(Illustrated above) An architect’s cursor snaps to the edge of a form that she is trying to enclose in her building modeling application. Since she is familiar with the tool’s behaviors, she anticipates the correction and, as a result, spends less time positioning her cursor accurately.

A financial trader is booking a deal in his trading application. As he fills in data, the application predicatively defaults subsequent fields, which he then simply tabs through if he agrees with the values that the system has entered.

A scientist selects a different filter for a graph within her analysis application, and the transformed representation of clinical data instantly appears. Without the application’s automation of the graphing operations needed to update this display, the resulting transformation would have taken significant time and effort to manually complete.

What discrete operations in the work practices that your team is striving to mediate are standard, exacting, and tedious? What do targeted individuals think of these operations?

Where might your team’s sketched functionalities introduce new operations that could also fit the standard, exacting, and tedious description?

Which operations in your concepts for work mediation might be usefully automated under the general goal of reducing users’ efforts?

What larger design and technology trends could influence your team’s ideas about small automations in your computing tool?

What predictive actions, useful suggestions, slight corrections, and refined interface tailoring could your application concepts automatically provide?

How might these automated operations reduce the incidence of predictable errors and corrective interactions? How could the design of these features relate to your products’ larger error prevention and handling approaches?

Could certain small automations benefit from clearly communicated conceptual models, or could some of them provide just as much value if they are typically overlooked?

How might your envisioned automations impact workers’ sense of control? In what cases might targeted individuals see these automations as unpredictable or distracting nuisances?

What interaction methods could allow users to recognize and override the effects of certain automations?

What settings and customization functionality can your team envision to help ensure that automations will operate in accordance with workers’ goals? How could these settings be clearly and contextually accessed?

Do you have enough information to usefully answer these and other envisioning questions? What additional research, problem space models, and design concepting could valuably inform your team’s application envisioning efforts?