Raoul Pal, founder of Real Vision, argues that crypto’s next leg higher may depend less on idiosyncratic token catalysts and more on macro liquidity conditions—particularly the US dollar and US bond yields. In a recent episode of Cointelegraph’s Trade Secrets, Pal said the dollar’s strength and higher yields are keeping liquidity from moving freely into risk assets, including digital currencies.
Pal also highlighted an increasingly important cross-asset dynamic: capital has been competing between crypto and AI equities. He believes a “pause” in AI trading—rather than a full-blown downturn—could help rotate funds back into the crypto market. At the same time, he expects the growth of AI agents to favor smart-contract platforms such as Ethereum and Solana over Bitcoin for a portion of the resulting economic activity.
Key takeaways
- Raoul Pal links crypto momentum to macro liquidity: a weaker US dollar could provide a “green light” for further market movement.
- Bond yields and the strong dollar are currently a headwind: Pal says they limit the flow of liquidity into crypto.
- AI equities have competed for funds: Pal points to the potential for crypto to benefit if AI markets trade sideways instead of crashing.
- AI agents may drive more activity on smart-contract chains: Pal expects Ethereum and Solana to capture more of that demand over time.
- Pal is cautious about simple “Solana vs. Ethereum” flip narratives: he says Ethereum’s capital concentration creates a different kind of advantage.
Why Pal wants to see the dollar weaken
Pal’s central macro argument is straightforward: when the dollar trends higher and yields remain elevated, liquidity tends to stay more tightly bound to traditional markets. In his view, crypto needs more favorable conditions to extend its rally.
On the question of what would change, Pal said that if policymakers and markets engineer a weaker dollar, crypto could receive clearer support. He emphasized he does not see a full green light yet, but the directional implication is that loosening in the dollar/yield backdrop would improve the odds of additional upward momentum.
He also framed liquidity as a key variable that determines whether markets can grow without stress. In his assessment, conditions that “suck out” liquidity are dangerous for any asset class trying to sustain a rally—crypto included.
AI’s tug-of-war with crypto: rotation without a bubble burst
Pal tied his liquidity thesis to an intermarket pattern involving AI equities. He pointed to a period between Aug. 19 and Aug. 25, when Bitcoin reportedly rose about 25% to roughly $80,000, alongside seven consecutive losing sessions for Nvidia. The takeaway for Pal: when AI trade activity pauses or cools, capital can rotate toward crypto.
At the same time, Pal warned against the opposite scenario. A disruptive AI crash would likely signal liquidity being withdrawn from the system—something that would threaten the conditions crypto relies on to rise. He said the market generally fares better when liquidity remains plentiful rather than evaporating.
He laid out the type of outcomes he would prefer: a weaker dollar, a steeper yield curve, and banks increasing lending and money supply through expanded credit. However, he noted that borrowing costs have been moving higher and cited that the US 10-year Treasury yield climbed to 5.29% in September. He also referenced the Federal Reserve raising its benchmark rate by a quarter-point, citing Cointelegraph’s coverage of that decision.
With those headwinds in place, Pal’s “second best scenario” is more modest: AI stocks trading sideways. That, he argued, could still allow funds to rotate into crypto without a sudden liquidity shock.
AI agents and stablecoin payments could tilt activity toward Ethereum and Solana
Beyond macro conditions, Pal argued that the next wave of economic activity may come from AI agents—software that interacts with services and transactions. He believes that as agents begin paying for content access and executing tasks that require settlement, smart-contract platforms may benefit.
He referenced an Amazon Web Services initiative that added a capability for AI traffic monetization, enabling content owners to charge AI bots for access. He also pointed to Coinbase’s role in agentic payment verification and settlement through its x402 protocol, noting that USDC on Base is among the supported payment options.
Pal suggested that agents could eventually finance longer-lived operations through token-based mechanisms—issuing tokens to fund projects with durations ranging from short bursts to multi-month or year-long initiatives. In that model, smart contracts provide the infrastructure to transact as the work happens and returns are generated.
From that perspective, he said Ethereum and Solana stand to see greater adoption “over time” as AI systems use their networks’ capabilities to carry out and settle transactions.
Solana’s activity vs Ethereum’s capital concentration
Pal also weighed in on an ongoing debate in crypto markets: whether Solana will surpass Ethereum in market capitalization during the current cycle. While he expressed enthusiasm for both networks, he cautioned against treating “flip” narratives as inevitable.
He referenced a prior claim made by Multicoin Capital co-founder Kyle Samani on Trade Secrets, where Samani predicted SOL would surpass Ether’s market capitalization in this cycle. Pal responded that Samani “needs to hold his horses a little bit,” though Pal acknowledged it is still possible.
To explain why the comparison is not one-dimensional, Pal noted that the networks lead on different metrics. Using DefiLlama figures, he cited that Solana recorded around 3.2 million active addresses over the preceding 24 hours (Monday), versus Ethereum’s 387,000. Yet he contrasted that with decentralized finance depth: Ethereum has approximately $54.4 billion in DeFi protocol value, far above Solana’s roughly $6.7 billion.
Pal described a framework he calls “economic density,” dividing total value locked by active users. His argument is that Ethereum draws more capital relative to user count, while Solana’s activity involves smaller transaction sizes—an asymmetry he summarized by saying Solana’s core activity is “speculation” in “smaller clip sizes.”
On price forecasting, Pal said he has stopped sharing public targets because they tend to be clipped, circulated, and repeated in ways that can distort expectations. He characterized the idea of Bitcoin reaching “million-dollar” levels by 2030 as more of a “meme” rooted in growing adoption, ETF interest, and Bitcoin’s use as collateral. Still, he said he does not have an issue with Bitcoin reaching that kind of milestone by 2032.
What readers should watch next is whether the macro signals Pal flagged—especially the dollar and yield trajectory—actually turn in crypto’s favor, and whether AI markets enter a sideways rotation rather than a liquidity-draining crash. If that pattern holds, Pal’s framework suggests crypto could benefit—while AI-agent monetization and payments may increasingly route growth toward smart-contract ecosystems.
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