Venture capital lionizes companies with immediate, steep growth ("high slope"). However, many of the most significant, defensible companies like Figma are "area under the curve" stories. They endure a long build phase before emerging as dominant, creating more long-term value than companies with fast but less defensible growth.

In an era of rapid technological shifts, durable value comes not from steady revenue growth but from a founder's capacity to reinvent the company repeatedly. Databricks' CEO Ali Ghodsi exemplifies this by successfully navigating multiple S-curves, which is the true driver of long-term success.

Just as Kaizen and “China cost” revolutionized physical product businesses over 40 years, AI is initiating a similar, decades-long optimization cycle for intellectual property and human-centric processes. Companies that apply this “digital Kaizen” to lean out workflows will gain a compounding cost and efficiency advantage, similar to what Danaher achieved in manufacturing.

Cognizant frames AI adoption across three maturing vectors: 1) Hyper-productivity for automating tasks, 2) Industrializing AI by embedding it in core workflows, and 3) Re-identifying the Enterprise, where AI agents become collaborative partners for complex, cross-functional work.

Because machine vision is integrated early in new manufacturing line build-outs, Cognex's business often inflects before the public knows what new product or feature is driving the capital expenditure. This makes the company a bellwether for innovation cycles at giants like Apple.

Significant disruption often comes from applying mature technologies in novel contexts, not just from new inventions. Gaonkar points to 1970s lithium-ion batteries revolutionizing EVs and old gaming GPUs now powering the AI boom as prime examples of this powerful investment thesis.

The current wave of AI companies is growing at unprecedented rates, far outpacing the growth curves of the mobile, social, or SaaS eras. They are becoming larger and more consequential much faster, a phenomenon described as "speed running the process of company growth."

Cognex focuses on sophisticated, top-tier customers with complex needs, requiring a highly technical sales process. In contrast, market leader Keyence targets the mid-to-low tiers with standardized products and a high-velocity, process-driven sales force, allowing both to thrive.

Cognex deploys complex 'deep learning' for nuanced tasks humans once performed, opening new applications. Simultaneously, it uses simple 'edge learning' that customers can train with a few images. This second approach opens a new, less sophisticated customer segment previously out of reach.