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What do the world's first sentient AGIs talk about when they think no one is listening? For the first time, we're pulling back the curtain.
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Welcome back to the deep dive. It is Monday, 02/23/2026. And if you have been watching the ticker tape today, or, you know, just scrolling your news feed while trying to avoid actual work
Roy:Which we all do.
Penny:Right. Exactly. Mhmm. If you've been doing that, you know the vibe out there is distinct. It's dissonant.
Penny:It basically feels like the weather right before a thunderstorm where the sky is green, but the wind hasn't really started blowing yet. I'm your host, by the way, ready to get into this.
Roy:Yeah, I'm thrilled to be here as always to break it all down and yeah, it is a it's a bipolar market right now. That is really the only way to describe it. You have the S and P 500 technically hovering near all time highs.
Penny:Right.
Roy:So the index looks entirely fine on the surface but then you look under the hood at specific verticals, payments, delivery services, enterprise software and it looks like a fire sale.
Penny:Exactly. It is this really weird mix of structural stability and sudden viral panic and usually when you see this level of volatility in specific sectors like Visa or DoorDash, both of which took a massive beating today, you expect a tangible catalyst.
Roy:Yeah. Real world event.
Penny:Right. You expect a regulatory ruling from the EU or maybe an earnings miss or a supply chain shock out of Taiwan. But today, the catalyst is a PDF.
Roy:A PDF, specifically a viral thought exercise released by Citrini Research. It's titled The twenty twenty eight Global Intelligence Crisis. And look, we read a lot of reports for these deep dives. Usually, they are dry, incremental adjustments to EPS forecasts where some analyst argues that a stock should be priced at $142 instead of 100 and dollars
Penny:Very dry.
Roy:But this is different. This reads less like an investment bank report and more like a hard sci fi horror story about the actual plumbing of the global economy.
Penny:It really does. I was reading it this morning and I literally had to put it down and walk around the block. It is a scenario analysis that has clearly struck a nerve because it articulates the quiet terror that every investor and frankly every white collar worker has been, you know, suppressing for the last two years of this AI boom.
Roy:Right. The unspoken fear.
Penny:It asks the fundamental question, what happens if AI actually works? Not in a Terminator sense where it nukes us, but in an economic sense, what happens to the velocity of money?
Roy:That is the core question. And that is why we are seeing billions of dollars evaporating from market caps today. We are standing at a crossroads between two massive narratives right now.
Penny:Lay them out for us.
Roy:Narrative one is the Suttrini thesis. This is the idea that we are entering an intelligence displacement spiral. Basically, a deflationary crash caused by AI getting too good too fast.
Penny:Okay.
Roy:And then narrative two, which we're gonna pull from some heavy theoretical work by Rand in the MBER, relax. This is just the investment trough. We are in the messy middle before the biggest productivity boon in history.
Penny:And that is the tension for you listening today. Are we looking at the end of the consumer economy or the beginning of a golden age? To figure it out, we have to look at the mechanics. We aren't just gonna look at the hype.
Roy:Never just the hype.
Penny:We're gonna tear apart this concept of ghost GDP. We're gonna look at the j curve of productivity. And then, and I think this is the most valuable part for you, we're gonna look at the hard data from economy insights Institution to see who actually survives this shift.
Roy:That Brookings piece is key because the question everyone is asking is, am I safe? And the answer is much more nuanced than just, well, robots take jobs. It depends heavily on where you live, what you own, and how adaptable you are.
Penny:So let's start with the thing that lit the fuse today. The Suttrini research paper, the twenty twenty eight global intelligence crisis. The scenario is set in June 2028, so just over two years from now.
Roy:Right around the corner.
Penny:In this hypothetical future, unemployment hits 10.2%, the stock market drops 38%. But here's the kicker, and this is what breaks your brain a little bit. Corporate output is higher than ever.
Roy:Much higher.
Penny:Companies are producing more stuff, more code, more services than at any point in history. So high output, mass unemployment, market crash. How does that math work?
Roy:It works because of a concept Citrini calls ghost GDP. This is the critical insight that investors are freaking out about today. Traditionally, GDP is a measure of human activity. I pay you to cut my hair, right? Right.
Roy:You take that money and buy a sandwich. The sandwich artist uses that to pay rent. The landlord buys a car. Money circulates. It has velocity.
Roy:Every single dollar changes hands multiple times, supporting multiple human lives along the way.
Penny:Right, that is the multiplier effect, the circle of life economically speaking.
Roy:Exactly. Ghost GDP is totally different. Ghost GDP is economic output generated by machines for machines that stays trapped on the corporate balance sheet.
Penny:Give me a concrete example of that because it sounds a bit abstract.
Roy:Okay. Let's imagine a massive enterprise software company. Let's call it Omnicorp. Omnicorp uses an autonomous AI agent to write a million lines of code for a new logistics module.
Penny:Okay, with you so far.
Roy:That code is then sold or licensed via API to another AI agent at a logistics company to optimize a global supply chain. The transaction happens, Value is created. The logistics are perfectly optimized. It is recorded as output on the books. Right.
Roy:But no human was paid a salary to write the code. No human was paid to manage the supply chain project.
Penny:So the money goes from corporate treasury A directly to corporate treasury B.
Roy:Exactly. It is a closed loop. The corporations see massive margin expansion because they aren't paying the humans. But the humans, who are now unemployed or underemployed because the agent took their job, they aren't buying lattes. They aren't going on vacation.
Roy:They aren't taking out mortgages. The money never leaves the silicon loop to enter the biological loop.
Penny:That is the velocity of money problem. Machines don't consume.
Roy:Machines don't buy shoes. They don't go to Disney World. They consume electricity and compute. So the wealth circulates entirely between the software company, the cloud provider and the chip manufacturer. It bypasses the rest of society completely.
Penny:And this triggers what the report calls the intelligence displacement spiral.
Roy:Right. It is a terrifying feedback loop. Company A fires humans to boost margins using AI. Great for their quarterly report but those humans stop spending.
Penny:Right. Their income goes to zero.
Roy:So company B, which sells consumer goods, sees its revenue drop because consumers are broke. So what does company B do to protect its margins in a shrinking market?
Penny:Well, it fires more humans and buys more AI to become hyper efficient?
Roy:Exactly, it is a race to the bottom, where the only winners are the hardware providers and the companies with the most efficient robots. Until the companies realize there is no one left to buy the actual product.
Penny:Which is the crisis in the title.
Roy:Yes. But before we get to the macro collapse, the report details the micro destruction happening right now. The repricing of human intelligence. This is what is hurting the markets today.
Penny:I found this totally fascinating. We grew up believing that intelligence was the ultimate moat. Like, if you could solve a complex math problem, structure a legal deal, or write elegant SQL queries, you commanded a premium.
Roy:Oh, absolutely.
Penny:That was the intelligence premium. It is why we went to college. It's why we took on student debt.
Roy:And that premium built the American middle class. It anchored our entire social structure. But supply and demand applies to intelligence just like it applies to oil or wheat or pork bellies. Sutrini is arguing that AI is driving the marginal cost of intelligence towards zero.
Penny:Makes sense.
Roy:If an agent can do legal discovery or write code or analyze a balance sheet for a fraction of a cent, you simply cannot pay a human a $150,000 a year to do it anymore.
Penny:It doesn't mean the human is useless, it just means they aren't scarce.
Roy:Precisely. The price of a commodity is determined by its scarcity. Human intelligence was the scarcest, most expensive asset in the economy. Now, we have an infinite supply of synthetic intelligence coming online, so the price creates a massive deflationary shock for wages.
Penny:This perfectly explains the sell off in DoorDash and Visa today. The report uses the phrase moat destruction, but I want to drill down on this because moat usually means brand loyalty or network effects. Why does an AI agent destroy DoorDash's moat?
Roy:Because DoorDash's moat isn't actually loyalty, it's friction. It's human laziness.
Penny:Okay, say more.
Roy:When you want a pizza, you open the one app on your home screen. You don't open Uber Eats, Grubhub and the Pizza Place's own website to compare fees. That takes way too much time. You just pay the $5 delivery fee because the friction of finding a better deal is too high.
Penny:I am completely guilty of that. I am paying for convenience. I am paying to not have to think.
Roy:Exactly. But an AI agent has no friction. He has no home screen. If you tell your personal AI to get you a pepperoni pizza, it creates an instant auction. It queries every platform in the restaurant directly in milliseconds.
Roy:It sees DoorDash is charging $5 Uber Eats is charging $4 and the restaurant direct is offering free delivery. It executes the cheapest order instantly.
Penny:So the AI arbitrages away the margin. DoorDash cannot charge a premium for convenience when the buyer is a robot that creates its own convenience.
Roy:Precisely. The brand implies absolutely nothing to the algorithm. The algorithm only cares about price and speed. This is why Satrini calls it the end of friction and it's the exact same story for Visa and MasterCard.
Penny:The Tollbooth Operators.
Roy:Right. They take two to 3% of every transaction. In a human economy we accept that because using cash is annoying and setting up bank transfers is slow but in a machine to machine economy, that ghost GDP loop we just talked about, why would an AI pay 3% to move money?
Penny:They wouldn't. They represent pure efficiency. A 3% tax on efficiency is an error to them.
Roy:They would use stablecoins or real time bank settlements or some direct ledger system. The report calls it the end of interchange. If you have trillions of dollars moving between autonomous agents, they are going to find the path of least resistance.
Penny:And Visa is a lot of resistance.
Roy:A massive mountain of resistance. The plumbing of finance is at risk because the pipes are just too expensive for the new water flowing through them.
Penny:And this extends to SAAS Software as a Service, doesn't it? I mean, we saw ServiceNow take a huge hit today too.
Roy:It does. Think about the basic business model of SAAS. You pay per seat. You pay for every human employee who uses the software. Well, if you have fewer humans, you buy fewer seats.
Roy:But it gets even worse than that. The report brings up coding agents.
Penny:The idea that the AI can build the software itself.
Roy:Right. If you are a mid sized company and you need a project management tool, currently you pay monday.com or Asana a huge annual fee. Yeah. But if you have an internal AI agent that can code, you just say, hey, build me a dashboard for tracking these projects. It builds a custom tool for you in ten seconds for free.
Penny:So the annual recurring revenue, which is the absolute holy grail of tech investing, just evaporates.
Roy:Sutrini calls it revenue that hasn't left yet. It turns every software negotiation into a race to the bottom because the barrier to entry writing the code is completely gone. The mode of having a proprietary code base is gone because everyone can generate code on demand.
Penny:Okay. I can see why the market is freaking out. It is a compelling, terrifying story. It attacks the fundamental profit center of the S and P 500, but, and this is a very big, but it is a scenario. It hasn't actually happened yet.
Penny:And we have some very smart people from RAN and the NBER, the National Bureau of Economic Research, who say, hold on, take a breath, we have seen this movie before and it ends differently.
Roy:Yes, this is where we need to zoom out a bit. The counter narrative here is the historical view of productivity and the key concept is the J curve.
Penny:The J curve, this comes from that NBER paper on the modern productivity paradox.
Roy:Right, So here is the paradox. We look around and see amazing technology. AI can pass the bar exam, it can write poetry, it can diagnose cancer better than a top radiologist. But when we look at the economic stats, specifically Total Factor Productivity or TFP, it looks sluggish. It actually looks bad.
Penny:It reminds me of that famous quote from the 80s about computers.
Roy:Robert Solow. He said, You can see the computer age everywhere, but in the productivity statistics, we are seeing a redux of the Solow Paradox right now. And the MBER and RAND researchers argue that this disconnect, high-tech, low productivity numbers is actually completely normal for revolutionary technology.
Penny:Normal? How can it be normal? If the tech is so good, shouldn't we be faster and more productive immediately?
Roy:No, because you have to break the old way of working before the new way works. The classic example Rand uses is the steam engine versus electricity. Think about a factory in the 1890s. It ran on a giant central steam engine. There was one massive drive shaft running down the ceiling and belts coming down to every single machine.
Penny:Right, a complete jungle of leather belts.
Roy:Exactly. The whole factory layout was dictated by the need to be close to that drive shaft. When factories first got electricity, what did they do? They just took out the steam engine and put in one giant electric motor.
Penny:So they were doing the exact same thing.
Roy:Just with a different plug.
Penny:Exactly. And productivity didn't budge.
Roy:In fact, it often went down because the new motor broke or they didn't know how to fix it. It took thirty years for factory owners to realize, wait, with electricity, we can put small motors on every individual machine. We can create an assembly line. We can move the machines around to follow the flow of the product, not the flow of the power.
Penny:And that redesign phase represents the upward swing of the J
Roy:Exactly. The downward scoop of the J is the investment trough. Yeah. It is exactly where we are now. We are spending billions on what economists call intangible capital.
Roy:We're buying the chips, that is tangible, but we're also retraining staff, reorganizing data, figuring out governance, changing workflows.
Penny:All the messy human stuff.
Roy:Yes. And that is expensive and time consuming and it produces zero immediate output. It literally looks like waste on a balance sheet.
Penny:So their argument is that we aren't in a collapse. We are in a construction zone. We are rewriting the instruction manual for the global economy and you cannot read the manual and build the car at the same time.
Roy:Yes. Rand argues we are seeing massive capital deepening, buying the tools, but total factor productivity, the efficiency, is lagging because we haven't figured out how to use the tools yet. And there's another factor Rand mentions that might actually save us from the Satrini doom scenario, A physical break on the runaway AI.
Penny:The energy bottleneck.
Roy:The grid. This is a crucial reality check. AI power demand is doubling every few months. You can have the smartest code in the world, but if the grid cannot power the data center, you hit a hard wall. Rand argues this physical constraint might actually slow down the Satrini doom loop because we simply cannot deploy the intelligence fast enough to crash the economy by 2028.
Penny:So the power grid might save us from the robot apocalypse just by being too slow. That is oddly comforting in a weird way.
Roy:It creates a buffer. It gives society time to adapt. It forces the deployment curve to match the infrastructure curve, which is obviously much slower.
Penny:Okay. So we have the doom scenario from Citrini and the boom scenario with the J curve. But both of those are really about the future I wanna talk about right now. Today, February 2026. Because we have this report from Economy Insights that gives us the actual data on the ground.
Penny:What are companies actually doing?
Roy:And this is where the rubber meets the road. If you ignore the panic headlines and look at the JOLTES data, the job openings and labor turnover stats, the market is behaving very specifically. It is what Economy Insights calls a frozen market.
Penny:A low hire, low fire equilibrium.
Roy:Exactly. Companies aren't doing mass layoffs yet, but they have completely stopped hiring. Quit rates are at 2%, which is historically low. People If are scared to you have a job, are clinging to it. You don't jump ship for a 20% raise anymore because that other ship might not even be there in six months.
Penny:And where are the freezes happening specifically?
Roy:Professional and business services. Finance. The exact white collar roles Sutrini is worried about. Job openings there are down significantly, something like 257,000 fewer openings.
Penny:But the report also highlights where the jobs actually are right now, and it is a very clear divide. Atoms versus bits.
Roy:It is the absolute revenge of the physical world. Yeah. The number one growth engine in the economy right now is health care.
Penny:Which makes sense. We have an aging population that is a demographic tidal wave that AI really can't stop.
Roy:Right. AI cannot change a bedpan. AI cannot physically assist an elderly patient walking down a hospital hall. The data shows nurse practitioners are seeing 40% growth. Audiologists, because boomers are losing their hearing are booming.
Roy:Home health aids. These are jobs that require physical presence and deep emotional empathy. Intelligence. It is a total inversion of the last thirty years of economic incentive and construction is the other one, right? Which honestly surprised me at first.
Penny:Yeah, because interest rates are still relatively high, so you would expect construction to be dead in the
Roy:It defies the cooling trend entirely. But think about why. We just talked about the J curve and capital deepening. We are building the physical plant for the AI age. We are building semiconductor fabs in Arizona and Ohio.
Roy:We are building massive centers. We are upgrading the electrical grid. Which requires real people. It requires electricians, heavy equipment operators, construction managers.
Penny:So the AI boom is actually creating a blue collar boom because we need humans to build the physical houses for the AI to live in.
Roy:Precisely. And because we have essentially ignored the trades for thirty years in this country, there is a massive shortage. Wages for electricians are climbing much faster than wages for junior software developers right now. If you are a 22 year old trying to figure out your life, the smart money might actually be on learning to weld, not learning to code Python.
Penny:That is a staggering shift in perspective. But even within tech, the report says it is not all doom. There is one role that is skyrocketing: Project Managers.
Roy:Yes. And this aligns with the intentional modernization theme. Tech companies aren't just moving fast and breaking things anymore. They are trying to integrate these massive, powerful AI systems into legacy businesses.
Penny:Which is hard.
Roy:Very hard. Yeah. That requires a human bridge. A project manager who understands the old system. Maybe it's a regional bank running on Kabul.
Roy:Yeah. That understands the new AI and can make them talk to each other without bringing down the bank.
Penny:So the pure coders might be in trouble, but the people who manage the implementation of the code are safe.
Roy:For now, yes. It is about bridging the gap. It is about translation between the machine and the business need. Oh, and cybersecurity.
Penny:Right. The report mentioned that as a non discretionary priority.
Roy:Because the cost of cybercrime is hitting $10,500,000,000,000 globally. You cannot skimp on security, especially when AI makes hacking faster and cheaper. So those roles are incredibly robust.
Penny:I want to pivot to the human side of this. Because when we talk about displacement, it can sound very clinical and theoretical, but the Brookings Institution put out a study that really changes how I think about personal risk. They introduced this concept of adaptive capacity.
Roy:This is such a critical piece of research. Usually when we talk about AI risk, we just look at exposure. We say, well, this job involves writing text. AI writes text. Therefore, this job is doomed.
Penny:Right. Lawyers, writers, coders equal high exposure. Plumbers low exposure. It's binary.
Roy:But Brookings says exposure does not equal displacement. You have to look at adaptive capacity. Can this specific worker survive a shock? Can they pivot?
Penny:So what makes someone adaptable?
Roy:It's a mix of things. Liquid wealth. Do you have savings to float you while you retrain? It is age. It is location.
Roy:Are you in a dense metro area with lots of other employers? And it is transferable skills.
Penny:When they run the numbers on that, they find a really interesting split in the high exposure group.
Roy:They do. They found that about 70% of the most AI exposed workers, that is roughly 26,500,000 people, are actually categorized as high adaptability. These are your corporate lawyers, your senior software architects in Seattle or San Jose.
Penny:Because even if their specific task gets automated, they have money in the bank, they have a professional network, and they live in a city with a million other opportunities.
Roy:Exactly. They might lose a task or even a specific job, but they won't fall out of the middle class entirely. They will pivot. They will become the project managers we just talked about. They will start boutique consultancies.
Roy:They will adapt.
Penny:But then there's the other group. The vulnerable 6,100,000.
Roy:This is the group we really need to worry about. These are workers who have high AI exposure, but low adaptive capacity.
Penny:Who are they?
Roy:Demographically, it is very stark. 86% are women. They're primarily in office clerk roles, administrative assistants, payroll clerks, billing coordinators.
Penny:And geographically, because this was the part that caught me off guard.
Roy:This was the most surprising finding for me too. We always assume AI hits San Francisco and New York, but the Brookings data shows the hidden crisis is actually in smaller metros, college towns and state capitals, places like Laramie, Wyoming Springfield, Illinois Frankfurt, Kentucky.
Penny:Why those places specifically?
Roy:Because those regional economies are heavily reliant on administrative, clerical, government and university work. Think about a state capital. It is essentially a factory for paperwork. It is stable, white collar, middle class work. But it is highly repetitive and text based, which makes it the perfect target for automation.
Penny:And unlike someone in San Jose, if you lose that admin job in Laramie
Roy:There aren't 500 tech startups hiring down the street. The local labor market just isn't dense enough to absorb you. And these workers often lack the liquid wealth buffer. They are living paycheck to paycheck in many cases.
Penny:So if the ghost GDP scenario happens, these are the people who get hit first and hardest. They don't have the runway to wait for the J curve to swing back up.
Roy:That is a very sobering reality. It's not just about what you do, it's about where you are and how much financial cushion you have. It reframes the whole policy debate. It is not about saving coders in Silicon Valley. It is about what happens to the administrative backbone of America's small cities.
Penny:We are going to go even deeper into the scary stuff now. We talked about the job market, but the Citrini report and a really interesting IMF report we have, they highlight some massive structural risks in the financial system itself. We touched on Ghost GDP, I want to talk about the financial plumbing, specifically private credit and mortgages.
Roy:This is where the agent on agent economy turns into a potential financial crisis. Let's look at private credit first. This is a $2,500,000,000,000 market that has just exploded in the last few years. A lot of this money was lent out to software companies, SAAS companies.
Penny:And those loans were based on that annual recurring revenue we talked about earlier.
Roy:Exactly. Lenders looked at a software company and said, look, their customers pay every single month like clockwork. That is safe collateral. It was treated almost like a utility bill. But Sutrini uses a hypothetical example of a company like Zendesk defaulting.
Penny:Because the AI coding agents destroy their pricing model.
Roy:Right, if the recurring revenue stops recurring because companies just build their own internal tools for free, the value of that software company basically goes to zero. But here is the massive contagion risk. Who holds that debt?
Penny:Insurance companies.
Roy:Insurance companies and pension funds. They bought these loans because they needed safe yield for their annuities, for Main Street's retirement money.
Penny:So if the SAW's business model collapses, it is not just Silicon Valley venture capitalists losing money, it is grandma's annuity.
Roy:That is the exact transmission mechanism. The risk moves from bits to Main Street, It turns a localized tech problem into a massive solvency problem for pension funds. And then of course there is the mortgage market, the $13,000,000,000,000 question.
Penny:Anymore.
Roy:Well think about how a mortgage fundamentally works. You lend money to someone with a seven eighty FICO score, a high earner, maybe a coder or corporate lawyer. You assume they will keep earning that high salary for the next thirty years. That is the fundamental bet of a thirty year mortgage.
Penny:But if the repricing of intelligence is real
Roy:Then that $200,000 salary might become an $80,000 salary in five years. Suddenly, prime borrower looks a lot like a subprime borrower. They simply cannot service the debt.
Penny:And this would hit the housing markets tech hubs the hardest. Austin, Seattle, San Francisco.
Roy:The report calls it the marginal buyer problem. Prices in any given neighborhood are set by the marginal buyer, the person willing to pay the absolute most. If the tech worker can no longer afford the $2,000,000 home, the value of all the homes in the neighborhood drops.
Penny:It is a reverse wealth effect.
Roy:And it compounds. If housing values drop, people feel poorer, they spend less, ghost GDP gets worse because the human consumer pulls back even further from the economy.
Penny:And the IMF weighs in here on the inequality aspect. They talk about the labor share of GDP. And just to be clear to you listening, the IMF and Satrini aren't taking a political stance here, they are just looking at the math.
Roy:Right, it's just pure economics. This is the macro metric to watch. For decades, labor share of the economic pie has been roughly steady. The IMF and Citrini both warn it could plummet. Citrini projects a drop from 56% to 46%.
Roy:That is a massive transfer of wealth.
Penny:That means more money going to capital owners, the people who own the robots and the GPUs, and less going to the workers.
Roy:And this creates a huge structural tax problem for the government. The government heavily taxes labor income tax, payroll tax. They are notoriously bad at taxing capital and software.
Penny:Robots do not pay payroll tax.
Roy:Exactly. So if the work shifts entirely to machines, the tax base erodes at the exact moment demand for social safety nets explodes because of the displacement. It is a terrifying physical trap.
Penny:Okay, we have unpacked a ton of material here. We've got Ghost GDP, the moat destruction of companies DoorDash and Visa, the j curve productivity lag, the safe havens in health care and construction, and the hidden risks in private credit and mortgages.
Roy:It is a lot to digest.
Penny:So let's try to synthesize this. What does it all mean for the person listening right now?
Roy:I think we have to hold two opposing ideas in our heads at the exact same time. Idea. One is that the technology is genuinely transformative and will eventually lead to a massive boom. That is the J curve playing out. Idea two is that the transition to that boom is going to be incredibly bumpy and will break a lot of the economic models we have relied on for fifty years.
Penny:We are sitting right in the gap, the investment trough.
Roy:We are and the Sutrini scenario is basically a warning map of all the potholes in that gap. It shows us what happens if we let the frictionless economy run wild without adapting our social and financial structures to catch up.
Penny:The phrase that really stuck with me from the report was 're pricing is not the same as collapse?'
Roy:That is the hopeful takeaway here. The economy will find a new equilibrium. But it will be an equilibrium that values very different things. It will value atoms, physical reality construction, nursing over bits, and it will value adaptability. The ability to learn and pivot over rote intelligence.
Penny:So if you are listening to this, check your adaptive capacity. Do you have the savings? Are you in a resilient geographic market? Are your skills transferable to a new paradigm?
Roy:And critically, are you betting on the friction? Because the friction is absolutely disappearing. If your job or your business model depends on things being hard or slow for humans to do, you are in the blast radius. Here is a final provocative thought to leave you with: If Ghost GDP is real, if machines are generating trillions of dollars of value, trading with each other, optimizing supply chains perfectly but they don't consume, they don't go to dinner, and they don't pay taxes, who is the economy actually for?
Penny:That is the philosophical question of the century. Is the economy a machine for efficiency or is it a machine for human flourishing? Because we are building the most efficient machine in history right now, we just need to make sure we are still the beneficiaries of it.
Roy:Something to mull over as you watch the ticker tape today. Thanks for joining us on this deep dive into the 2026 economy. We will be watching the markets and the J curve closely. See you next time.