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.

For AI-native products where the primary interface is just a prompt box, the traditional role of a growth team in optimizing activation diminishes. The entire activation experience happens via conversation with an AI agent, making it an inseparable part of the core product's responsibility, not a separate optimization layer.

Simply offering the latest model is no longer a competitive advantage. True value is created in the system built around the model—the system prompts, tools, and overall scaffolding. This 'harness' is what optimizes a model's performance for specific tasks and delivers a superior user experience.

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.

Instead of simply adding AI features, treat your AI as the product's most important user. Your unique data, content, and existing functionalities are "superpowers" that differentiate your AI from generic models, creating a durable competitive advantage. This leverages proprietary assets.

For years, Google has integrated AI as features into existing products like Gmail. Its new "Antigravity" IDE represents a strategic pivot to building applications from the ground up around an "agent-first" principle. This suggests a future where AI is the core foundation of a product, not just an add-on.

The best agentic UX isn't a generic chat overlay. Instead, identify where users struggle with complex inputs like formulas or code. Replace these friction points with a native, natural language interface that directly integrates the AI into the core product workflow, making it feel seamless and powerful.

Tools like Descript excel by integrating AI into every step of the user's core workflow—from transcription and filler word removal to clip generation. This "baked-in" approach is more powerful than simply adding a standalone "AI" button, as it fundamentally enhances the entire job-to-be-done.