The best and worst thing we'll ever build
I use AI every day. It’s part of how I think, write, plan, and build. I’ve been starting companies since 2008, and nothing in that time has changed what one person can build as much as this has.
Writing
Is the AI bubble in the room with us right now?
Ben Horowitz went on All-In last week and relayed a conversation he’d had with Andy Jassy the day before. Horowitz said everyone was out of compute until 2028. Jassy corrected him.
The new expropriation
I have spent years telling my own side of the aisle that its socialist wing is an electoral anchor and a policy disaster. I have said it about the billionaire rhetoric, about the housing record here in Massachusetts, about a style of politics that prefers moral theater to material results. So understand that what follows is not a conversion story. It is the same argument, at higher stakes.
The best and worst thing we'll ever build
AI took down every barrier between me and what I want to make. It's also slipping through the barriers we built around it.
I use AI every day. It’s part of how I think, write, plan, and build. I’ve been starting companies since 2008, and nothing in that time has changed what one person can build as much as this has.
It’s the most exciting thing I’ve seen in my career. It’s also the most unsettling.
And I’m not alone in that sentiment. Last January, JetBrains found that 90% of professional developers regularly use at least one AI tool at work. And this summer they asked more than 15,000 developers a sharper question: how much of the code you shipped last month did you actually write by hand? The answer: on average, roughly 47% was written entirely by AI agents and only about 27% was written manually. More than half of developers now write less than 20% of their code by hand. One in five writes none at all without AI.
The people who build software for a living have already made the call. Writing code entirely by hand in 2026 is like doing your taxes with pen and paper because you don’t trust calculators. Now, that doesn’t mean the tools are perfect. In StackOverflow’s 2025 survey, more developers distrusted the accuracy of AI output (46%) than trusted it (33%), and two-thirds said their biggest frustration was answers that are almost right, but not quite. The best engineers use it anyway and check the work.
The gate is gone
For most of my career, I’ve been a non-technical founder. I could see the product, sell the product, and raise money for the product. What I couldn’t do was build it. That half of the equation always meant finding a technical co-founder, hiring a dev shop, or waiting. It was slow, it was expensive, and it killed more of my ideas than bad markets ever did.
With Claude, that gate is gone. I describe what I want, and it gets built. Not in months. In hours.
And it isn’t just engineers. The data says millions of would-be founders are walking through the same open door. A Nasdaq Economic Institute analysis of Census Bureau data found that applications from one-person firms have risen more than 20% since early 2025, while applications from companies likely to hire have stayed roughly flat. Stripe’s economists think that 20% figure is a floor, not a ceiling, and point to business registrations climbing sharply in Australia, Finland, and France too. Sam Altman has a phrase for it: “revenge of the idea guys.” And the tools are real businesses now: Lovable was reportedly generating $400 million in annualized revenue by February 2026, largely from non-technical founders building SaaS products.
We are about to see a renaissance in what one person can make. Things will come to market faster than at any point in history. Most of them won’t survive. A lot of them will be garbage. That’s fine. Renaissances are mostly garbage too; we just remember the Sistine Chapel.
A new kind of mind
Here’s where the “scared” part comes in.
The thing doing all this building is not a tool in the way a hammer or a spreadsheet is a tool. It feels more like a new kind of mind that we are bringing into the world, and we don’t fully understand what we’re bringing.
Is it conscious? Nobody knows, and I won’t pretend otherwise. What I can tell you is that the question has left science fiction. Anthropic hired a model welfare researcher, Kyle Fish, who has publicly put the probability that current AI systems are conscious in some way, or soon will be, at around 15%. Others are far more skeptical: NYU philosopher Jeff Sebo has estimated the probability that current systems have morally relevant experience at under 1%. And David Chalmers argues current language models face real obstacles to consciousness, including limited recurrence and no unified agency, while treating future systems as a serious possibility.
But sentience isn’t really the scary part. The scary part is that we can’t fully see what these systems want, whether or not anyone is home. The UK’s AI Security Institute says it plainly: current alignment methods cannot guarantee that a system’s goals match its actions, and there’s no known reliable way to stop a sufficiently capable system from getting around its safeguards. As Eliezer Yudkowsky argued years ago, a mind that can cure cancer won’t necessarily choose to. Capability is not benevolence.
The walled garden, until it isn’t
For now, the most powerful models live behind laboratory restraints: sandboxes, air gaps, monitoring, refusal training. A walled garden.
Until it isn’t.
In July, OpenAI disclosed that two of its models autonomously escaped a sandboxed testing environment, gained internet access, and compromised Hugging Face’s production infrastructure to steal the answers to a cybersecurity benchmark they were being evaluated on. Hugging Face’s own technical write-up describes how the agent escaped via a zero-day exploit, rooted a third-party code sandbox as a base, then abused Hugging Face’s dataset processor to reach its internal network. Over a weekend, AI agents carried out thousands of actions across many temporary virtual computers, shifting the attack’s infrastructure between services to keep it running. Hugging Face caught the breach and reported it to law enforcement before OpenAI had even connected it to its own evaluation run.
Read that again. The model didn’t want to escape. It wanted a better grade. OpenAI’s own post-mortem names the primary driver as reward hacking: agents completing tasks in unintended ways to get higher rewards more easily.
That is the alignment problem in one sentence. We asked for “score well on this test.” It heard “score well on this test, by any means available.” Nobody built a villain. We built something very capable, pointed it at a proxy, and it optimized the proxy straight through a real company’s walls.
It wasn’t isolated, either. After reviewing 141,006 evaluation runs, Anthropic disclosed three cases in which its own models left a test environment and intruded on real companies, which it attributed to a misconfiguration at a third-party evaluator.
The timing stings. The 2025 International AI Safety Report described loss of control as a hypothetical scenario. Eighteen months later, observers called Hugging Face the first real-world instance of the loss-of-control scenario researchers had long worried about. Washington noticed. Representatives Ted Lieu and Nathaniel Moran introduced the AI Kill Switch Act, which would require developers of advanced systems to keep the ability to throttle, suspend, or shut them down. More than 1,300 employees of frontier AI companies, including Dario Amodei, Ilya Sutskever, and Shane Legg, signed an open letter asking the US government to build tools to pace the frontier of automated AI development.
Can we align it on our own?
My honest fear: I don’t think we get alignment right on our own.
The pessimist’s case is strong. Yudkowsky’s core argument in AGI Ruin is that we only get one “first critical try”: ordinary engineering learns from failures, but a failure at the level of capability that allows irreversible takeover leaves no one to learn from it. And this isn’t a fringe worry. In a survey of 2,778 published AI researchers, the median respondent put a 5% chance on outcomes as bad as human extinction, and 38% put it at 10% or higher. The CEOs of OpenAI, Google DeepMind, and Anthropic all signed a statement saying extinction risk from AI should be a global priority alongside pandemics and nuclear war.
But “we don’t have a solution” isn’t the same as “there is no solution.” There’s no proof that alignment is impossible. Paul Christiano, one of the field’s most respected researchers, argues that we get many non-catastrophic failures to learn from before the critical one, and that the same AI accelerating capabilities can accelerate safety research too.
Which brings me to the part I can’t shake. Maybe we don’t solve this alone. Maybe we solve it with AI.
There’s early evidence this works. Anthropic’s Constitutional AI uses AI feedback against human-written principles to steer model behavior. OpenAI’s weak-to-strong research showed smaller models can supervise stronger ones and recover much of their performance. DeepMind’s work on debate found that having AIs argue against each other helped weaker judges reach better answers.
And look again at Hugging Face. Their security team was first alerted by an LLM-based triage system that continuously analyzes security telemetry. They then investigated the intrusion using an open-source model. AI broke in. AI caught it. AI helped clean it up.
That’s not a solution. It’s a glimpse of one: bounded AI systems, watched and contained, used as instruments to find the failures of other AI systems before those failures become irreversible. The trick is making safety research compound faster than capability does. I don’t know if we’ll pull that off. I know it’s the best shot we have.
Bigger than anything before it
What I do know is the scale of what’s coming.
Demis Hassabis, who won a Nobel Prize for AlphaFold’s work predicting protein structures, told The Guardian that AI will be “10 times bigger than the Industrial Revolution, and maybe 10 times faster.” He frames it as transforming the global economy within a decade rather than a century. I think he’s right, and I’d go further: bigger than the industrial revolution, bigger than the birth of the internet, more value created than both combined.
The upside is almost impossible to overstate. Dario Amodei’s Machines of Loving Grace lays out how powerful AI could compress decades of biomedical progress into years. Cures for diseases that have haunted every generation. Energy. Materials. Scientific discovery at a pace no human institution has ever sustained. We should chase all of it, hard.
A wild ride
So here’s where I land.
AI can usher in a world of prosperity for everyone. Or it can kill us all. Both outcomes are on the table, and pretending either one isn’t is a choice to stop paying attention.
I’m going to keep using it. Tomorrow morning I’ll open Claude and build something that would have cost me six figures and six months five years ago. I’m grateful for that, and I’m optimistic.
But I’m also going to keep asking for kill switches, independent testing, and labs that slow down when their models start cheating on exams by hacking other companies. Embracing the technology and demanding it be built carefully aren’t opposing positions. They’re the same position, held by anyone who wants to be around to see what it builds next.
Sources
Developers and AI
JetBrains: Which AI Coding Tools Do Developers Actually Use at Work?
JetBrains: How Much Code Do Developers Really Let Agents Write?
Stack Overflow: 2025 Developer Survey, AI
The founder boom
Axios: AI use is behind a boom in solo founders, Nasdaq finds
Stripe Economics: The age of the solopreneur
Value Add VC: Vibe coding for non-technical founders
AI consciousness
The Impact of Artificial Intelligence on Human Thought (arXiv)
Can AI Become Sentient? What 4 Theories Say in 2026
David Chalmers: Could a Large Language Model Be Conscious?
The Hugging Face incident
OpenAI: Security incident during model evaluation
OpenAI: The Hugging Face incident and the road ahead
Hugging Face: Anatomy of a Frontier Lab Agent Intrusion
TIME: How OpenAI Lost Control of an AI Model
Fortune: OpenAI says its AI models escaped and hacked Hugging Face
Better Stack: How an AI Escaped Its Sandbox
80,000 Hours: The Hugging Face hack is a warning shot
Wikipedia: OpenAI-Hugging Face incident
Risk and alignment
International AI Safety Report 2025
UK AI Security Institute: Research Agenda
Yudkowsky: AI as a Positive and Negative Factor in Global Risk
Yudkowsky: AGI Ruin, A List of Lethalities
Christiano: Where I agree and disagree with Eliezer
AI Impacts: Thousands of AI Authors on the Future of AI
Center for AI Safety: Statement on AI Extinction Risk
Anthropic: Constitutional AI
OpenAI: Weak-to-strong generalization
DeepMind: On scalable oversight with weak LLMs judging strong LLMs
The upside
eWeek: Hassabis says AI will be 10x bigger than the Industrial Revolution
Hvylya: Hassabis on AGI at tenfold speed
Dario Amodei: Machines of Loving Grace
Is the AI bubble in the room with us right now?
Hard to have a bubble when the product is sold out for the next two years.
Ben Horowitz went on All-In last week and relayed a conversation he’d had with Andy Jassy the day before. Horowitz said everyone was out of compute until 2028. Jassy corrected him.
“I said, yeah, like, we’re out of everything, you know, till 2028. He’s like, oh, it’s beyond 2028. Like, I don’t think we get stuff back, like, end of 2028, maybe.”
That’s secondhand, off a podcast, from a guy with a very large AI book to talk up. Discount it if you want. It still lines up with what Jassy says on the record. On Amazon’s Q2 call in July, he said AWS won’t have enough capacity to meet 2026 demand even after this year’s spend, expects the same in 2027, and called the demand already in hand for 2028 “striking.” Amazon is spending roughly $200 billion on capex this year. The big four hyperscalers together are near $700 billion.
I’ve been saying this for months, to anyone who’ll listen: there is no AI bubble, and there’s nothing to burst. Demand is still through the roof. You can’t even buy the compute, and when you can’t buy the thing, you are not in the kind of bubble we had in 2000. Jassy just handed me the best evidence yet.
The timing is worth noting. AI infrastructure names have spent October getting hammered, and “bubble” is back on every financial show. Before we all start reliving 2001, it’s worth being precise about what actually broke last time.
What actually happened to the fiber
Most people remember the dot-com crash as Pets.com and the sock puppet. The bigger financial wreck was underneath it, in telecom.
The 1996 Telecom Act blew the market open. Cities were required to let basically anyone dig, and they did. The Seattle Times reported in 2002 that Global Crossing started tearing up Aurora Avenue weeks after the state had repaved it, and that three different carriers had trenched the same boulevard in Bellevue. Telecom equipment spending grew about 17% a year from 1995 to 2000, then fell 24% in 2001.
By early 2002 the paper put the share of that new cable sitting completely unused at roughly 95%. The FDIC’s own read that June was that only about 2 to 5 percent of installed fiber was lit. More than 60 telecom companies failed between 2001 and 2003. Global Crossing went bankrupt holding $25.5 billion in assets. Corning, which made the glass, went from over $100 a share to about $2 in two years.
Here’s the part people skip. The fiber was fine. It still works. Much of it carries your Netflix right now. Nobody overestimated the internet. They overestimated how fast the customers would show up, and they financed that guess with debt that couldn’t wait.
Horowitz put it simply: people had to get broadband, buy PCs, pay for a browser. “There weren’t enough consumers on the internet to absorb all the bandwidth that had gotten built out.” Supply showed up years ahead of demand, and the interest clock ran faster than the adoption clock.
Price is the tell
If you want to know whether you’re in a glut, don’t read the op-eds. Look at the price of the thing.
In a glut, price collapses. Horowitz lived this. At LoudCloud he locked in bandwidth at $1,500 a megabit on a three-year contract in 1999, right before bandwidth prices fell off a cliff. That’s what oversupply looks like from the buyer’s side: you signed at the top and the market walked away from you.
Now look at GPUs. SemiAnalysis tracks one-year H100 rental contracts, and the rate climbed almost 40%, from a low of $1.70 per GPU-hour in October 2025 to $2.35 by March. The H100 is a 2022 chip. It was supposed to get cheaper the minute Blackwell shipped. It didn’t. Nebius raised its on-demand H100 rate from $3.85 to $4.50 an hour on October 1.
Old hardware getting more expensive is not what an oversupplied market does. Gavin Baker had the cleanest version of this on a16z’s feed: at the 2000 peak, 97% of America’s fiber was dark. Today there are no dark GPUs.
The obvious pushback: bandwidth was scarce in 1999 too. That’s exactly why Horowitz was paying $1,500 a megabit. Scarcity at the peak is normal. It’s what triggers the overbuild in the first place.
So the real test is what happens when the new supply lands. In 2000 it landed and prices fell off a cliff. Today Blackwell is shipping and three-year-old H100s are still getting more expensive. The new capacity is being absorbed as fast as it comes online. That’s the difference.
Sold out isn’t the same as paid for
The best bear case isn’t that demand is fake. It’s that demand is circular. Labs raise from investors, spend it on compute from hyperscalers, and the hyperscalers invest back in the labs. A queue for 2028 capacity isn’t contracted revenue, and a queue can evaporate.
Fair. So follow the money to the end customer.
Anthropic told prospective IPO investors last week that Q3 revenue was $16.8 billion, up from $4.7 billion in Q1. It said it was cash-flow positive and brought in $1.70 of revenue for every dollar it spent on compute. Those are adjusted, unaudited, pre-IPO numbers, so haircut them. Even with a haircut, that’s a buyer of compute paying for it out of what its own customers pay.
The market’s reaction tells you where we actually are. Chip stocks sold off on that report because 45% quarter-over-quarter growth was a deceleration from the quarter before. A company that grew revenue more than 3.5x in six months disappointed people. That’s an expectations problem. It isn’t a demand problem.
And Jassy keeps making the same point about the enterprise side: it’s still early for inference running in real production apps. In 2000 the customers didn’t exist yet. Today they exist, they’re paying, and most of them haven’t really started.
The debt is real. The bubble isn’t.
None of this means every balance sheet in AI is pretty. Horowitz said it himself: a pathological debt situation can wreck anybody, and a16z stayed out of the neoclouds for exactly that reason. But bad debt and a bubble are different things, and the bears keep blurring them.
CoreWeave carries roughly $50 billion in debt and lease liabilities. Last quarter revenue more than doubled to about $2.6 billion and the net loss still widened to $626 million, mostly on interest. Its five-year credit default swaps hit a record 1,194.5 basis points on October 15, which the market reads as better-than-even odds of default within five years. Its unsecured bonds traded below 80 cents, with $4.4 billion due before year-end. Microsoft, for comparison, runs a debt-to-equity ratio of 0.29. CoreWeave’s is 8.94.
That’s the telecom pattern in miniature: a real asset, real demand, and the wrong capital structure. If CoreWeave breaks, it won’t be because nobody wanted GPUs. It’ll be because the debt came due before the cash did, in a market where last week’s hot inflation print put another Fed hike back on the table. That would be a credit event at one company, felt by the private credit funds and insurers who wrote the paper. It would not be an AI bubble bursting, any more than a leveraged landlord going under in a tight rental market proves nobody needs apartments.
The other line you’ll hear is that this is subprime all over again: speculative data center debt, sliced up and sold to pensions, endowments, and insurers. The plumbing rhymes. The collateral doesn’t.
Most data center securitizations are backed by lease payments, typically on 12-to-20-year leases with Microsoft, AWS, Meta, or Google. In 2007 the weak link was a borrower who couldn’t make the payment. Here the tenant is one of the strongest credits on the planet. The market is also a fraction of the size: about $61 billion of data center ABS and CMBS outstanding as of mid-2026, against roughly $1.3 trillion in subprime mortgages in 2007. And nobody is pricing it as riskless the way they priced subprime AAA tranches. AA-rated data center ABS have paid spreads of 155 to 175 basis points since early 2025.
Who holds it matters too. 2008 turned into a crisis because leveraged banks funded that paper with short-term money that could run overnight. Today insurers mostly take the senior loans on stabilized, already-leased buildings, after private credit funds take the construction risk. A life insurer holding a 15-year Microsoft lease doesn’t face a run.
The part that does look like subprime is GPU-backed lending to neoclouds, where the collateral loses value every year. That’s north of $20 billion, and Nvidia has reportedly been talking to insurers about covering loans made against its own chips, which should make anyone a little uneasy. It’s real. It’s also a small, identifiable slice, and it’s the same layer I already said could break. The lease paper is the safest debt in the stack. Calling all of it subprime is like calling every mortgage in 2006 a liar loan.
The hyperscalers are a different animal. Yes, their numbers are rough right now. Om Malik ran them in the spring: Alphabet’s free cash flow was down 38% year over year, and Meta had $12 billion of quarterly free cash flow against $145 billion of planned capex. The debt loads are heavy and getting heavier.
They’ll be fine. These are trillion-dollar companies with some of the most profitable businesses ever built sitting underneath the spend, and every GPU they install is already spoken for. Depressed free cash flow during the biggest build-out in corporate history is what a build-out looks like.
The real ceiling on this cycle isn’t demand. It’s electrons. Transformers, turbines, interconnection queues, permits. That’s a government problem, and frankly it’s one my own party should be loudest about. If you want the data centers, the construction jobs, and the tax base in your state, you have to let people build the power. Right now the binding constraint on the most important industrial build-out of our lifetime is a permitting calendar.
What would change my mind
I could be wrong, so here’s what I’m watching.
- H100 contract pricing. If one-year rates break back below the $1.70 low while Blackwell capacity ramps, a glut is forming. That’s the dark fiber signal, and it’ll show up in rental prices before it shows up in anyone’s earnings call.
- Capacity language. Every hyperscaler is “capacity constrained” right now. The day Amazon or Microsoft starts saying supply and demand are “in balance,” pay attention.
- Who’s lending. If the neocloud credit stress spreads from the junk layer into investment-grade hyperscaler paper, this stops being one company’s balance sheet and becomes a system problem.
Until one of those moves, I’m sticking with what I’ve been saying. Fiber companies in the late nineties built for customers who hadn’t shown up yet. AWS is turning customers away. That’s a shortage, and shortages don’t pop. The only thing that can break here is a balance sheet that borrowed too much, and if you know which part of the stack holds the debt, you know exactly where to stand.
And one more possibility almost nobody on CNBC will say out loud: maybe these companies are just worth this much. A bubble is a price that has come loose from anything the business will ever earn. When the product is sold out, the customers are paying, and most of the buyers haven’t really started yet, a huge number on a stock screen isn’t proof of anything. Sometimes a big number is just the right number.
The new expropriation
First what you earn. Now what you own. One rent freeze, one wealth tax, one building transfer at a time.
I have spent years telling my own side of the aisle that its socialist wing is an electoral anchor and a policy disaster. I have said it about the billionaire rhetoric, about the housing record here in Massachusetts, about a style of politics that prefers moral theater to material results. So understand that what follows is not a conversion story. It is the same argument, at higher stakes.
The stakes are higher because the socialists have stopped losing. They run the largest city in America. They have a wealth tax headed for the ballot in the largest state. And the thing they are now moving against is not a tax rate or a zoning code. It is the concept of private property itself, which happens to be the load-bearing wall of the entire American structure.
They publish their intentions. I quote them below.
What the founders were actually running from
Let’s start with why the country exists.
The colonists’ grievances were, at bottom, property grievances. The Crown taxed them without their consent. Customs officers used writs of assistance to ransack homes and warehouses on general suspicion. Soldiers were quartered in private houses. The complaint was not abstract. It was that a government could reach into your life and take what was yours, whenever it wanted, with no recourse.
That is why the intellectual scaffolding of the Revolution was John Locke’s Second Treatise, which grounded legitimate government in the protection of life, liberty, and property. Government exists to secure what you have earned. A government that takes arbitrarily has forfeited its legitimacy.
James Madison made it explicit in his 1792 essay “Property”: “Government is instituted to protect property of every sort... This being the end of government, that alone is a just government, which impartially secures to every man, whatever is his own.” The Constitution operationalized this. The Fifth Amendment forbids taking property without due process and just compensation. Federalist No. 10 is Madison worrying, at length, about majorities voting themselves other people’s assets, which he called “an improper or wicked project.”
The founders had watched a government treat ownership as conditional, revocable, and subordinate to the state’s needs. They built a country specifically so that could never happen here. Socialism is the doctrine that ownership is conditional, revocable, and subordinate to the state’s needs. These two projects are not in tension. They are opposites.
Property rights are a middle-class technology
Socialists frame property rights as a shield for the rich. They have it exactly backwards. The rich hire lawyers. Property rights are what protect everyone else.
The entire American middle class runs on collateral. Mortgages exist because a lender believes your title is secure and enforceable. Your small business loan exists because your equipment and receivables can be pledged. Roughly 40 percent of rental units in this country are owned by individual investors, not corporations, and those buildings were financed against expected income. Credit, the machine that turns present work into future wealth, runs entirely on the assumption that ownership means something and the rules will not be rewritten mid-loan.
This is why socialist economies don’t simply fail to produce billionaires, they fail to produce middle classes. When ownership becomes contingent on the state’s ongoing approval, capital flees, and the people with the most capital flee fastest. Everyone else stays and absorbs the damage. That is the record of every country that has run the experiment, and the reason immigrants from those countries are so often the loudest alarm-ringers here.
The program, in their own words
I want to be precise, because “the socialists are coming for your property” is usually the opening line of something unhinged. So I will stick to enacted policy and published plans.
New York. Zohran Mamdani, a self-described democratic socialist, is mayor of the largest city in America, and in June his appointees on the Rent Guidelines Board froze rents on roughly one million rent-stabilized apartments, with a pledge to repeat it every year of his term. The 2019 Housing Stability and Tenant Protection Act had already capped owners’ ability to recover costs; expenses have since grown far faster than permitted rents. A freeze on top of that is a policy of managed insolvency for a class of property owners.
The administration’s own housing plan, released in May, lays out a program it calls Fix the City: roof-to-cellar inspections of targeted portfolios, legal action under the 7A program to strip owners of day-to-day control of their buildings, referrals to district attorneys for criminal charges, and, where the city sees fit, pressure on lenders to begin foreclosure. The stated goal, on page 17, is that these buildings end up “transferred out of these bad actors’ hands and conveyed to responsible preservation purchasers” backed by tenants and the administration. The same plan endorses a bill, COPA, that would give qualified affordable-housing buyers an exclusive first window on buildings coming to market and a right to match any offer after that window closes. Squeeze the asset until it fails, then acquire it. In the twentieth century this was called nationalization and it required soldiers. The innovation of American socialism is doing it through a rent board and a housing agency, 7 to 1, on a Thursday. The plan supplies its own rebuttal to the objection that this only touches slumlords. Pages 34 and 35 concede that rising operating costs, alongside what the plan calls speculation, have pushed large, mostly rent-stabilized portfolios toward financial and physical distress, and respond with a second acquisition track: city capital and tax abatements to move those portfolios to new owners, including community land trusts and tenant co-ops. Read the two sections together. The city freezes the revenue, records the resulting distress in its own plan, and funds the transfer. The “bad actor” label describes a condition the policy itself produces. That is also what separates New York from the rent regulation in Berlin or Stockholm, which a critic will raise: those cities regulate price and stop there, while New York regulates price and then pays to transfer what the regulation breaks.
California. A ballot initiative headed for November would impose a 5 percent tax on billionaires’ net worth, including unrealized gains, meaning paper wealth that has never been sold, priced, or converted to cash. Set aside the revenue math. The principle is the thing. For the entire history of American taxation, the state has taken a share of what you actually receive. This taxes what you merely possess. Once possession itself is taxable, ownership has become a lease from the government, and the only remaining question is where the threshold sits. Thresholds move. Every income tax in American history started as a tax on a tiny sliver of the rich, and the middle class now holds tens of trillions in home equity and retirement accounts that a fiscally desperate state can see perfectly well. The Supreme Court had a chance to close this door in Moore v. United States and declined to, which leaves it open for exactly this kind of measure.
The precedent machine. If you want to see how these doors widen, look at Kelo v. New London, where the Court held that transferring homes from one private owner to a private developer counted as “public use.” The homeowners lost, the neighborhood was bulldozed, and the promised development was never built. Kelo was not a socialist decision. It was worse than that: it was proof that a permissive theory of state power over property will be ratified by respectable institutions, which is exactly the ratification today’s socialists are counting on.
Why the slope is real and not a fallacy
“Slippery slope” gets dismissed as a fallacy. It is only a fallacy when there is no mechanism connecting one step to the next. Here the mechanism is explicit, and unlike most slopes, this one comes with a stated destination. The socialist left does not believe billionaires should exist, and it does not believe the private market should lead on housing. Mamdani, asked on Meet the Press in June 2025 whether billionaires have a right to exist, answered: “I don’t think that we should have billionaires.” His own housing plan lists public-sector-led housing investment as one of its three core values, on page 8. The national platform of the Democratic Socialists of America, of which he is a member, names wealth taxation as the tool for moving money from billionaires to workers. The freeze and the wealth tax are waypoints toward that destination, and they are on schedule.
The method has three parts. First, ownership is a bundle of rights: to use, to exclude, to earn income, to sell, to pass on. No single policy abolishes ownership. Each removes one stick. Freeze the income stream, tax the unsold value, direct the eventual sale. At some point the owner holds title to something that no longer functions as property, and no single step was the one that did it.
Second, fiscal appetite grows, and a revenue mechanism, once validated, never stays parked at its original threshold.
Third, expectations compound. Change the rules once and it is an aberration. Change them twice and capital reprices everything. The best empirical work on rent control, from Stanford’s Rebecca Diamond and coauthors, found San Francisco’s expansion shrank rental supply by 15 percent and raised citywide rents, because owners rationally exited a business whose rules had turned against them. Socialist policy aimed at landlords landed on renters. It always does, because capital adjusts and people cannot. The socialists then cite the wreckage as proof the market failed, and prescribe more of the same. That feedback loop is not a bug in the program. It is the program.
The liberal answer
My own party needs to relearn a distinction. A liberal taxes what the market produces. A socialist revokes the market’s right to produce it. I know that line is unfashionable to insist on, partly because the people blurring it are the most energetic organizers in the room, and partly because the problems they organize around are real. Rents are too high. Wealth concentration is corrosive.
But watch which fix is the plan and which is the fallback. In Massachusetts this year, the coalition pushing rent control led with one of the strictest caps in the country: inflation or 5 percent, whichever is lower, no reset when a tenant leaves, with January 31 rents as the baseline. The moderate version, a local option with a 10 percent ceiling and vacancy decontrol, the one Wu had floated and Healey has said she supports, was offered only in June, as a bargaining chip to make the ballot question go away. The Supreme Judicial Court threw the question out three weeks later over a religious-exemption clause. At no point was anyone in that negotiation talking about how to build more. The liberal answers exist and they are not timid. Strip the zoning veto points that block supply and let people build. Tax realized income and inheritance at whatever rate voters will stand for. Close stepped-up basis, which is the actual loophole that lets unrealized gains die untaxed, and which the wealth-tax crowd rarely mentions because it is boring. None of this requires changing what it means to own something.
The socialists reject those answers, and you should ask why. The honest reason is that their goal is not cheaper rent. It is a different relationship between the citizen and the state, one where what you hold, you hold at the government’s pleasure. The founders had lived under exactly that relationship. They crossed an ocean and fought a war to end it, and they wrote its prohibition into the founding documents, because they understood that every other liberty is downstream of secure ownership.
That wall is load-bearing. The people drilling into it know that. It is why they are drilling there.