The Macro Shift: Insatiable AI demand meets the technical reality of rapidly depreciating model assets, pushing AI companies to prioritize infrastructure control and long-term capability scaling over short-term consumer-facing profitability.
The Tactical Edge: Invest in AI infrastructure plays (GPUs, energy, data centers) and companies building model-agnostic agentic systems, as these components offer more durable value than individual frontier models.
The Bottom Line: The market is underestimating the demand growth for increasingly capable AI models. Expect continued massive capex in compute, and position for a future where AI agents become indispensable, driving significant, sustained enterprise spend over the next 6-12 months.
AI's economic viability is shifting from model-specific gross margins to the long-term utility of persistent agents and the underlying compute infrastructure.
Invest in or build infrastructure plays (GPUs, energy, data centers) that support the insatiable demand for AI compute, recognizing that model software is a rapidly depreciating asset.
The market's recent "whiplash" on AI valuations misses the true demand growth and the strategic pivot towards infrastructure and long-running agents.
The AI industry is moving from a pure software-as-a-service model to a vertically integrated infrastructure play, where control over compute and power becomes the ultimate competitive advantage.
Invest in or build solutions that abstract away the underlying model, allowing for easy swapping between providers, while focusing on persistent agent memory and identity.
The market underestimates AI demand. Companies controlling infrastructure and delivering agents capable of sustained, high-value work will capture significant value over the next 6-12 months, even as model development costs remain high.
The AI industry is shifting from a pure software-like model to one where infrastructure ownership and continuous R&D are paramount.
Prioritize infrastructure investment: Given the GPU and energy constraints, securing or building proprietary compute infrastructure will be a decisive competitive advantage.
The next 6-12 months will see a continued capital expenditure arms race in AI infrastructure.
The AI industry is shifting from a software-like business model to one resembling capital-intensive infrastructure, where models are rapidly depreciating assets. This forces a focus on massive, continuous R&D and infrastructure buildout (GPUs, energy) to unlock future capabilities and markets, rather than immediate software-like margins.
Prioritize infrastructure investments. For builders, design systems with model agnosticism, allowing for easy swapping as models improve or become obsolete. For investors, evaluate AI companies not just on current gross margins, but on their ability to secure compute, attract top talent for R&D, and demonstrate a credible path to future market expansion through scale.
The next 6-12 months will see continued massive capital expenditure in AI infrastructure. Companies that can secure GPU supply and energy, while effectively managing the short lifespan of frontier models through continuous R&D, will hold a decisive competitive advantage. The market will increasingly reward long-term vision and infrastructure plays over short-term profitability.
If you look at how much they spent in R&D in the four months before they released GPT5, that quantity was likely larger than what they made in gross profits during the whole tenure of GPT5 and GPT5.2.
The models as a rapidly depreciating asset actually brings a little bit into focus of what might be the enduring asset... it seems to me that this part is infrastructure.
The market is always right... However, with that said, they didn't get the demand growth. They didn't get the way in which that demand is outstripping supply. They didn't get how much more we were going to demand as these models get better.
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.
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.
Bitcoin, once digital gold, is now frontier tech, vulnerable to broader tech sell-offs.
Reallocate capital towards crypto assets benefiting from regulatory clarity and innovation: stablecoins, tokenized assets, privacy, prediction markets, perpetual futures.
Bitcoin's short-term narrative is challenged, but its long-term tech thesis holds.
Real-time data platforms are supplanting traditional economic reporting, forcing investors to re-evaluate their information sources, while AI's capital expenditure is creating a bifurcation between infrastructure providers and speculative model companies.
Prioritize investments in blockchain infrastructure and stablecoin-centric payment solutions that cater to the emerging agentic economy, and leverage real-time data for a competitive information advantage.
The convergence of real-time data, AI agents, and blockchain rails will fundamentally alter market dynamics and value capture over the next 6-12 months, rewarding those who understand the shift from centralized, lagging systems to decentralized, optimized ones.
The Macro Shift: AI is fundamentally reshaping corporate IT spending, driving a strategic pivot from external SaaS subscriptions to internal development, which will consolidate profits within mega-cap tech and pressure traditional software vendors.
The Tactical Edge: Identify and invest in vertically integrated tech giants that can leverage AI for internal cost savings and new product development, while selectively shorting asset-heavy, midstream, or non-essential SaaS providers during strength.
The Bottom Line: The current market is a re-evaluation of fundamental value across tech and crypto. Focus on companies with strong internal demand for compute and real-world utility, and understand that crypto's speculative cycles, while volatile, are driven by a unique social dynamic that will persist.
