The AI Economy Is Stabilizing

Key Concepts

• AI Economy Stabilization: The perceived settling of the economic landscape surrounding Artificial Intelligence.
• Model Layer Companies: Businesses focused on developing and providing foundational AI models (e.g., large language models).
• Application Layer Companies: Businesses building applications using existing AI models.
• Infrastructure Layer Companies: Businesses providing the hardware and supporting services for AI model training and deployment.
• AI-Native Companies: Companies built from the ground up leveraging AI as a core component.
• Incremental Improvement vs. Disruptive Advancement: The distinction between gradual model enhancements and revolutionary breakthroughs.

---

The Stabilization of the AI Economy in 2025

The speaker expresses significant surprise at the stabilization of the AI economy by 2025, contrasting it with the volatile and uncertain environment experienced at the end of 2024. At the close of 2024, the speaker describes a period of “incredibly rapid change” characterized by instability and unpredictability regarding the future of AI startups and the broader economy. There was a pervasive sense of anticipation for an unknown “other shoe to drop.”

However, by 2025, a more defined structure has emerged. The AI landscape now appears to be stratified into three distinct layers: the model layer, the application layer, and the infrastructure layer. This layered structure suggests a maturing market where the roles and potential for success are becoming clearer. The speaker believes that companies operating within each of these layers are positioned to achieve substantial financial success.

Layered Structure of the AI Economy

The speaker specifically outlines the three layers:

• Model Layer Companies: These entities focus on the core development and provision of AI models. This implies a concentration of resources and expertise in building the foundational technology.
• Application Layer Companies: These businesses leverage existing AI models to create specific applications and solutions. The speaker notes the emergence of a “relative playbook” for building these “AI-native companies,” suggesting standardized approaches and best practices are developing. This indicates a reduction in the initial uncertainty surrounding how to effectively utilize AI in new ventures.
• Infrastructure Layer Companies: This layer provides the essential hardware and services required to support the training and deployment of AI models. This includes computing power, data storage, and related technologies.

Incremental Model Improvement & Lack of Disruptive Breakthroughs

The stabilization isn’t attributed to a single, dramatic advancement in AI. Instead, the speaker emphasizes that the improvements in AI models throughout 2025 have been “incrementally” rather than “major steps forward.” This is a crucial point: while models have gotten better, there hasn’t been a revolutionary breakthrough that fundamentally altered the landscape. The speaker states, “the models themselves have incrementally improved this year, but there haven't been like major steps forward that have shaken everything.” This suggests the stability stems from a consolidation around existing capabilities rather than a sudden leap in performance.

Implications for AI-Native Companies

The emergence of a “playbook” for building AI-native companies is a key indicator of the market’s maturation. This implies that the initial experimentation and uncertainty surrounding AI integration have subsided, and more predictable paths to success are becoming apparent. The speaker’s observation that “everyone is going to make a lot of money” suggests a widespread expectation of profitability across the AI ecosystem.

Synthesis

The primary takeaway is that the AI economy, after a period of intense volatility, has entered a phase of relative stability in 2025. This stabilization is characterized by a layered market structure, the emergence of best practices for AI-native companies, and incremental improvements in AI models rather than disruptive breakthroughs. The speaker’s perspective suggests a shift from a period of exploration and uncertainty to one of consolidation and predictable growth within the AI landscape.