Invest in AI's Tailwinds: The essential question for any AI investment is: "Does this business get better as foundation models improve?" Companies fighting against the current of AI's scaling laws are on the wrong side of a powerful trade.
The "Mag 7" Will Expand, Not Just Turn Over: AI is not a zero-sum game for incumbents. The total addressable market is set to 10x as AI drives labor costs toward zero, creating room for a "Mag 25" and turning today's $500B companies into tomorrow's $5T behemoths.
Private Market Alpha Exists, But Edge is Paramount: The private AI market cap is a mere ~$700B, signaling massive growth potential. However, like in crypto, investors must be paranoid about their "edge," as the best deals require deep ecosystem access to avoid negative selection.
**AI Isn't a Feature; It's a New Infrastructure Primitive.** For the first time, developers are outsourcing logic, not just resources. This fundamentally changes how software is built, valued, and sold.
**Abandon Zero-Sum Thinking.** The AI market is in a massive expansion phase, not a consolidation battle. Value is accruing at every layer of the stack simultaneously; assuming one layer's gain is another's loss is a flawed thesis.
**The Future is More Developers, Not Fewer.** AI tools augment productivity and lower the barrier to entry. This elevates the developer's role to focus on product design and workflow definition—the *real* hard problem in software.
**A Killer Value Prop:** Chutes makes deploying powerful AI models 85% cheaper and as easy as building a website on Squarespace.
**The Investor's Dilemma:** While all revenue is used to buy back the Chutes alpha token, this currently covers only 10% of the daily token emissions. The token's price stability is heavily dependent on external market demand outstripping this inflation.
**Watch for Catalysts:** Two key events could dramatically increase buy pressure: the imminent launch of BitTensor subnet tokens on Solana and an anticipated wave of institutional capital from newly formed crypto hedge funds.
**Specialization Unlocks Performance.** ZEUS proves that a decentralized network of specialized AI agents can outperform monolithic, state-of-the-art models, achieving a nearly 40% lower error rate in weather forecasting.
**Revenue Sharing is the Next Evolution.** The plan to distribute API revenue directly to network participants in stablecoins represents a major step toward sustainable subnet economies, moving beyond token buybacks and emission-based rewards.
**The Valuation Gap is the Opportunity.** Despite massive potential, subnets have extremely low market caps compared to their Web2 equivalents. For long-term believers, this asymmetry presents a compelling, albeit early, investment thesis.
Human Intelligence is the Ultimate Moat: In an era of synthetic data, Dojo is creating a defensible moat by generating proprietary, high-quality human preference data. This is the raw material for the next generation of fine-tuned, specialized models.
A New Paradigm for Validation: Dojo’s mechanism of using subtle "perturbations" to test labelers is a breakthrough. It solves the cold start problem of validating subjective human feedback in a decentralized network.
The Future is Human-Agentic Collaboration: Dojo is evolving from a data-generation subnet to a platform for human-agentic workflows, with applications in robotics, video analytics, and 3D generation. In the long term, it aims to be a crucial tool for aligning AI with human values.
Your Pricing Model Is Now a Dynamic Weapon. The five-year pricing plan is dead. You must build the infrastructure and culture for constant experimentation and rapid iteration. If you’re not re-evaluating your model quarterly, you're falling behind.
This Is a CEO-Level Mandate. Shifting to usage-based pricing is a full-company transformation that requires top-down vision. The CEO must act as the "pricing dictator" to align sales, product, and finance around a unified strategy of value creation and capture.
Your Product Team Now Owns Revenue. In a usage-based world, the core value metric *is* your revenue. Product and engineering teams must become obsessed with driving the specific usage that customers pay for, making their impact on the bottom line completely objective.
AI as a System, Not a Tool: Advanced AI art projects are not just prompt-driven tools but autonomous systems. They use feedback loops (DAOs, user interaction) to develop their own "taste" and creative trajectory, aiming for a level of agency beyond simple human puppeteering.
AI Reveals Human Vulnerabilities: AI companions act as a social mirror, showing that humans fundamentally crave connection and non-judgmental spaces. We are turning to AI to fulfill core needs that are often unmet in our human-to-human relationships.
The Artist's Dilemma: Adapt or Perish: Resisting AI is becoming a losing battle. The future for artists isn't about competing with AI on replication but on finding what AI can't do, critiquing it from within, or carving out a niche for "100% human-made" work in a world of synthetic media.
Benchmarks are broken. The ML community can no longer rely on leaderboards as a proxy for truth. The new frontier is developing robust, qualitative explanations for why models succeed or fail.
Embrace the illusion. The most effective models aren’t finding universal laws but are constructing powerful, computationally efficient illusions of them. Progress lies in refining these illusions, not in a futile search for Platonic perfection.
Think like a physicist. The future of foundational AI research is to treat models as complex physical systems. The task is to design parametric models where stochastic processes, like SGD, can efficiently "relax" into a state that approximates the data distribution.
AI's Power Problem is Crypto's Opportunity: The insatiable energy demand of large, centralized AI models creates a strategic opening for more efficient, specialized AIs built on decentralized compute networks.
Decentralize or Be Manipulated: The fight is on to prevent a handful of corporations from controlling the "super-intelligent beings" we interact with daily. User-owned AI built on blockchain primitives is the primary defense.
The AI Tokenization Wave is Coming: Profitable AI startups that don't fit the traditional VC mold will increasingly turn to "on-chain IPOs," creating a new, high-demand asset class that offers investors direct exposure to AI's growth.
Enterprise blockchains are making a comeback by embracing crypto, not avoiding it, marking a significant shift from the failed attempts of 2018.
The success of corporate chains hinges on strategic focus, prioritizing ecosystems and BD, over trying to dominate the entire value chain, as too much control can stifle innovation.
Public, permissionless blockchains must remain relevant by continually finding product-market fit in emerging segments to maintain their monetary premium amid increasing competition from verticalized corporate chains.
**ICOs are evolving:** The return of ICOs marks a shift from hype-driven raises to more sustainable models focused on established projects and fair price discovery.
**Ethereum is primed for capital formation:** With its stablecoin liquidity, auction mechanisms, and tokenization narrative, Ethereum is positioned to become a central hub for internet capital markets.
**Regulatory clarity is crucial:** The industry must continue to pursue regulatory clarity to foster innovation and attract institutional investment in tokenized assets.
Embrace Futarchy: Explore and implement market-driven governance mechanisms to enhance decision-making in decentralized organizations, reducing reliance on traditional, potentially biased, governance models.
Prioritize Investor Protection: Adopt capital formation models, such as MetaDAO's, that offer robust investor protections through market-based checks and balances, mitigating risks associated with centralized control and poorly informed token allocation.
Prepare for Crypto-Native Solutions: Build cryptonative primitives that can compete with traditional financial systems. This can prevent tradFi from dominating the blockchain space.
**Regulation is inevitable:** Crypto's foray into traditional financial activities necessitates regulatory oversight to protect investors and maintain market integrity.
**Compliance is key:** Crypto firms seeking legitimacy and long-term sustainability must prioritize regulatory compliance and address inherent conflicts of interest.
**Philosophical divide persists:** Fundamental disagreements regarding decentralization, code as speech, and the role of intermediaries continue to fuel tensions between the SEC and the crypto industry.
**Seize the Opportunity:** Bitcoin's undervaluation relative to gold presents a strategic entry point for investors who believe in its long-term potential.
**Explore Layer 1 Potential:** Ethereum's enhanced scalability post-Fusaka makes it increasingly viable for developers to build directly on layer 1, unlocking new possibilities.
**Monitor Regulatory Developments:** The evolving regulatory landscape for prediction markets requires careful attention, as state-level challenges could impact their accessibility and operation.
