Make the system understandable
People need to know what a product is doing and what it expects from them. This is especially important when an AI system produces an answer that looks confident but may be incomplete.
Show the context behind a suggestion. Distinguish an estimate from a confirmed fact. Give uncertainty a visible place in the interface instead of hiding it in a footnote.
Keep people in control
Automation should make a person more capable, not make their choices disappear. Meaningful review, editable outputs, and clear undo paths make it easier to use a system with confidence.
Not every action needs the same level of friction. A reversible formatting change and a consequential external action deserve different interaction patterns. Design that distinction intentionally.
Design the difficult moments
The quality of a product is often clearest when a connection fails, an input is missing, or the result is unexpected. Explain what happened in plain language. Preserve the person’s work. Offer a useful next step.
Trust grows through these ordinary moments. It is the accumulated experience of a product behaving predictably, respecting attention, and helping someone move forward.