Evidence versus assumption
What is known from research, analytics, or support themes, separated from what the team is assuming.
Product flows and interfaces shaped around real user decisions.
Not every product decision needs design exploration. We start by establishing what's already known and what genuinely needs deciding.
Design decisions should trace back to a defined source, not to what looks appealing.
What is known from research, analytics, or support themes, separated from what the team is assuming.
Who does what, in what context, and what "done" looks like for them.
What data and content the interface actually needs to show, including the difficult and edge cases.
Platform, accessibility, and technical constraints that shape what is actually buildable.
Loading, empty, error, permission, and recovery states are part of the design, not left to engineering to improvise.

Loading, empty, error, permission, and recovery states are part of the design, not left to engineering to improvise.
Wireframes, prototypes, or a design system are chosen for what they need to prove, not applied as a default package.
Requirements and testing are named explicitly rather than implied by "clean design."
Feasibility, data, and platform behavior inform design decisions before they are presented as final.
The stack follows the requirement, not the other way round. These are the categories this engagement typically has to decide.
The exact artefacts depend on the product question. None of the following should be assumed automatically.
Every design decision trades something specific for something else. The useful choice is the one whose reason is understood.
Fidelity should match what is being tested, not the team's comfort with polish.
A new pattern is justified when the existing system genuinely cannot serve the need, not by preference.
Some workflows benefit from design and engineering working the same problem in parallel, with tighter feedback.
A full design system is a governance commitment; a scoped component set may serve one project better.
Deliverables should make the design reasoning and its handoff visible and usable.
What is known, what is assumed, and the decision this design work needs to inform.
Information architecture, flows, and interface states including failure and recovery paths.
Usability and accessibility findings against real tasks, not just internal review.
Specifications, assets, and open questions in a form implementation can actually use.
The starting engagement should establish what's known before design work is scoped.
A bounded stage to establish what is known before design work is scoped.
A project-shaped stage to design one workflow, product area, or system.
Design and engineering run together for tighter feedback on feasibility.
Continued design ownership once the product has an active roadmap.
UI/UX Product Design is the right starting point for evidence-led design decisions. A different service may own the wider need.
Choose this when implementation, not design decisions, is the primary need.
Choose this when the next useful step is testing a first release, not design exploration.
Choose this when design is one part of a broader existing-product transition.
Choose this when design responsibility needs to continue alongside an active roadmap.
Technical delivery and architecture details. Key decisions regarding code quality, integrations, and handoff rituals.
No. Product design can include users, tasks, information architecture, workflows, states, interaction, visual hierarchy, prototypes, evaluation, accessibility direction, design systems, and engineering handoff according to scope.