Macro investor and Real Vision co-founder Raoul Pal returned to the When Shift Happens podcast for episode 173 to argue that the recent crypto drawdown is a nasty correction inside a much larger bull market, not the end of the cycle. Across an hour and a half he ties together the AI capital race, the coming economic singularity, why layer one blockchains are a kind of universal basic equity, and the deceptively simple discipline that actually compounds wealth: buy, hold, and almost never sell.

TLDW

Pal frames everything through what he calls the universal code, the conversion of units of energy into units of intelligence, and says the global race to fund AI is so large that no government or company can stop feeding it capital. That liquidity, plus relentless currency debasement, is the engine under both the AI stocks going vertical and the crypto market that has lagged them. He calls the Bitcoin slide from 126K toward 60K a normal correction in a bull market, says liquidity is now reaccelerating, and argues smart contract layer ones (Ethereum, Solana, Sui) are the best risk-adjusted bet because the entire financial system and a coming swarm of AI agents will run on those rails, giving crypto an effectively infinite total addressable market. He explains why he added Zcash as a Bitcoin-with-privacy and quantum-proof trade, lays out his plan to launch an NFT fund built around grail digital art and NFT-backed lending, and makes a data-backed case that buying oversold dips and never selling beats trying to trade cycles. The conversation closes on a 70/30 bullish framework for 2026 and 2027 and a reflection on kindness.

Thoughts

The strongest idea in this conversation is not a price target, it is a reframe. Pal keeps pulling the camera back from “what will Bitcoin do this quarter” to “what is the organizing principle of the entire economy right now,” and his answer is the funneling of all available capital into anything that produces intelligence. Once you accept that frame, the buy-the-dip behavior in both AI equities and crypto stops looking like mania and starts looking like a rational response to a one-way game. The part worth sitting with is his game-theory claim that neither the US nor China can stop, and that even a spectacular failure like an OpenAI blowup would simply trigger an instant asset auction rather than a collapse, because no single player can be allowed to win outright. Whether or not that is fully true, it is a genuinely different mental model than the recession-and-bust cycle most investors carry around.

His layer-one thesis is the most actionable takeaway and also the most quietly radical. The pitch is that for the first time ordinary people can own a piece of the core infrastructure that the machine economy will be built on, the way you never got to own a slice of TCP/IP or the open web. He calls this universal basic equity and treats it as humanity’s pension plan. The honest tension he admits is that the racy returns may not be in the boring base layer at all, and that the truly investable winners of this era, the private stablecoin companies, are largely closed off to retail. So the layer-one trade is partly a consolation prize for the fact that the best businesses are unreachable. That is a more candid admission than most crypto bulls will make.

The behavioral core of the episode is the most useful for a normal reader, and it is almost embarrassingly simple. Pal has been in markets for 35 years and says he does not know a single person who reliably buys bottoms and sells tops, including the legends, who he points out made most of their money on management fees rather than heroic trades. His prescription is to add only when the asset is one to two standard deviations oversold on its long-term log trend, otherwise do nothing, and to treat patience as an action rather than inaction. The line that does the most work is “the market owes you nothing.” It quietly dismantles the entitlement that drives people to overtrade, chase, and burn emotional energy on a strategy that the data says underperforms simply holding.

Where a reader should keep some skepticism is the certainty. Pal assigns the bull case a 70 percent probability and the bear case 30, but the bear case he sketches (Middle East war reignites, inflation forces tightening, liquidity gets starved, the intelligence buildout slows) is not a minor footnote, it is the whole structure failing at once. The thesis also leans hard on the assumption that AI agents will become massive on-chain economic actors, which is plausible but still mostly forward-looking rather than observed. The value here is the framework, not the forecast. If you take one thing, take the energy-into-intelligence lens and the standard-deviation discipline, and hold the specific tickers and timelines loosely.

Key Takeaways

• Pal’s central frame is the universal code: the universe, and now the economy, continuously converts units of energy into units of intelligence, and capital flows to whatever produces the most intelligence.
• The AI buildout is a race of nations and corporations that nobody can exit. Game theory means neither the US nor China can stop, because the other side would gain a decisive advantage.
• Even a catastrophic AI failure would not break the trend. If OpenAI ran out of money, its assets would be auctioned instantly to multiple buyers so no single company could double its compute and win the whole game.
• The economic singularity is the point where institutions and the way we measure the economy can no longer keep up with the speed of technology, made worse when AI and robots are added to the population as economic actors.
• AI is the first real-world example of Reed’s law, the exponential of the exponential, where most past technology followed the slower Metcalfe’s law log channel.
• By around 2028, roughly five to six years after AI went mainstream, AI will have produced more words than all of humanity has produced in sum total since the Gutenberg press.
• The current run is funded by cash flow, not debt. Unlike the late-1990s tech boom, the buildout is paid for out of the earnings of the most cash-generative firms in history.
• Chips and energy are the binding constraints. Companies report being booked out three years and beyond, and xAI is reportedly handing older data centers to Anthropic because no one can get enough compute.
• Pal expects the Fed to run a Greenspan-style playbook, cut rates and then get out of the way, letting a productivity miracle grow the economy faster than the debt pile so debt to GDP falls.
• Bitcoin falling from 126K toward 60K is a nasty correction in a bull market, not a bear market. Pal has seen many 50 percent Bitcoin drawdowns since 2013, and altcoins always fall further on the risk curve.
• The 2025 to 2026 correction has been choppy and slow rather than the fast V-shape of 2021, which is part of why sentiment feels so bad.
• Crypto lagged because liquidity is finite. The government shutdown withdrew liquidity, which hits crypto with about a three-month lag, while AI capex and Chinese gold buying sucked capital away.
• Liquidity is now reaccelerating in the US, China, and globally, which Pal sees as the reason the worst is likely over for crypto.
• The birth of economic agents in late 2024 gives crypto an effectively infinite total addressable market, since agents will be economic actors that hold treasuries, make payments, and transact on-chain.
• Smart contract layer ones are Pal’s preferred bet. He compares the structure to operating systems and cloud, where value concentrates into three to five major players plus a few specialists.
• He calls owning layer ones universal basic equity and humanity’s pension plan, the chance to own the rails the agentic economy will run on, something the internet never offered retail.
• Discounted cash flow analysis is the wrong tool for valuing a blockchain. The whole purpose of the network is to be the cheapest, fastest, and most programmable, so high fees are a bug, not a strength.
• Pal measures layer ones by intelligence density: number of developers, programmability, speed to finality, applications per user, and the ratio of stablecoins to total value locked as stored energy.
• Only three tokens maintained economic density when the market fell 80 percent: Ethereum, Solana, and Sui. ETH is the safe Microsoft-like choice, Solana is faster and cheaper, Sui is earlier but extremely fast and programmable.
• Pal added Zcash in the correction as a Bitcoin-with-privacy trade. The left-curve case is simple privacy value, the right-curve case is that it is also quantum-proof and a hedge against AI-enabled state surveillance.
• He admits he did not execute the Zcash buy well, kept meaning to add more while traveling, and watched it run up 50 percent. He treats it as a small position, not a portfolio overhaul.
• On Hyperliquid he is complimentary but uninvested, because he does not trade, use perps, or use leverage, and he expects Robinhood and Coinbase to compete hard for that niche.
• DeFi is better suited to machines than humans. Agents may not even need front ends or websites, just low-friction access to swap across multiple stablecoins and currencies instantly.
• DeFi is not dead despite mega-hacks. Pal argues hacks force better products, and notes that banks quietly absorb theft losses too, so the answer is to build more secure systems.
• The entire financial system is moving to blockchain rails because they are the most efficient way to operate, a prediction Pal first made in 2014 before smart contracts existed.
• Pal is launching an NFT fund focused on grail assets (one-of-one alien CryptoPunks, top artists) trading from roughly 600K to tens of millions, plus a convex middle tier of artists with social consensus.
• He names artists like Dies with the most likes (whom he compares to a Hunter S. Thompson of art) and Kim Asendorf, whose work uses tokens at the pixel level.
• The fund will also lend against NFTs for yields around 15 percent or more, acquiring assets cheaply if borrowers default and recycling yield into emerging artists.
• His real estate analogy: a smaller NFT in a great collection is like a modest apartment in a billionaire neighborhood, while grails are the 20 million dollar penthouses that actually compound.
• Bitcoin is partly an AI proxy because global savings should rise as AI lifts economic growth, and Bitcoin targets a share of those savings as a digital store of value.
• The core mindset shift: if you know where the world is going and roughly where market cap is heading on the log trend, you would never sell, you would only ever accumulate.
• Selling well is nearly impossible. Even if you take profit at two standard deviations overbought, adding it back at the bottom is something almost no one actually manages.
• The people who made the most money in crypto are the ones who did not trade it. Pal cites holders who profited by doing essentially nothing while active traders lost their edge.
• Pal’s discipline requires roughly two to three actions every five years: add when one to two standard deviations oversold, optionally trim when two standard deviations overbought, otherwise nothing.
• By his standard deviation measure, Bitcoin and crypto are as cheap as they have been in their long-term uptrend versus the NASDAQ, which he reads as a signal to allocate more to crypto.
• Fear and greed sat below 10 for the longest stretch in the index’s history during this correction, hitting its lowest reading ever, a classic oversold extreme.
• His 2026 to 2027 bull case stacks stablecoin explosion, the Clarity Act getting signed, rising global liquidity, debt rollovers forcing money printing, a strong business cycle, AI agents, and a cheap entry point. He puts it at roughly 70/30 to the upside.

Detailed Summary

Two economies and the money illusion

The conversation opens loosely with travel, stablecoin spending, and a riff on why people agonize over a 75 dollar airport breakfast but happily lose money on an NFT that drops 80 percent. Pal’s explanation is that we live in two economies at once. The crypto and tech economy can grow 50 to 150 percent in a good year, while the real economy grows around 2 percent. Money earned in the fast economy does not feel real, which is why people spend and speculate so freely with it. This sets up the rest of the episode, where Pal treats the fast economy as the place serious capital is being forced to go.

The AI capital race nobody can stop

Asked why the stock market only seems to go up, Pal gives two reasons: liquidity expansion and the most extraordinary capital event in human history, the funneling of all capital into intelligence. He frames it as a race of nations, corporations, and individuals that cannot be slowed because of game theory. No superpower can let another reach AGI alone, only the US and China can afford the race, and neither can stop without ceding the advantage. He even games out an OpenAI bankruptcy and concludes the US would instantly auction the assets across many buyers rather than let one firm double its compute and win, which is why he calls the whole thing too big to fail. The practical conclusion is blunt: buy the dip, because the structure forces capital to keep flowing.

The economic singularity, Reed’s law, and electricity through sand

Pal defines the economic singularity as the moment when institutions and our economic measurements can no longer cope with the speed of technology, especially once AI and robots count as population. He explains that almost all past technology adoption followed Metcalfe’s law, a log channel visible in the charts of Google, Facebook, and the NASDAQ, but AI is the first observed example of Reed’s law, the exponential of the exponential. To make it concrete he cites ARK research showing AI will, by roughly 2028, have produced more words per year than all of humanity, and notes Anthropic expected 10x growth and got 80x in a quarter. He marvels that we are putting electricity through silicon, the second most common element on Earth, and producing intelligence six orders of magnitude faster than a human neuron.

Why crypto lagged and why the worst is over

Pal explains the crypto underperformance mechanically. There is only so much liquidity, the government shutdown withdrew it, and that hits crypto with roughly a three-month lag, landing right in the middle of the October drawdown. At the same time, the AI buildout and Chinese gold buying pulled capital toward the longest-duration assets, leaving SaaS and crypto with nearly identical charts as they got left behind. His read for 2026 is that liquidity is now reaccelerating across the US, China, and the world, so there is nothing to worry about yet. The Bitcoin move from 126K toward 60K is, in his framing, a normal correction, comparable in length to the roughly six-month 2021 pullback that resolved into new highs.

Layer ones as universal basic equity

The heart of the investment thesis is that smart contract layer ones will accrue a growing share of crypto value as the investable infrastructure layer. Pal argues the entire financial system plus a coming swarm of AI agents will use these rails, giving crypto an infinite total addressable market. Like operating systems and cloud, value will concentrate into three to five chains plus specialists. He measures them by intelligence density rather than discounted cash flow, since the point of the network is to be cheapest and fastest. By his analysis only Ethereum, Solana, and Sui held economic density through an 80 percent drawdown. ETH wins on developers, security, and Lindy effects (the Microsoft you do not get fired for owning), Solana is faster and cheaper, and Sui is earlier but offers a different order of magnitude on speed, finality, and programmability. He frames owning a basket of four or five as humanity’s pension plan.

Zcash, privacy, and the quantum hedge

Pal reveals he added Zcash during the correction, alongside buying more Sui. He had said in December he would wait for it to pull back, and he did, though he admits he did not buy enough as it ran up 50 percent. His left-curve case is that privacy has real value and people will understand it more, making it essentially Bitcoin with privacy that could plausibly reach 5 to 10 percent of Bitcoin’s value. His right-curve case is that it is also quantum-proof and a hedge against governments wielding AI-enabled control over people. He dismisses the mid-curve worry that it will be banned, noting that the ban fear has shadowed crypto his entire career and never materialized.

Agents, DeFi, and financial rails

Pal argues the biggest future users of DeFi and crypto payments will be AI agents, whose scale is effectively infinite. Setting up agents himself, he keeps hitting walls that require small payments, and sees agents making endless micro-payments plus larger transactions, holding treasuries across multiple stablecoins and currencies, and rebalancing through DeFi instantly without any human involved. DeFi, he says, is actually better suited to machines than people, and may not even need front ends. On the wave of mega-hacks he is unbothered, arguing they force better products, that banks quietly absorb theft too, and that the financial system always migrates to the most efficient rails because that is how you make more money. He first predicted blockchain would become the financial industry’s infrastructure rail back in 2014.

The NFT fund and grail digital art

Pal is launching an NFT fund because so many people told him they want exposure but do not know how. The fund targets grail assets, the scarce one-of-one pieces with proven social consensus that trade from around 600K into the tens of millions, plus a convex middle tier of artists who have long-term proven value and could be wildly re-rated. He names Dies with the most likes, an Indiana artist cataloging the decline of middle America whom he likens to Hunter S. Thompson, and German artist Kim Asendorf, whose 3D works are built from individually tokenized pixels. The math of convexity is the draw: an artist re-rating from 20 to 200 ETH while ETH itself multiplies could compound into a 100x. The fund will also lend against NFTs for yields above 15 percent, acquiring assets cheaply on default and recycling yield into emerging artists, and will build a club connecting investors to artists. His real estate framing reassures smaller holders: owning a lesser piece in a top collection is like a modest flat in a billionaire neighborhood.

Never sell, and the math of patience

The behavioral spine of the episode is Pal’s argument that buying, holding, and accumulating beats trading cycles. He has built a Real Vision indicator that signals a buy when an asset is one to two standard deviations oversold on its log regression channel, and says it compounds at a stupid rate. The problem with selling is deciding how much and then having the discipline to buy it back at the bottom, which almost no one does. In 35 years he says he has never met anyone who reliably buys bottoms and sells tops, and notes the trading legends made most of their money on management fees. The people who made the most in crypto are the ones who did nothing. He reframes holding as patience, an active stance, and ties it back to the universal code: buying Bitcoin and doing nothing is the most energy-efficient trade you can make, while overtrading burns mental and emotional energy for a worse outcome. His advice to those tempted by AI’s vertical charts is to go play with AI and just hold your Bitcoin.

The 2026 to 2027 outlook

Pal closes the macro case by stacking the bull factors: a massive stablecoin expansion over the next 24 months, the Clarity Act getting signed and freeing builders, rising global liquidity, trillions in interest payments that force more money printing, a strong business cycle recycling earnings into speculative assets, the arrival of AI agents, and a cheap entry point with fear and greed at historic lows. He even floats a permanent resolution of Middle East conflict as part of the upside. The bear case is the mirror image: war reignites, inflation runs hotter, tightening starves capital, and the intelligence buildout slows. He puts the odds at roughly 70 percent bullish, 30 percent bearish, and says he does not see the bear case yet. The episode ends on a personal note about kindness, with Pal unable to name a single kindest act because, he says, everything is made of kindness.

Notable Quotes

“We’re going through the most extraordinary time in human history. Nothing else matters. This whole funneling of all capital into intelligence is the biggest race that’s ever happened.”

Raoul Pal, on why capital keeps flooding into AI

“The game is so big that nobody will stop.”

Raoul Pal, on the game theory of the US and China AI race

“This is how amazing it is. We’re putting electricity through sand and creating intelligence.”

Raoul Pal, on silicon and the universal code

“It’s a nasty correction in a bull market. I’ve been in crypto since 2013. I’ve seen many corrections, non-bear markets of 50% in Bitcoin.”

Raoul Pal, on Bitcoin falling from 126K toward 60K

“The market owes you nothing. You would just have to be better at doing a job.”

Raoul Pal, on the entitlement that ruins crypto investors

“This is humanity’s pension plan. We get to invest in the infrastructure rails of which all the agentic economy will run.”

Raoul Pal, on owning layer one blockchains

“The people who’ve made the most money out of crypto are the people who don’t trade it.”

Raoul Pal, on why holding beats trading

“Your job is to be a mercenary for your own capital. You want to make the most money over time.”

Raoul Pal, on why no one has to stay loyal to crypto

“Bitcoin and crypto is as cheap as it has been in its long-term uptrend versus NASDAQ.”

Raoul Pal, on the relative value signal he watches

This is a compressed look at a wide-ranging conversation. Watch the full episode on When Shift Happens here for Pal’s complete reasoning, the charts he references, and the back-and-forth that the summary above leaves out.

Related Reading

• Real Vision the financial media platform Raoul Pal co-founded, where his Global Macro Investor research and exponential age thesis live.
• Metcalfe’s law (Wikipedia) the network-value relationship Pal uses to model the log regression channel for crypto.
• Reed’s law (Wikipedia) background on the exponential-of-the-exponential growth Pal says AI is the first real-world example of.
• Technological singularity (Wikipedia) context for the economic singularity Pal argues is now only about four years away.
• Zcash the privacy coin Pal added in the correction as a Bitcoin-with-privacy and quantum-proof trade.