Memory & Cognition

Rules for reducing unnecessary mental work, supporting recognition, preserving context, and helping users build reliable expectations about the system.

Every interface asks the user to perceive information, hold some of it temporarily, connect it to prior knowledge, and decide what to do next. Problems appear when the product makes the user remember information the system already knows, infer hidden state, translate inconsistent terminology, or reconstruct relationships that could have remained visible.

Layr should treat cognitive effort as a budget. Some of that budget belongs to the user's real task: comparing investments, configuring infrastructure, reconciling records, diagnosing a production incident. The product adds avoidable cost when its own structure, language, sequencing, or state management becomes another problem to solve.

This category therefore emphasizes externalized context, coherent concepts, recognition over recall, and stable mental models. It also includes explicit safeguards against common misuse of psychological research, especially rigid interpretations of Miller's Law.

Cognitive design is the management of information across time. A user may see the correct data and still struggle because it appears too early, disappears too soon, uses unstable names, or requires several pieces to be combined mentally. Layr should therefore inspect not only what is present on one screen but also what must survive navigation, interruption, comparison, and state changes.

A useful distinction for agents is between domain thinking and interface thinking. Domain thinking is the reasoning the user came to perform: evaluating a tradeoff, diagnosing a problem, configuring a policy. Interface thinking is work created by the product: remembering hidden values, translating terminology, reconstructing state, or figuring out which component owns which action. Layr should preserve necessary domain thinking while reducing avoidable interface thinking.

• What information must the user remember instead of simply seeing it?
• Does the product use stable names and behaviors for the same concepts?
• Can users understand how objects relate and predict what an action will do?
• Are long or complex information sets organized into meaningful chunks?
• Does the design reduce avoidable reasoning without hiding information required for a correct decision?