The Two-Headed Bull. The market is driven by a flight to hard assets like gold due to fiscal decay and a speculative mania in AI stocks. Smart money isn't choosing—it's positioned in both.
Bitcoin's Generational Test. Bitcoin's future as "digital gold" hinges on a generational handoff. For now, its price action tells a different story: it trades like a tech stock, not a safe-haven asset.
Asia is the Epicenter of Froth. While the Western crypto market grinds methodically higher, the real heat is in the East. BNB’s explosive rally and the cash-flush atmosphere at conferences show where the speculative capital is flowing.
A Perfect Storm for a Melt-Up: A potent cocktail of future Fed cuts, massive fiscal deficits, and the AI capex boom is setting the stage for a parabolic, blow-off top market rally.
The Debasement Trade is On: Japan's currency policy is supercharging the US dollar and forcing a global reckoning with fiat dilution, driving a secular flow of capital into hard assets.
Crypto is Now a Macro Asset: Forget the four-year halving cycle. Crypto's fate is tied to global liquidity, and ETH is exhibiting strong supply-side dynamics that could fuel significant outperformance.
AI Is a Pattern-Matcher, Not a Logician. Current models excel at synthesizing existing knowledge but fail at the novel, multi-step creative reasoning required for frontier mathematics. They lack the fundamental logic to build sound proofs from scratch.
The Mathematician Becomes the Editor. As AI automates computation and literature reviews, the primary human role will shift to strategic oversight: identifying valuable problems, validating AI-generated work, and setting the research agenda for the entire field.
Benchmark or Be Disrupted. The math community must lead the charge in creating and assessing rigorous AI benchmarks. Failure to do so risks letting non-experts define success, potentially devaluing the discipline based on superficial AI achievements.
An AGI Moonshot, Not an LLM Factory: Hone’s singular focus is solving the ARC-AGI benchmark to achieve true generalization. This is a high-risk, high-reward play for a step-function leap in AI, not just another incremental improvement.
Architecture Over Data: The strategy is to out-innovate, not out-collect. By exploring novel architectures like JEPA, Hone aims to create models that think more efficiently and don't depend on ever-expanding datasets, sidestepping the data moat of centralized giants.
The Business Model is the Breakthrough: There is no immediate revenue. The investment thesis is straightforward: solve AGI, earn the ultimate bragging rights, and then monetize the world’s first truly intelligent model through distribution partners like Targon.
Vertical Integration is Non-Negotiable: To build AGI, the old model of horizontal specialization is dead. Owning the stack—from research to infrastructure to product—is the only way to move fast enough.
Ship to Socialize: Don't build AGI in a lab and drop it on an unsuspecting world. Products like Sora are deliberate steps to co-evolve technology with society, managing impact through iterative, public-facing releases.
The Real Turing Test is Science: The true measure of AI's power is its ability to make novel scientific discoveries. Altman believes GPT-5 is already approaching this milestone, which will have a more profound impact on humanity than any chatbot.
Stop Fearing Parameters. When in doubt, go bigger. Scale is not just about capacity; it’s a tool for inducing a powerful simplicity bias that improves generalization and paradoxically reduces overfitting.
Trade Hard Constraints for Soft Biases. Instead of rigidly constraining your model architecture, use gentle encouragements. An expressive model with a soft simplicity bias will find the simple solution if the data supports it, while retaining the flexibility to capture true complexity.
Think Like a Bayesian. Even if you don't run complex MCMC, adopt the core principle of marginalization. Techniques like ensembling or stochastic weight averaging approximate the benefits of considering multiple solutions, leading to more robust and generalizable models.
Reward Function is Everything. Mantis’s success hinges on its information-gain-based reward system, which attributes value based on a miner’s marginal contribution to a collective ensemble, not just their individual accuracy.
Inherent Sybil Resistance. By rewarding unique signals, the incentive mechanism naturally discourages miners from running the same model across many UIDs, solving a critical vulnerability in decentralized AI networks.
The Product is Verifiable Alpha. The endgame is not just to build a subnet but to produce a monetizable product: high-quality financial signals, auctioned to the highest bidder and backed by an immutable on-chain performance record.
Incentives Dictate Intelligence. Mantis's breakthrough is its reward function. By precisely measuring a miner's marginal contribution, it makes unique alpha the only profitable strategy and naturally defends against Sybil attacks.
The Ensemble is the Alpha. The network’s power lies not in finding one genius quant, but in combining many good-enough signals into one great one. The collective intelligence is designed to be far more valuable than any individual participant.
The Future is Verifiable, On-Chain Alpha. Mantis plans to monetize by auctioning its predictive signals, creating a transparent marketplace for intelligence and proving that a decentralized network can produce a product valuable enough to compete with Wall Street's top firms.
Google's "Tax on GDP" Is Under Threat. AI is eroding the informational searches that feed Google's funnel and will eventually intercept high-intent commercial queries, redirecting economic power to new agentic platforms.
The Future of Shopping Is Agentic, Not Search-Based. Consumers will delegate research and purchasing to specialized AI agents that optimize every variable, from product choice to payment method, fundamentally changing how brands acquire customers.
Trust Is the Ultimate Moat. In a world of automated "crap," business models built on human trust and strict curation, like Costco's, become exceptionally defensible.
AI's gravitational pull on talent and capital is forcing crypto to mature beyond speculative tokenomics, transitioning focus from "meme value" to demonstrable product-market fit and real-world utility.
Identify and invest in projects building at the intersection of crypto and AI, or those creating "net new" applications that abstract away crypto complexity for mainstream users, especially in areas like identity or fintech.
This bear market is a necessary, albeit painful, reset. It's a time for builders to focus on creating tangible value and for investors to seek out projects with genuine utility, as the era of easy speculative gains is over.
The commodification of AI compute, driven by decentralized networks, is shifting power from centralized data centers to globally distributed, incentive-aligned miners. This creates a more efficient, resilient, and cost-effective foundation for intelligence.
Explore building AI agents and applications on Shoots' expanding platform, leveraging their TEEs and end-to-end encryption for privacy-sensitive use cases. The "Sign in with Shoots" OAuth system offers a compelling way to integrate AI capabilities without upfront compute costs.
Shoots is not just an inference provider; it's building the foundational infrastructure for a truly decentralized, private, and intelligent internet. Over the next 6-12 months, expect to see a proliferation of sophisticated AI agents and applications built on Shoots, driven by its unique blend of incentives, security, and global compute.
The Macro Shift: Ethereum pivots from a "rollup-centric" vision to a multi-faceted approach: a powerful, ZKVM-scaled L1 coexists with a diverse "alliance" of specialized L2s. This adapts to technical realities and renews L1's core focus.
The Tactical Edge: Builders should prioritize differentiated L2 solutions or contribute to L1's ZKVM scaling. Investors should evaluate L2s based on distinct utility and symbiotic relationship with Ethereum.
The Bottom Line: Ethereum's market leadership remains, but this pivot signals a pragmatic roadmap. The next 6-12 months will see rallying around L1 ZKVM scaling and clearer L2 roles, demanding sharper focus on where value accrual and innovation occur.
Global liquidity is high, but capital is reallocating from speculative crypto to traditional stores of value and, paradoxically, to DeFi platforms offering RWA exposure. This signals a maturation where utility and transparency are gaining ground over pure hype.
Identify protocols with demonstrable revenue generation from real-world use cases, like Hyperliquid, as potential outperformers. Focus on platforms that offer transparency and accountability, as market structure shifts towards more regulated and predictable venues.
The crypto market is undergoing a structural reset, moving away from a retail-driven, speculative cycle. Investors must adapt to a landscape where fresh capital is scarce, institutional flows favor gold, and DeFi's next frontier involves real-world assets.
The convergence of AI agents and programmable money is creating a new frontier for digital commerce and liability. This shift demands a proactive re-evaluation of regulatory frameworks, moving beyond human-centric definitions of accountability and transaction.
Builders should design AI agent systems with cryptographically embedded controls, allowing for granular policy enforcement (e.g., spending limits triggering human review) and leveraging stablecoins for microtransactions in decentralized agent-to-agent economies.
The next 6-12 months will see increasing pressure to define AI agent liability and payment rails. Investors should prioritize projects building infrastructure for secure, auditable agent commerce, while builders must integrate compliance and control mechanisms from day one to navigate this evolving landscape.
The economy is shifting from human-centric labor and scarcity to AI-driven abundance, where machine intelligence itself becomes the primary unit of economic exchange, challenging traditional monetary and employment structures.
Investigate and build "proof of control" solutions using crypto primitives (like ZKPs, TEEs, decentralized compute/storage) to secure AI agents and data.
The next 6-12 months will see increased demand for verifiable control over AI systems. Understanding how crypto enables this, and how human value shifts from transactional jobs to unique human interaction, is crucial for navigating this new economic reality.
