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.

A new wave of startups, like ex-Twitter CEO's Parallel, is attracting significant investment to build web infrastructure specifically for AI agents. Instead of ranking links for humans, these systems deliver optimized data directly to AI models, signaling a fundamental shift in how the internet will be structured and consumed.

Enterprise AI vendors are moving beyond simple search or chat applications. The real value and defensibility lie in the underlying 'context engine' that connects and understands siloed company data, user activity, and permissions. This engine provides the accuracy and relevance that generic LLMs fundamentally lack.

Former OpenAI VP Peter Deng argues that as AI models become commoditized, differentiation will shift to product taste and intuitive workflows. He contends that success will hinge on a deep understanding of consumer desires, making the model itself less important than the user experience it enables.

The nascent AI agent ecosystem lacks effective discovery mechanisms for third-party tools ('skills'). This creates an opportunity for curated marketplaces that help users find, vet, and even pay for high-quality, trustworthy agent capabilities, solving a key bottleneck to adoption.

As AI model performance commoditizes, the strategic battleground is shifting from models to platforms. Tech giants like Google are positioning their offerings not as features, but as the fundamental 'operating system' for the agentic enterprise. The new competitive moat is the control plane that orchestrates agents.

Like Kayak for flights, being a model aggregator provides superior value to users who want access to the best tool for a specific job. Big tech companies are restricted to their own models, creating an opportunity for startups to win by offering a 'single pane of glass' across all available models.

AI search goes beyond the query itself; it considers what it knows about the user. For instance, it won't recommend a multi-million dollar enterprise solution to a mid-sized company. Brands must clearly signal their ideal customer persona so AI can make the correct match.

Unlike Google's ad-based model, future AI platforms like ChatGPT may vertically integrate and fulfill user requests directly. Instead of sending traffic to a real estate agent, the AI might become the real estate agent, capturing the entire value chain and eliminating the need for third-party businesses.