AI-native
An AI-native product is built around what a model can do, rather than having AI added to a product designed without it. The model's strengths and limits shape the workflow, the interface and the data from the start.
What it means
The difference shows in the first design decisions. An AI-enabled product adds a feature, such as a chat box or a summary button, to a workflow that was designed without it. An AI-native product starts from the question of where judgement is needed and designs the workflow around the model doing that part, with the rest handled by ordinary software.
AI-native doesn't mean everything is a model. The best AI-native products use a model only where it earns its place, and rules, forms and good interfaces everywhere else, because rules are cheaper, faster and easier to test.
How we use it
Our method We call ourselves an AI-native product and venture studio, and in practice that means deciding where a model earns its place before we design anything. We're as likely to recommend rules. In apprn, our salon venture, the product's spine is one verified event, not a model, and AI goes only where judgement helps.
Related terms
Published 28 September 2026. All terms