Previously, building 'just a feature' was a flawed strategy. Now, an AI feature that replaces a human role (e.g., a receptionist) can command a high enough price to be a viable company wedge, even before it becomes a full product.

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Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.

Most companies use AI for optimization—making existing processes faster and cheaper. The greater opportunity is innovation: using AI to create entirely new forms of value. This "10x thinking" is critical for growth, especially as pure efficiency gains will ultimately lead to a reduced need for human workers.

The economic incentive for VCs funding AI is replacing human labor, a $13 trillion market in the US alone. This dwarfs the $300 billion SaaS market, revealing the ultimate goal is automating knowledge work, not just building software.

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.

The narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.

Instead of focusing on foundational models, software engineers should target the creation of AI "agents." These are automated workflows designed to handle specific, repetitive business chores within departments like customer support, sales, or HR. This is where companies see immediate value and are willing to invest.

The transition from AI as a productivity tool (co-pilot) to an autonomous agent integrated into team workflows represents a quantum leap in value creation. This shift from efficiency enhancement to completing material tasks independently is where massive revenue opportunities lie.

The paradigm shift with AI agents is from "tools to click buttons in" (like CRMs) to autonomous systems that work for you in the background. This is a new form of productivity, akin to delegating tasks to a team member rather than just using a better tool yourself.

In a world where AI makes software cheap or free, the primary value shifts to specialized human expertise. Companies can monetize by using their software as a low-cost distribution channel to sell high-margin, high-ticket services that customers cannot easily replicate, like specialized security analysis.

Unlike traditional software that supports workflows, AI can execute them. This shifts the value proposition from optimizing IT budgets to replacing entire labor functions, massively expanding the total addressable market for software companies.