Permira differentiates in the crowded tech private equity space by targeting category-leading software companies. Their strategy focuses on doubling down on product investment to accelerate growth, rather than milking the business for short-term margin expansion.

Instead of building AI models, a company can create immense value by being 'AI adjacent'. The strategy is to focus on enabling good AI by solving the foundational 'garbage in, garbage out' problem. Providing high-quality, complete, and well-understood data is a critical and defensible niche in the AI value chain.

WCM avoids generic AI use cases. Instead, they've built a "research partner" AI model specifically tuned to codify and diagnose their core concepts of "moat trajectory" and "culture." This allows them to amplify their unique edge by systematically flagging changes across a vast universe of data, rather than just automating simple tasks.

During the dot-com crash, application-layer companies like Pets.com went to zero, while infrastructure providers like Intel and Cisco survived. The lesson for AI investors is to focus on the underlying "picks and shovels"—compute, chips, and data centers—rather than consumer-facing apps that may become obsolete.

In the current market, AI companies see explosive growth through two primary vectors: attaching to the massive AI compute spend or directly replacing human labor. Companies merely using AI to improve an existing product without hitting one of these drivers risk being discounted as they lack a clear, exponential growth narrative.

In a new, high-risk category, betting on infrastructure ('shovels') isn't necessarily safer. If the category fails, both app and infra lose. But if it succeeds, the application layer captures disproportionately more value, making the infrastructure a lower-upside bet for the same level of existential risk.

Instead of betting on which AI models or applications will win, Karmel Capital focuses on the infrastructure layer (neocloud companies). This "pick and shovel" strategy provides exposure to the entire ecosystem's growth with lower valuations and less risk, as infrastructure is essential regardless of who wins at the top layers.

The enduring moat in the AI stack lies in what is hardest to replicate. Since building foundation models is significantly more difficult than building applications on top of them, the model layer is inherently more defensible and will naturally capture more value over time.

Beyond AI infrastructure providers (NVIDIA, AWS), a key opportunity lies in the 'layer below'—companies like Uber and Spotify. They leverage big tech's tools but dominate specific verticals because they possess superior, niche-specific user data, which AI then supercharges for monetization and personalization.