A16z's "big venture" model was based on two core ideas: first, that Marc Andreessen's "Software is Eating the World" thesis would create 10x more viable companies, and second, that founders required a superior VC "product" with platform services that only scale could provide.

Traditional valuation models assume growth decays over time. However, when a company at scale, like Databricks, begins to reaccelerate, it defies these models. This rare phenomenon signals an expanding market or competitive advantage, justifying massive valuation premiums that seem disconnected from public comps.

To build a multi-billion dollar database company, you need two things: a new, widespread workload (like AI needing data) and a fundamentally new storage architecture that incumbents can't easily adopt. This framework helps identify truly disruptive infrastructure opportunities.

During a fundamental technology shift like the current AI wave, traditional market size analysis is pointless because new markets and behaviors are being created. Investors should de-emphasize TAM and instead bet on founders who have a clear, convicted vision for how the world will change.

The current moment is ripe for building new horizontal software giants due to three converging paradigm shifts: a move to outcome-based pricing, AI completing end-to-end tasks as the new unit of value, and a shift from structured schemas to dynamic, unstructured data models.

The narrative of startups "destroying" incumbents is often wrong. As shown by MongoDB coexisting with Oracle and HubSpot with Salesforce, disruptive companies can create massive value by expanding the total market, allowing both new and old players to grow simultaneously.

Companies like Amazon (from books to cloud) and Intuitive Surgical (from one specific surgery to many) became massive winners by creating new markets, not just conquering existing ones. Investors should prioritize businesses with the innovative capacity to expand their TAM, as initial market sizes are often misleadingly small.

Consumer innovation arrives in predictable waves after major technological shifts. The browser created Amazon and eBay; mobile created Uber and Instagram. The current AI platform shift is creating the same conditions for a new, massive wave of consumer technology companies.

Investors err when they size a new market based on its predecessor (e.g., Uber vs. taxis). A fundamental supply-side change creates new capabilities that unlock massive, previously invisible demand, making initial market size calculations dangerously conservative.