The AI industry is transitioning from a model-centric competition to an infrastructure and agent-centric one, where raw compute and persistent user experience dictate long-term value.
Prioritize investments in AI infrastructure providers and platforms that enable model agnosticism and agent memory.
Expect continued massive capital expenditure in AI infrastructure, a focus on enterprise solutions, and the rise of "sticky" AI agents that abstract away underlying model changes, shifting the competitive battleground.
The AI industry is moving from a software-like model, where products have long lifespans, to one where models are rapidly depreciating assets requiring continuous, heavy R&D investment.
Prioritize investments in AI infrastructure and agent orchestration layers that abstract away underlying models.
The market is underestimating the demand growth for increasingly capable AI models.
The Macro Shift: AI models are rapidly depreciating software assets, making the underlying compute and energy infrastructure the enduring value proposition.
The Tactical Edge: Prioritize building model-agnostic agentic workflows that retain memory and context, allowing for flexible model swapping and cost optimization.
The Bottom Line: The AI race is a capital-intensive marathon where infrastructure ownership and a long-term vision for capability expansion, not immediate model profitability, will determine market leadership over the next 6-12 months.
Invest in companies building core AI infrastructure (GPUs, energy, data centers) or those developing enterprise-grade AI agents that deliver measurable, long-duration value, rather than consumer-focused models with short lifespans.
The AI industry is moving from a software-like gross margin business to an infrastructure-heavy, capital-intensive play where sustained R&D investment is a prerequisite for market relevance, not just growth.
The market's recent jitters about AI capex miss the point: demand for increasingly capable AI is outstripping supply.
Prioritize investments in AI infrastructure plays (GPUs, energy, data centers) and companies building model-agnostic agent layers.
The market is underestimating the insatiable demand for increasingly capable AI, which will drive massive compute spend and make infrastructure the true bottleneck and value driver over the next 6-12 months.
Insatiable demand for ever-improving AI capabilities is driving unprecedented compute spend, but the true long-term value shifts from rapidly depreciating models to the underlying, enduring infrastructure and the persistent "memory" of AI agents.
Invest in or build solutions that abstract away the underlying model, focusing on agentic memory and robust infrastructure. This future-proofs against model obsolescence and capitalizes on the growing demand for persistent AI workers.
The market's recent "whiplash" on AI valuations misses the core truth: demand for advanced AI is outstripping supply. Companies that can build or secure infrastructure and develop sticky, agent-based experiences will capture significant value over the next 6-12 months, despite current profitability questions.
The AI industry is reorienting from a model-centric race to an infrastructure and agent-centric value proposition, where delivering persistent, high-value AI workers will outweigh the transient superiority of any single model.
Invest in or build solutions that abstract away the underlying LLM, focusing on agentic memory, workflow integration, and robust infrastructure.
The next 6-12 months will see a continued re-evaluation of AI valuations, favoring companies that demonstrate a clear path to monetizing agentic capabilities and owning critical compute infrastructure, rather than just shipping the "next best model."
The memory aspect of semiconductors today has gotten so extreme. Stuff is so expensive that people are simply not able to make lower-end equipment or like devices anymore. And this is like killing everything, right?
AI chips deliver 65% operating margins, exceeding gaming GPUs' 40%. This incentivizes NVIDIA to prioritize AI data center chips.
Meta's AI investments directly improve its core advertising business, generating substantial revenue from 3.5 billion users. This makes AI capex a straightforward investment.
Investigate platforms offering regulated perpetual futures on traditional assets. These venues are positioned to capture significant institutional flow by combining crypto's product innovation with TradFi's risk management.
The global financial system is bifurcating, with a clear trend towards regulated, institutional-grade venues for all tradable assets, including novel ones like compute power.
The future of finance involves crypto-native products like perpetuals, but their mass adoption by institutions hinges on robust regulation and superior risk management.
The Macro Shift: AI's productivity gains are consolidating power and profits within vertically integrated tech giants, fundamentally altering the competitive landscape for software and infrastructure providers.
The Tactical Edge: Re-evaluate SaaS investments, favoring mega-cap tech companies poised to absorb former SaaS revenues through internal AI-driven development. For crypto, identify and accumulate projects with genuine revenue generation during the bear market.
The Bottom Line: Position your portfolio for a world where AI drives corporate insourcing, crypto valuations reset to fundamentals, and core digital assets like Bitcoin undergo necessary technical upgrades to survive future threats.
Traditional finance is integrating with crypto, but often on its own terms, demanding more transparency from protocols while VCs continue to deploy significant capital into specific, high-potential crypto and AI intersections.
Scrutinize institutional "partnerships" for concrete terms and evaluate protocols based on their true moat against easy forks or platform risk.
The market is bifurcating: clear regulatory wins for specific crypto applications (like prediction markets) and innovative AI/crypto plays are attracting capital, while opaque TradFi deals and general L1 infrastructure face increased scrutiny. Position for clarity and genuine value accrual.
The digitization of finance is accelerating, with institutional capital now actively seeking onchain yield and efficiency. This is creating a competitive pressure cooker for traditional banks, while opening vast opportunities for nimble DeFi protocols.
Focus on protocols building robust RWA infrastructure and those providing deep liquidity for tokenized treasuries. These are the picks and shovels for the coming institutional capital wave.
The fight for stablecoin yield and institutional adoption will define the next 6-12 months. Position yourself to capitalize on the inevitable flow of capital from TradFi to transparent, yield-bearing onchain assets, even if it's just a fraction of the total.
Explore DeFi protocols in the N7 index (Morpho, Frax, Aave, etc.) for early exposure to institutional capital flows and RWA looping opportunities.
Experiment with AI agents to automate content creation, research, and even software development, drastically cutting operational costs.
The financial system is bifurcating into a "Neo Finance" layer where tokenized real-world assets are integrated with DeFi primitives, and an "AI-augmented" layer where autonomous agents supercharge individual and small team productivity.
Bittensor is transitioning from a purely experimental decentralized AI network to a performance-driven marketplace, demanding real-world utility and robust economic models from its subnets.
Builders launching subnets must secure initial TAO liquidity and a clear, executable product roadmap from day one to navigate the competitive landscape and achieve emission.
The network's continuous adaptation, from chain buys to MEV mitigation, signals a commitment to long-term stability and value.
