저자: RaoulPal&TomLee · 외국인
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유동성 회복과 AI 에이전트 확산으로 크립토가 구조적 재평가 국면에 들어섰다는 주장. 크립토는 과거 최고 수준에서 6만 달러대로 하락했으나 장기 상승 추세 내 재축적 국면으로 해석. AI 생산성 효과로 소프트웨어 등은 조정되나 주식 추세는 유지되며 연준 정책 전환이 순풍이라고 봄. 미국 셧다운 유동성 회수 후 3개월 시차를 두고 위험자산이 회복 중이라는 진단.
다듬은 글
Everything just changed for crypto. Raoul Pal and Tom Lee believe we are entering a phase unlike anything in history. Right now, two of the most influential voices in macro and markets are pointing towards the same structural shift from different angles. Raoul Pal is focused on liquidity returning, capital rotation reversing, and AI agents emerging as new economic actors on blockchain rails.
Tom Lee is focused on AI-driven productivity, shifting Fed expectations, and the early stages of a new expansion phase in risk assets. After months of pressure, crypto was left behind as liquidity drained and capital flowed into AI, big tech, and hard assets. But, Raoul Pal argues that phase is now reversing.
And when liquidity turns back on, crypto is usually the first to react. At the same time, AI agents are changing the structure of the market itself. Not just narratives, but actual autonomous systems beginning to transact and operate at scale. According to Raoul Pal, this expands crypto's addressable market into territory we have never seen before.
Tom Lee adds the macro layer, arguing that AI is only now starting to show its real productivity impact, and that policy is slowly shifting back into a more supportive environment for risk assets. Together, both are describing a setup that feels less like a normal cycle and more like a structural regime chang; The US withdrew liquidity for the government shutdown.
That lags crypto by 3 months. It hit crypto, that was 10 10 was in the middle of all of that. Liquidity's picking up again, crypto's picking up again, but there's a gap because Nasdaq, because of this massive need for capital and investment in the space, it just sucked in capital. The Chinese for a period of time bought a lot of gold in that gold rally.
So, what happened was the riskiest of assets, the furthest duration assets, which is SAS companies and crypto produced identical charts and they just got left behind for a bit. But, what's happened is literally everything's changed. Because in that period from that period of October um last year we birthed economic agents.
And they're scaling everywhere. Everybody's building them. So, what you've got is it it dawned on me suddenly is like everyone's like, "Yeah, agents are going to use, you know, wallets and blah blah blah." But, then when you play it through from what I've been talking about, the speed of which this is happening this means crypto has an infinite TAM.
The total addressable market is all of the agents. And they will be economic actors in their own right, building their own businesses, stuff like that. So, it's changed everything. So, when you were saying crypto is going to like 100 trillion dollars or Yeah. maybe half of that if we miss, this was based on humans.
Yeah. Yeah, it it was. Now it's still Metcalfe's law. It still follows the log trend, and that would take us still there. You might get there a bit earlier. But, what it kind of means is it just keeps going. Cuz A, the debasement of currency won't stop until debt to GDP collapses. We're not there yet.
GDP growth is not fast enough. We need to get through the economic singularity. Then we see you know, the global coordination rails of of uh blockchain being used for more and more things. Don't forget the entire financial system is going onto these rails. Mhm. And you get to front run it. They've announced what they're going to do.
And I've always said this, we've been able to front run the institutions all the way through. And people get exasperated with crypto cuz it went down for a year. And you're like look at the [ __ ] picture. You've got an infinite TAM, the entire financial system going off the rails, the Clarity Act being passed, the government will not stop debasing the currency.
Mhm. So, it just keeps going. Raoul Pal opens this phase of the market with a simple but powerful observation. Liquidity that was pulled out of the system during the government shutdown is now beginning to flow back in. That lag effect did not disappear. It moved through the system slowly and crypto absorbed the downside first as risk appetite contracted across the board.
What followed was not a breakdown in structure, but a capital rotation. Money moved into areas benefiting from the artificial intelligence buildout, large technology leaders, and defensive stores of value like gold. Crypto being one of the highest beta parts of the system was left consolidating while liquidity searched for safer or more immediate growth narratives.
Raoul Pal frames this kind of environment as temporary distortion rather than a trend reversal. When liquidity contracts, the most speculative assets get hit first. When it expands again, they are also the first to respond. That is where crypto tends to reprice faster than traditional markets because of its sensitivity to flows and positioning.
At the same time, a new structural layer is forming underneath the price action. AI agents are beginning to function as autonomous economic participants capable of initiating transactions and interacting across digital systems. This introduces a new form of demand for blockchain infrastructure that did not exist in previous cycles.
Capital today is still heavily focused on artificial intelligence and large-cap equities, but liquidity cycles do not stay static. They rotate, and when that rotation begins to reverse, it rarely does so gradually. It accelerates into the most reflexive parts of the market first. Crypto now sits directly at that edge again where liquidity returns tend to show up in the fastest and most aggressive way before spreading across the rest of the system.
. Nothing . Mhm. what what in this, this i. Mhm. They run out of money. That's the doom monger cuz t;> game. which you can't allow either. Mhm. ; Raoul Pal shifts the focus from liquidity alone into something even more powerful driving markets right now, the global race toward artificial intelligence.
He describes this moment as a competition between nations, corporations, and entire financial systems all pushing capital into intelligence at a pace that cannot be slowed down. This is not a normal technology cycle. It is a structural acceleration where capital is being pulled into compute, data infrastructure, and AI systems because no participant can afford to fall behind.
The United States and China sit at the center of this dynamic, locked in a game theory loop where neither side can slow down without risking long-term disadvantage. This creates a unique environment for risk assets. Liquidity is not just moving randomly across markets, it is being absorbed into a single dominant narrative, artificial intelligence, that has temporarily starved areas like crypto of attention and flow even as underlying infrastructure continues to develop.
Raoul Pal frames this as a temporary concentration of capital, not a permanent shift. When capital becomes overly concentrated in one theme, the system builds pressure elsewhere. That pressure eventually releases back into assets that were previously ignored or underweighted. Even in scenarios where parts of the AI ecosystem face stress or failure, the response from governments and large institutions would likely be immediate intervention.
The system is too strategically important to allow collapse, which reinforces the idea that capital will continue rotating within this broader intelligence race rather than exiting it. This matters for crypto because it sits directly adjacent to this shift. Blockchain rails are increasingly viewed as settlement and coordination layers for future digital economies, especially as AI systems begin to transact autonomously.
That positioning means crypto is not competing with AI but sitting underneath it as part of the same expanding infrastructure lay. So, for you Bitcoin going for forere's to Ethereum. Happens to it went back up also very quickly and then it went down . And what migh, from like January to July? And it was back at ou know, only went down six ; Raoul Pal reframes the recent volatility in crypto by separating emotion from structure.
In his view, a move like Bitcoin falling from around 126,000 towards 60,000 does not automatically signal a bear market. Instead, it reflects a deep correction inside a broader bullish cycle that is still intact. This distinction matters because crypto history is filled with similar moves. In previous cycles, Bitcoin has repeatedly dropped around 50% or more while still remaining in a long-term uptrend.
The risk curve in crypto is natural. When Bitcoin corrects, higher beta assets tend to fall even harder, creating the illusion of breakdown even when the macro structure has not changed. Raoul Pal points to prior cycles where assets like Solana and Ethereum experienced drawdowns exceeding 80% during bullish environments, only to later recover and set new highs.
These moves often happen during periods where liquidity is still present in the system, even if unevenly distributed. What makes the current cycle different is the rhythm of the correction. Instead of a fast crash followed by a sharp recovery like in earlier cycles, the market has been more drawn out and choppy.
That extended structure creates uncertainty, even though it does not necessarily change the underlying trend. Historically, slower corrections often lead to longer expansion phases afterward. The system spends more time building positioning, resetting leverage, and preparing for the next impulse higher.
From Raoul Pal's perspective, this type of price action is not the end of the cycle, but part of the reaccumulation phase that typically precedes larger upside moves. Once liquidity conditions stabilize and return more broadly, these compressed structures tend to resolve aggressively. In that context, the recent drawdowns are not the story of failure.
They are part of the setup for the next expansion phase where the strongest assets tend to move first and fastest when conditions flip. Why aren't you worried right now? Um you know, one thing an adage that came from Art Cashin, the late Art Cashin, is that bull markets don't die of old age. Um they get killed by the Fed.
So, um yes, so something to keep in mind is that just because stocks have done well doesn't mean that they can't continue to do well. And I know we'll get cover this in our conversation today, but I think in 2026 we are starting to see the other side of the payoff from AI. Um and it's creating winners and losers.
And uh I think that we are getting a policy shift from the Fed, which also is a tailwind. So, I think in many ways there are reasons for people to want to buy buy stocks this year. And what's going on right now? I mean, we've seen even in just the last couple weeks, right? Software stocks down a ton, crypto down a ton.
And we'll get into crypto a little more specifically later. Does a period like this start to freak you out? Does it change the thesis at all? Um well, I think many people in the audience have been following the story for the last 2 years, which has been uh AI like as a juggernaut. And you know, people already have exposure.
But as Liz pointed out, there is something that's different this year. All of a sudden a lot of stocks and industries are starting to have shrinkage. So, the software industry, for instance, is seeing shrinking demand and a repricing of their service. And there's now many research reports pointing out that agentic AI products or AI products are starting to replace traditional software.
And then as you know, there's even stories of uh technology employment has shrunk in the last 3 years since the introduction of ChatGPT. It's a shrinking share of employment and college graduates unemployment rate is now higher than non-college students of the same age. Now, that is like what you might think is the bad news story and that's what's the headlines right now.
But think of it the other way. That's productivity for the economy. This is how you measure productivity is that you produce more output with less people. So, that's proof that AI is productive. Software companies sell services to corporations. If they're spending less on software, which they are, that's a margin story.
We're starting to see the benefits of AI. Tom Lee anchors his view on a simple historical pattern. Bull markets do not typically end because they grow old. They end when policy tightens and liquidity is removed in a sustained way. That framework shapes how he interprets the current market environment where conditions are still evolving rather than collapsing.
From his perspective, the dominant force in this cycle is artificial intelligence. The AI build-out is beginning to show real economic effects, not just narrative momentum. Companies are already adjusting cost structures, productivity models, and workforce composition as AI tools start replacing portions of traditional software and services demand.
This creates a split economy. Some sectors experience pressure and repricing, while others benefit from efficiency gains and margin expansion. That divergence is not a sign of weakness in the broader system, but a signal of transition toward a new productivity regime. Tom Lee also highlights that market pullbacks in this environment often reflect rotation rather than destruction.
Software and speculative growth areas have already seen sharp corrections, but this has not invalidated the broader equity trend. Instead, it reflects capital shifting toward winners in the AI trade. At the same time, labor market signals show early signs of transformation. Employment in certain technology segments has softened, while productivity per worker is increasing.
Historically, this type of transition appears disruptive in the short term, but expansionary over longer horizons. Policy remains a key variable. As inflation trends and growth expectations shift, markets begin to anticipate a more supportive stance from the Federal Reserve. Even small adjustments in expectations can have outsized effects on risk assets when liquidity is sensitive.
Tom Lee's core message is that as long as policy does not aggressively tighten, the underlying trend for risk assets remains intact. Combined with AI-driven productivity gains, this creates an environment where markets can continue advancing even through volatility, with leadership rotating rather than the cycle ending.
When Raoul Pal and Tom Lee zoom out, they converge on a view that this cycle is not behaving like previous crypto expansions. The market is no longer being driven by a single clean liquidity wave. Instead, it is being shaped by overlapping forces that are colliding at the same time: liquidity cycles, artificial intelligence, and structural shifts in how capital is deployed across the global economy.
Raoul Pal emphasizes that crypto is no longer constrained by a purely human-driven market model. The rise of AI agents introduces a new category of economic participants that can transact, build, and interact autonomously. That effectively expands the total addressable market beyond traditional assumptions because it is no longer only about people using financial systems, but machines operating within them.
This creates a feedback loop that did not exist in prior cycles. More digital activity requires more settlement layers. More autonomous systems require more programmable money. That places blockchain infrastructure closer to the center of future economic coordination rather than at the edge of speculative behavior.
This is why both analysts are focused on the same underlying idea from different angles. The cycle is not simply repeating. It is evolving into a structure where digital assets, artificial intelligence, and global liquidity are increasingly intertwined, setting the stage for the next major expansion phase in risk markets. .
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