LLMs have hit a wall by scraping nearly all available public data. The next phase of AI development and competitive differentiation will come from training models on high-quality, proprietary data generated by human experts. This creates a booming "data as a service" industry for companies like Micro One that recruit and manage these experts.

Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.

Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.

As users delegate purchasing and research to AI agents, brands will lose control over the buyer's journey. Websites must be optimized for agent-to-agent communication, not just human interaction, as AI assistants will find, compare, and even purchase products autonomously.

The idea of a truly "open web" was a brief historical moment. Powerful, proprietary "organizing layers" like search engines and app stores inevitably emerge to centralize ecosystems and capture value. Today's AI chatbots are simply the newest form of these organizing layers.

Unlike chatbots that rely solely on their training data, Google's AI acts as a live researcher. For a single user query, the model executes a 'query fanout'—running multiple, targeted background searches to gather, synthesize, and cite fresh information from across the web in real-time.

The rise of AI agents means website traffic will increasingly be non-human. B2B marketers must rethink their playbooks to optimize for how AI models interpret and surface their content, a practice emerging as "AI Engine Optimization" (AEO), as agents become the primary researchers.

The next generation of social networks will be fundamentally different, built around the creation of functional software and AI models, not just media. The status game will shift from who has the best content to who can build the most useful or interesting tools for the community.

The future of AI is not just humans talking to AI, but a world where personal agents communicate directly with business agents (e.g., your agent negotiating a loan with a bank's agent). This will necessitate new communication protocols and guardrails, creating a societal transformation comparable to the early internet.