Capabilities and Containers

As we implement AI features into our products, we need a mental model that helps make sense of this domain. A shared language is a starting point for sense making.

Capabilities are core actions that generative AI can accomplish and are usually represented as verbs. Examples include: summarise, create, retrieve, research, and interact. Capabilities are a bit like Jobs-To-Be-Done for AI.

Containers are parts of a user interface or architecture that extract, transform and load information. These include search bars, notes, wizards, and databases.

Capabilities are connected to containers in a many to many relationship. Thinking of AI features as capability-container modules that can be reused in different parts of an application, just like a design system does for user interfaces, helps drive business cases.

concepts

Capabilities applied to containers encourage transferability