Bitcoin, Software Repricing, and the AI-Driven Market Rotation

Summary

The February 07, 2026 episode of the Anthony Pompliano Podcast features Jordi Visser arguing that Bitcoin’s recent drawdown reflects a broader repricing of software and long-duration assets rather than a collapse in Bitcoin’s core thesis. Visser contends that institutional hedging tied to private SaaS exposure, combined with structural AI disruption, has tightened Bitcoin’s short-term correlation with software equities. He frames 2026 as a pivotal year in which stablecoin utility, tokenization, and AI-driven capital rotation could reshape how markets value both Bitcoin and legacy enterprise models.

Take-Home Messages

1. Cross-Asset Correlation: Bitcoin is currently trading in close alignment with software equities, making institutional positioning a key driver of short-term volatility.
2. Institutional Hedging Flows: Private SaaS markdowns may push funds to hedge via liquid instruments like Bitcoin, amplifying price swings unrelated to fundamentals.
3. Utility Growth Signals: Rising stablecoin volumes indicate expanding payment and settlement activity even during price weakness.
4. AI-Induced Repricing: AI-native firms and agent-based workflows threaten legacy enterprise software multiples and redirect capital toward hardware and energy.
5. Divergence as a Signal: A decoupling of Bitcoin from weak software equities could indicate the unwind of hedges and a shift toward utility-based valuation.

Overview

Jordi Visser situates Bitcoin’s recent price decline within a broader repricing of long-duration technology assets, arguing that it cannot be analyzed in isolation from traditional financial markets. He notes that year-to-date declines in major software indices have closely tracked Bitcoin’s performance, suggesting that the same capital flows influencing software equities are also shaping Bitcoin’s trajectory. In his view, the narrative of a Bitcoin-specific failure misses the institutional mechanics at work.

He argues that private SaaS exposure accumulated during the venture boom years is now being marked down, creating pressure across both public and private balance sheets. Visser suggests that some institutions may hedge illiquid private positions with liquid, correlated assets such as Bitcoin, effectively embedding Bitcoin within a broader cap-structure adjustment process. This linkage, he implies, explains why Bitcoin can fall in tandem with software even when its long-term monetary thesis remains unchanged.

At the same time, Visser highlights expanding stablecoin volumes as evidence that transactional utility is accelerating, with network effects strengthening as payment flows scale. He references tokenization and regulatory progress as additional catalysts that could broaden institutional participation and formalize digital asset integration into traditional finance. These developments, he argues, reflect structural growth that may matter more over time than short-term price fluctuations.

The conversation then shifts to artificial intelligence, where Visser contends that AI agents and AI-native enterprises are challenging the economics of legacy enterprise software. He frames this as part of a broader capital rotation toward hardware, semiconductors, energy, and infrastructure required to support AI compute. In that context, Bitcoin’s near-term volatility may reflect its current classification as a high-beta technology asset, even as its longer-term role evolves alongside structural economic change.

Stakeholder Perspectives

1. Bitcoin Investors: Assess whether current volatility reflects temporary correlation and hedging flows rather than a deterioration in Bitcoin’s underlying adoption trends.
2. Asset Managers and Hedge Funds: Evaluate Bitcoin’s role as both a portfolio hedge and a source of liquidity when private technology valuations are under stress.
3. Pension Funds and Endowments: Reconsider exposure to long-duration private assets and the potential spillover effects on liquid markets.
4. Regulators and Legislators: Monitor how regulatory clarity around tokenization and stablecoins could expand participation while also reshaping systemic risk channels.
5. Enterprise Technology Firms: Confront margin compression and competitive disruption as AI-native workflows challenge traditional software models.

Implications and Future Outlook

If Bitcoin remains tightly correlated with software equities, portfolio mechanics and institutional hedging behavior may continue to dominate short-term price action. In that scenario, monitoring liquidity conditions and private-market markdowns becomes as important as tracking on-chain activity. A sustained divergence between Bitcoin and weakened software stocks would signal a structural shift in how markets classify and value Bitcoin.

The expansion of stablecoin payment volumes suggests that transactional use cases are gaining traction regardless of price volatility. As tokenization frameworks mature and regulatory clarity improves, more financial flows may migrate onto digital rails, potentially reinforcing Bitcoin’s broader ecosystem. Policymakers will need to balance innovation incentives with safeguards that address cross-market contagion risks.

The AI-driven restructuring described by Visser implies that value capture is shifting toward hardware, energy, and compute infrastructure, while legacy enterprise models face pressure. Over the next three to five years, this reallocation could reshape capital markets, labor demand, and corporate spending priorities. In that environment, Bitcoin’s perceived role may oscillate between high-volatility risk asset and maturing monetary network, depending on whether utility growth outpaces correlation-driven flows.

Some Key Information Gaps

1. Under what conditions could Bitcoin decouple from software sector correlations? Clarifying decoupling thresholds is essential for portfolio construction and for understanding when Bitcoin begins to trade on monetary fundamentals rather than technology beta.
2. How significant is institutional hedging of private SaaS exposure in influencing Bitcoin liquidity flows? Quantifying this mechanism would improve systemic risk modeling and help distinguish structural adoption from balance-sheet-driven volatility.
3. Will AI-native enterprises structurally reduce demand for traditional enterprise platforms? Answering this informs expectations about capital rotation, employment shifts, and the durability of legacy technology valuations.
4. Can stablecoin volume growth translate into sustained demand for underlying settlement assets? Determining whether transactional scaling supports long-term monetary premium is central to evaluating ecosystem resilience.
5. What indicators reliably signal when correlation-volatility breakdowns foreshadow broader market stress? Improved early-warning models could help investors and regulators anticipate cross-asset contagion.

Broader Implications for Bitcoin

Cross-Asset Monetary Transmission

If Bitcoin continues to move in tandem with technology equities during stress periods, it becomes embedded in global liquidity cycles rather than operating as a fully independent asset class. This linkage could amplify cross-border capital flow volatility, particularly where institutions hold concentrated private technology exposure. Over the next several years, the strength or weakening of this transmission channel will shape whether Bitcoin evolves toward a distinct monetary role or remains tied to broader risk-on dynamics.

Digital Settlement Infrastructure Expansion

Rising stablecoin volumes point toward a gradual migration of payment and settlement functions onto blockchain-based rails. As these rails scale, governments and financial institutions may face increasing pressure to modernize legacy systems or integrate hybrid models that combine traditional oversight with decentralized infrastructure. This transition could redefine how cross-border payments, remittances, and capital controls operate in practice.

AI-Driven Capital Reallocation and Energy Demand

The redirection of capital toward compute, energy, and infrastructure to support AI growth has implications beyond equity valuations. Greater energy demand for data centers and edge computing could intersect with Bitcoin mining strategies, reshaping how grids balance industrial loads and monetize excess capacity. Policymakers and market participants will need to anticipate how these overlapping demands influence energy pricing, grid resilience, and long-term infrastructure investment.

Institutional Portfolio Architecture Under Strain

As private-market exposures and long-duration assets reprice, institutional investors may increasingly rely on liquid proxies to manage risk. This practice can transmit shocks rapidly across asset classes, including Bitcoin, and complicate traditional diversification assumptions. Over time, institutions may need to redesign portfolio frameworks to account for tighter cross-asset correlations in an AI-accelerated economy.

Monetary Identity in an AI-Native Economy

If AI agents increasingly mediate commerce and capital allocation, monetary systems will adapt to machine-driven transaction environments. Bitcoin’s predictable issuance and programmatic settlement features could become more relevant in a world where automated systems prioritize reliability and neutrality. The next several years may reveal whether Bitcoin can transition from a correlated technology asset to a foundational monetary layer within AI-mediated markets.