$ Technology Investment Principles

The largest technology platforms possess structural advantages that are often amplified by the rise of AI, making them crucial core holdings:

Network Effects at Scale: Their vast user bases create self-reinforcing growth loops, making their services increasingly indispensable.

Data Moats & AI Flywheels: Unparalleled access to data fuels superior AI model training, leading to better products, attracting more users, generating more data—a powerful competitive cycle.

Massive R&D and Compute Resources: They can fund the enormous investments required for cutting-edge AI research, talent acquisition, and specialized hardware.

Ecosystem Control & Distribution: Integrated product suites and control over app stores/marketplaces create high switching costs and ensure efficient distribution of new AI features.

Regulatory Navigation Capacity: While facing scrutiny, they possess the resources to manage complex global regulations, which can act as a barrier to smaller competitors.

These factors create durable competitive advantages likely to sustain growth and profitability over long time horizons.

The goal is to identify companies exhibiting the durable characteristics of platform dominance. While the specific leaders may evolve over decades, key attributes to look for include:

• Clear market leadership in large, growing digital sectors (e.g., cloud computing, digital advertising, e-commerce, social networking, productivity software).

• Demonstrated ability to leverage network effects and build strong ecosystems.

• Significant investment in and successful integration of AI into core products.

• Robust free cash flow generation funding continued innovation and shareholder returns.

• Management teams with a proven track record of long-term strategic thinking.

Illustrative Examples (as of early 2025): Companies like Alphabet (GOOGL), Amazon (AMZN), Microsoft (MSFT), and Meta Platforms (META) currently exemplify many of these characteristics.

Focusing on these underlying attributes rather than just current market darlings provides a more timeless framework for selecting the platform side of the barbell.

AI isn't just another feature; it reinforces the core strengths of dominant platforms:

Enhanced Moats: AI leverages platform data to improve products and personalization, further solidifying user lock-in.

Operational Efficiency: AI optimizes internal operations, logistics, and infrastructure management at scale.

New Revenue Streams: AI enables entirely new services and capabilities that can be monetized across vast user bases.

Competitive Barriers: The cost and complexity of developing and deploying cutting-edge AI create significant barriers to entry, favoring incumbents.

Platforms are positioned not just to *use* AI, but to *define* how AI is deployed and monetized across the economy, capturing a disproportionate share of the value created.

Direct investing in individual startups is high-risk and requires significant expertise. Gaining exposure systematically through platforms or funds is generally preferable:

Syndicates & Rolling Funds: Platforms (like those pioneered by AngelList) allow investment alongside experienced VCs or domain experts, providing curated deal flow and diversification via smaller checks into many companies.

Accelerator Funds: Investing in funds focused on top accelerator batches (like Y Combinator) offers broad exposure to a portfolio of vetted early-stage companies.

Thematic Venture Funds: Specialized funds targeting specific sectors (e.g., AI infrastructure, biotech, climate tech) provide expert curation and diversification within a chosen area.

Equity Crowdfunding Portals: These platforms democratize access but require careful diligence due to variable quality. They can occasionally surface unique opportunities.

These approaches help manage risk through diversification and leverage expert selection, making venture investing more accessible and systematic.

When evaluating ventures (directly or selecting funds/syndicates), look for characteristics suited to the current environment:

Capital Efficiency via AI: Does the business model inherently leverage AI/automation to achieve significant output or scale with a lean team and minimal capital? This is a key differentiator today.

Strong Technical Founding Team: Especially in AI-driven businesses, deep technical expertise and understanding within the core team are crucial.

Clear Problem/Solution Fit: Does the venture solve a real, significant pain point in a way that delivers demonstrable value? Early traction or user engagement is a strong indicator.

Adaptability & Learning Capacity: The landscape changes rapidly. Teams that can learn, pivot, and adapt quickly are more likely to succeed than those rigidly attached to an initial plan.

Sustainable Advantage: How will the venture build defensibility? This could be through unique data, network effects (even niche ones), proprietary technology, or deep domain expertise.

Focusing on these attributes helps identify startups positioned not just to exist, but to thrive by leveraging modern technological capabilities effectively.

AI and modern tools also enable highly profitable, sustainable businesses that may not target hyper-growth or venture exits:

Micro-SaaS & Niche Tools: Small, focused software products serving specific needs can be highly profitable with very small teams.

AI-Augmented Services: Small expert teams using AI can deliver high-value services (consulting, creative, technical) with unprecedented efficiency.

Acquisition Entrepreneurship: Buying and optimizing existing small digital businesses leverages technology for improvement rather than starting from scratch.

Investing in or supporting these businesses (potentially through advisory work) offers diversification and aligns with the trend of achieving more with less via technology leverage, even if they don't fit the traditional VC mold.

Implementing the barbell strategy involves balancing the two distinct asset types:

Strategic Allocation: Weight the portfolio significantly towards dominant platforms (e.g., 60-80%) for stability and compounding growth, with a meaningful allocation (e.g., 20-40%) to diversified early-stage ventures for asymmetric upside potential. The exact split depends on individual risk tolerance and time horizon.

Diversification Within Poles: Avoid over-concentration even in platforms; diversify across several leading companies exhibiting the desired characteristics. For ventures, diversification across stages, sectors, and vintage years (investing consistently over time) is crucial.

Liquidity Awareness: Recognize the difference: platform stocks are generally liquid, while venture investments are illiquid for many years. Ensure the structure meets overall liquidity needs.

Disciplined Rebalancing: Periodically adjust allocations to maintain the target risk profile, but allow successful investments room to grow, balancing risk management with capturing long-term gains.

This structure aims to capture steady growth from established leaders while participating in the high-variance potential of disruptive innovation.

The two ends of the barbell have different primary risks:

Platform Risks:

• Regulation: Antitrust, privacy, and AI-specific regulations pose ongoing threats.

• Disruption: Vulnerability to paradigm shifts (though AI currently favors them).

• Valuation Risk: Mature growth rates may not support historically high multiples indefinitely.

• Execution/Capital Allocation: Missteps in large acquisitions or new ventures.

Venture Risks:

• Binary Outcomes: High probability of failure (total loss) for any single investment.

• Market/Execution Failure: Teams may fail to find product-market fit or execute effectively.

• Funding Dependency: Reliance on future funding rounds in volatile capital markets.

• Illiquidity: Long, uncertain time horizons before potential exits.

The barbell strategy inherently diversifies across these different risk types.

The strategy combines two different return generation models:

Platforms (Compounding Growth): Expected returns driven by sustained revenue growth (albeit moderating over time), potential margin expansion, and capital returns (buybacks/dividends). Aims for consistent, above-market compounding over decades.

Ventures (Power Law Returns): Returns follow a power-law distribution: the vast majority of gains come from a very small number of massive winners (e.g., >20x returns), offsetting the losses from the many failures. The portfolio relies on hitting a few home runs.

Combining these aims for a portfolio with resilience derived from the platforms and significant upside potential driven by the ventures, targeting strong absolute returns over the long term.