AI adoption is not limited to tech and white-collar work; it has become a universal business consideration. For example, a lumber mill in Vermont is using AI to sort planks, a task for which they struggled to hire skilled labor. This shows AI is being deployed as a practical solution to specific, localized labor shortages in legacy industries.

Instead of selling software to traditional industries, a more defensible approach is to build vertically integrated companies. This involves acquiring or starting a business in a non-sexy industry (e.g., a law firm, hospital) and rebuilding its entire operational stack with AI at its core, something a pure software vendor cannot do.

Legacy industries are often slow to adapt due to inertia and arrogance, creating massive opportunities. Flexport built a simple duty calculator in three days that the entire trade industry adopted, proving that a startup's key to success can be entering a field where competitors are technologically complacent.

The primary economic incentive driving AI development is not replacing software, but automating the vastly larger human labor market. This includes high-skill jobs like accountants, lawyers, and auditors, representing a multi-trillion dollar opportunity that dwarfs the SaaS industry and dictates where investment will flow.

A core skill in process automation, honed in early robotics and enterprise integration, can be the unifying driver of a career. This focus provides a consistent framework for innovation and problem-solving, even when pivoting into a complex new domain like healthcare data.

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.

Instead of creating a tech sector from scratch, the most effective path is to identify and invest in tech niches adjacent to a city's existing industries (e.g., Energy Tech for an oil town). This leverages existing talent, infrastructure, and supply chains, making the transition more natural and sustainable.

Traditionally, service businesses lack scalability for VC. But AI startups are adopting a 'manual first, automate later' approach. They deliver high-touch services to gain traction, while simultaneously building AI to automate 90%+ of the work, eventually achieving software-like margins and growth.