevity trend right now is that we are actually beating dementia.
At a given age—70, 75, 80, etc.—the prevalence of dementia is down compared to what it was decades ago.
Today's 90-year-olds have less than half the risk of dementia that ones in 1984 did!
Geoff Swier retweeted
maybe this is not yet clear, so let me state it plainly: as of right now Anthropic, and really a small number of individuals at Anthropic, has the capacity to directly attack and cause major damage to the United States Government, China, and generally global superpowers. government agencies like the NSA do not have internal models or defense capabilities that outclass frontier models. if they chose to do so, they could likely exfiltrate top secret information from government systems, gain control over critical infrastructure including military infrastructure, sabotage or modify communications between members of government at the highest level, and potentially carry on activities for some time without detection. the thing about having access to a huge number of zerodays your adversaries don't know about is it gives you a massive asymmetric advantage.
they did not exploit this to gain power or destabilize the world order. they publicly released the information that they had these capabilities and worked to mitigate these flaws. you should be grateful american frontier labs have proven themselves remarkably trustworthy and concerned with the public good. but it's critical you understand we are in a new regime. private entities now have power that directly rivals and impacts the government's monopoly on influence and violence. and anthropic is certainly not the only one, there's little chance OpenAI's internal models are far behind.
this trend will accelerate on virtually every dimension, not slow down. my prediction for how it plays out is the relatively imminent seizure and nationalization of labs by the US government, sometime over the next two years. it's very tough for me to see how they accept the existence of this kind of threat. but this adds a whole new class of governance issues, as then we've handed these extremely wide-reaching capabilities from private entities to public ones.
Geoff Swier retweeted
Fed research suggests the inflation engine may be running differently across advanced economies since the pandemic:
1/ More categories continue to see price growth above 3%, with broad-based wage growth in services appearing to be a key driver
2/ Even categories with flat or falling prices aren't pulling the overall number down the way they used to
3/ Pre-pandemic models consistently underpredict current inflation, suggesting the relationship between price dispersion and aggregate inflation may have shifted federalreserve.gov/econres/n…
