AI Native
What does AI native mean?
AI native refers to companies or products that are built from the ground up with AI as a core component of their architecture and value proposition, rather than adding AI capabilities to existing products. AI native companies design their entire product experience and business model around what AI makes possible, representing a fundamentally different approach than traditional companies adding AI features.
How do AI native products differ from products with AI features?
The distinction lies in architecture and design philosophy. Products with AI features start with an existing product built on traditional software principles and then add AI capabilities on top. AI native products begin with AI as a foundational element—the entire product architecture, user experience, and value proposition are designed around what AI enables.
For example, tools like Cursor (an AI-powered code editor) and Devin (an autonomous AI software developer) are AI native because the product couldn't exist without AI at its core. In contrast, a traditional code editor that adds an AI autocomplete feature is augmenting an existing product rather than being AI native.
Why does the AI native distinction matter?
AI native companies face different product development challenges and opportunities than companies adding AI to existing products. AI native teams must solve problems like building effective evals from scratch, designing entirely new user interaction patterns, and creating business models that didn't exist before AI. Meanwhile, traditional companies adding AI must balance new AI capabilities with existing product architectures, user expectations, and established workflows. Both paths require different strategies, skills, and mindsets.
Learn more:
- Building AI Products - All Things Product Podcast with Teresa Torres & Petra Wille
- Debugging AI Products: From Data Leakage to Evals with Hamel Husain
- Building Alyx: How Arize AI Dogfooded Its Way to an Agentic Future
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