My work has moved between contexts that rarely share a designer: clinical trial software, a travel company growing into new markets, a parenting programme moving online, a laboratory system, a fleet of autonomous robots, and a design organisation inside a delivery business.
From the outside this can look like range for its own sake. From the inside it is one piece of work done in different materials.
In each case the work started the same way. Several people held a picture of the same thing, a product, a programme or a process, and each picture was reasonable and slightly different. The first thing I made was one version everyone could see: a model, a set of flows, a diagram of who does what and when. The design came from there.
For a charity running a randomised trial, that picture was a diagram of the trial and the data model behind it, and it stopped the trial changing shape depending on who was in the room. For a robotics company, it was the flows and permissions that described what an autonomous fleet does and who may step in. For a laboratory system, it was a hierarchy rebuilt around the sample. For a brand, it was an agreed account of what the company is now and what it is becoming.
What each context sharpens
The move is the same everywhere. Each context teaches a different reason it matters, and a different way it fails.
Clinical research taught exactness. When a screen records evidence for a trial, the shared picture has to be precise enough to survive an audit, and a blank field and an uncertain answer mean different things to the study. That instinct now runs through my work on AI, where a system’s confidence and its accuracy have to be kept apart.
Commercial work taught speed and consequence. A shared picture is only useful if teams can act on it this quarter, and its value shows quickly in adoption, support load and the decisions it makes easier. Commercial pressure is good at exposing pictures that are elegant and unused.
Social programmes taught legibility for the people with the least power in the system. A parent joining a group online, a facilitator with a full caseload and a funder reading a report each have to be able to read the picture in their own terms, or it belongs only to whoever drew it.
Technical systems taught that the picture has to include the machine’s side. An autonomous fleet or an AI assistant has its own view of the world, built from what it has observed and what it infers, and a picture that leaves that out describes only the humans.
What travels
Artefacts rarely transfer cleanly. A permissions model from robotics will not fit a charity, and a measurement framework from e-commerce will mislead a parenting programme. What travels is the set of questions underneath them: who has to trust this, what would count as it working, what the system claims about the people it serves, and what has to change around it for the work to hold.
Each context also has its own way of going wrong, and moving between them makes those easier to see. Commercial work can mistake value for growth. Social work can mistake care for caution. Technical work can mistake a model of the system for the system itself. Crossing between them keeps any one of those from settling in as common sense.
That is the case for range in a design practice. The move stays constant, and each context keeps it honest in a different way.
The shared picture works much as Star and Griesemer described boundary objects: plastic enough to serve each group’s needs, and robust enough to keep a common identity across them. Schön’s reflective practitioner names the habit of reframing a problem through the situation in hand, and Epstein’s case for range argues that breadth sharpens judgement in environments that do not repeat neatly.
My own claim is only a practitioner’s account: the one move that crosses contexts intact, and the different property of it that each context teaches.