1. The First Real Crypto Bull Market Driven by Altcoins [1]

thumbnail The current crypto bull market is projected to be the first "real" one, primarily driven by altcoins, with potential 14x returns due to their expected outperformance against Bitcoin.

1.1. Bitcoin's Diminishing Returns in Past Bull Markets [1]

  1. Bitcoin's current price is around $85,527, which is not very exciting for a show focused on market movements. [1]
  2. This bull market is considered crypto's first "real" bull market, especially for altcoins, which are expected to see significant growth. [6]
  3. Historically, Bitcoin's bull market returns have decreased over time. [30]
    1. The first bull market yielded approximately 10,700% (100x) returns. [31]
    2. The next bull market saw about an 18x return (1,600%), or roughly 15x. [35]
    3. The most recent bull market provided a 6x or 7x return. [41]
  4. Based on this trend, a conservative estimate for Bitcoin's current bull market is a 2x return, potentially reaching $250,000. [43]

1.2. Altcoins Expected to Outperform Bitcoin by 7x, Leading to 14x Returns [59]

  1. The current market is primarily an altcoin bull market, not just a Bitcoin one. [59]
  2. A chart comparing "others" (altcoins excluding the top 10) against Bitcoin shows an overall upward trend, despite past disappointing runs like the ICO boom and DeFi summer. [61]
    1. This upward trend suggests that altcoins are gaining ground against Bitcoin. [72]
    2. The chart currently sits at the bottom of its channel, indicating potential for a significant upward movement. [76]
  3. If this pattern continues, altcoins are projected to outperform Bitcoin by 6 to 7 times. [78]
    1. This projection is based on the altcoin chart moving from 2.5 million to 17 million, representing a 7x increase. [81]
  4. Combining Bitcoin's projected 2x return with altcoins' 7x outperformance against Bitcoin, the average altcoin could see a 14x return in this cycle. [84]
    1. This is considered a very conservative estimate. [87]
  5. In previous cycles, altcoins increased by 5x relative to Bitcoin in 2021 and 7x in 2017, with some individual altcoins achieving 2,000x to 10,000x returns. [93]

2. AI Agents as the Catalyst for the Altcoin Bull Market [101]

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The biggest altcoin season ever will be driven by AI agents, which will conduct billions of transactions daily on blockchain rails, creating a machine-native economy.

2.1. The July Thesis: AI-Driven Altcoin Season [101]

  1. In July, when Bitcoin was trading sideways and many expected a downturn, the speaker predicted the biggest altcoin season ever, driven by AI. [101]
  2. The core thesis, tweeted on July 28th, stated: [106]
    1. All asset markets will trade 24/7, 365 days a year. [112]
    2. All markets will be immediately settled on-chain. [113]
    3. Humans will not be trading them; instead, automated systems and AI agents will. [114]
    4. These agents will trade at unimaginable frequencies, with all fees captured by crypto protocols. [116]
  3. This thesis, formed during the bear market, suggests that a future "agentic economy" will utilize crypto rails, specifically altcoins, which are expected to outperform Bitcoin. [118]

2.2. Raoul Pal on the Power and Inevitability of AI [123]

  1. Raoul Pal emphasizes that AI is the most powerful technology ever discovered, representing a jump from carbon-based intelligence to silicon, which is a million times faster. [126]
  2. The global race for AI dominance, particularly between China and the US, is so critical that no nation can afford to lose. [134]
    1. AI's compounding rate (doubling every 4.2 months) means falling behind by even a short period could make it impossible to catch up. [137]
    2. This could lead to one nation-state having the most powerful technology. [140]
  3. AI agents are seen as the solution to declining productivity growth, especially given population trends. [143]
  4. Historically, the focus has been on the AI trade (NASDAQ), which significantly outperformed crypto during the bear market. [146]
    1. The AI trade outperformed crypto by about two-thirds. [153]
  5. The current focus on AI infrastructure (data centers, computational power, energy) is already priced into the NASDAQ. [156]

2.3. The Rise of Billions of AI Agents and Their Economic Impact [158]

  1. While there are approximately 3.6 to 3.7 billion economically productive humans, a study expects over 1 billion AI agents to be deployed by 2029. [158]
    1. This represents roughly 25% of the entire human workforce. [172]
  2. These AI agents are projected to perform 217 billion actions per day by 2029, generating $22.5 trillion in economic value between 2025 and 2031. [174]
  3. Fortune 500 companies could each have 150,000 AI agents by 2028. [179]
  4. The current AI revolution has primarily focused on building infrastructure for these agents, but the next phase will involve these agents transacting with each other 24/7. [181]
    1. Raoul Pal highlights that the agentic economy requires a coordination layer for value and identity, which blockchains are inherently designed for. [193]
    2. Agents will need to pay for goods, services, electricity, and compute, and will eventually build their own businesses using crypto markets to raise capital quickly. [198]
  5. The sheer volume of transactions (billions daily) by AI agents far exceeds human capabilities, making traditional payment systems inadequate. [210]

3. BlackRock Confirms Blockchain as the Foundation for the Machine-Native Economy [218]

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BlackRock's report, "The Machine Native Economy," validates the long-held thesis that AI agents will settle transactions on blockchain rails, using stablecoins and tokenized assets, thereby achieving product-market fit for crypto.

3.1. BlackRock's Report Validates Crypto's Role in AI Transactions [218]

  1. The long-standing thesis that crypto would be a "solution looking for a problem" has found its use case in AI, as agents need to settle transactions. [218]
  2. A recent BlackRock report, "The Machine Native Economy," confirms this convergence of AI and crypto. [223]
  3. The report states that agentic commerce requires machine-to-machine native payment rails. [229]
    1. The rise of agentic AI will increase demand for blockchains, programmable payment infrastructure, stablecoins, native crypto assets, and tokenized non-chain assets for payments and settlement. [230]
  4. BlackRock explicitly suggests that existing payment rails (like ACH and card networks) are less suited for the "always-on, very low transactions requiring programmable execution" of the new AI infrastructure. [232]
  5. The report emphasizes that machine-native transactions require purpose-built agentic payment protocols, with crypto-native blockchain rails being particularly suited for high-frequency, machine-to-machine transactions around the clock. [240]
  6. The beneficiaries of this shift include stablecoins, native crypto assets, and tokenized real-world assets, which can support transactions and digital ownership. [245]
    1. Tokenization will provide standardized, machine-readable representations across asset classes, reducing integration complexities. [248]

3.2. Stablecoins as the Settlement Layer and Compute as Collateral [250]

  1. The BlackRock report highlights that stablecoins will likely become the primary settlement layer for AI agents, as old payment rails cannot process their unique "language." [252]
  2. Layer 1 blockchains are also mentioned as crucial infrastructure. [257]
  3. A significant concept introduced is compute becoming collateral. [260]
    1. An AI agent could use its compute power as collateral for a loan, meaning failure to pay would result in its compute power being shut down. [261]
  4. Blockchains offer more suitable time conventions (block times) for AI agents than traditional time zones, as agents operate continuously and require granular timekeeping. [264]
  5. Raoul Pal summarizes BlackRock's understanding: AI is machine-native intelligence, crypto is machine-native money, agents need blockchains instead of banks, stablecoins are their money, and compute becomes a tokenized asset class. [270]
    1. The machine economy will also require tokenized identity, contracts, attention, energy, and information. [275]

3.3. Crypto Achieves Product-Market Fit Through Tokenization and AI Agents [278]

  1. The shift from questioning the need for tokens in 2017-2018 to now actively seeking to launch tokens for everything demonstrates crypto's evolution. [278]
  2. Everything, including compute, agents, and energy, will eventually be tokenized and operate on blockchain rails. [287]
  3. This widespread tokenization and the role of billions of AI agents settling transactions on blockchains confirm the potential for a 14x return on altcoins. [291]
    1. Bitcoin, while potentially seeing a 2x or 3x return, is less exciting compared to altcoins' projected 7x outperformance. [301]
  4. The thesis is supported by IDC research, which projects 1 billion AI agents by 2029, performing 217 billion actions or transactions daily. [304]
  5. This marks crypto's first real bull market because, unlike previous cycles driven by Bitcoin's store-of-value narrative or failed altcoin experiments (ICO boom, DeFi summer), there is now clear product-market fit. [349]
    1. The ETH/BTC chart, which represents altcoins versus Bitcoin, has broken out of a nine-year downward trend, signaling this product-market fit. [351]
    2. This fit is driven by the tokenization of everything and the trading of these tokens by billions of AI agents at incomprehensible speeds. [360]
  6. An analogy highlights the absurdity of alternative solutions: a founder suggested giving every AI agent a prepaid debit card, which is far less efficient than blockchain settlement with smart contract rules. [343]

4. Identifying Winning Altcoins in the AI Agent Economy [350]

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To achieve significant returns in the AI agent economy, investors should focus on protocols that AI agents will actively use for transactions, such as specific Layer 1 blockchains, decentralized exchanges, and identity solutions.

4.1. Portfolio Alignment with AI Agent Transactions [350]

  1. Investors should evaluate their portfolios to ensure they align with the needs of an AI agent economy. [362]
  2. Potential beneficiaries include:
    1. Zcash: Could serve as fast, cheap, and private money for AI agents. [369]
    2. Ethereum-like networks: Will facilitate real-world asset transactions, primarily through Layer 2 solutions. [373]
    3. Solana: Could be a key infrastructure for AI agents due to its speed and low cost. [375]
    4. Decentralized Exchanges (DEXes): Agents will need to trade positions, hedge, and swap currencies, making DEXes like Uniswap, Aave, and HyperLiquid essential. [329]
    5. Tenzu Tao (TAI): The AI infrastructure itself will be utilized by agents. [381]
    6. Near: Positioned as the AI blockchain and rails for the agentic economy, benefiting from fundamental growth. [326]
    7. Worldcoin: Essential for proving humanness in an agent-dominated world. [389]
    8. Canton: A Layer 1 blockchain that could become the standard for corporate blockchains, as companies deploy numerous agents. [391]
    9. GTO: Captures economic value on Solana, which will be driven by agents. [398]
    10. Arweave: Another platform suitable for agent-to-agent transactions. [402]
  3. Other necessary layers include wallets, stablecoin payment rails, Layer 1 blockchains, identity modules, and credit score modules. [334]
  4. Projects like "Pump" (meme coins) are considered short-term bets and unlikely to benefit from the agent-to-agent economy. [394]

4.2. Investment Strategy for the AI Agent Economy [403]

  1. The BlackRock report confirms the immense scale of this bull market, driven by the deployment of billions of AI agents within the next two years. [405]
  2. When making investment decisions, ask whether a specific blockchain, DEX, or protocol will genuinely benefit from an economy where billions of AI agents are transacting. [410]
  3. Short-term bets, such as meme coins, are unlikely to provide exponential returns in an agent-to-agent world. [411]