Design and
UX
SDEN designs product interfaces (research, wireframes, design system, accessible by default) with the design tokens shared between Figma and the production codebase.
What this domain covers
Design sits inside engineering, not on top of it. The engineer scoping the data model is in the room for the wireframe review; the designer running research watches the team fold feedback back in.
Interface and architecture get decided together, not stapled together after the fact.
Accessibility is a default, not a feature: WCAG 2.2 AA on every product unless you choose otherwise, tested against assistive tech before a release ships. Design tokens (color, type, spacing, motion) live in one source of truth, exported to Tailwind for code and Figma for design, so the system stays in sync without manual reconciliation.
From challenge to capability
Whatever the domain, the path is the same: scope it, build it with agents, and leave you owning it.
Design and UX: the SDEN defaults
Defaults we ship
- User research before wireframes; wireframes before high-fidelity design
- Design system tokens shared between Figma and Tailwind / code
- WCAG 2.2 AA as the default accessibility bar
- Motion budgets that respect prefers-reduced-motion
Deliverables
- User research notes and synthesized findings
- Design system (tokens, components, documentation)
- Production-grade UI integrated by the same team that designed it
- Accessibility test results against the published WCAG criteria
What we refuse to ship
We will not hand over a Figma file as if it were a deliverable. The deliverable is the shipped interface, integrated and accessible. Figma is a working artifact, not the product.
More from
the SDEN blog.
Cornerstone writing from the SDEN team: what AI changes, what it doesn't, and how a senior team ships the difference.
Product design after the AI shift: what changes for users and teams
Generative interfaces, probabilistic outputs, and agentic flows break parts of the UX playbook. The patterns that hold, and the ones we are quietly retiring.
RAG for business: building knowledge assistants that actually work
Retrieval-augmented generation grounds AI answers in your data. What RAG is, when it beats fine-tuning or a plain prompt, and what separates a knowledge assistant you can trust from a demo.
AI agents for business: where they work, and where a workflow wins
Agents are powerful and easy to get wrong. When a task genuinely needs an agent, when a plain workflow is the better answer, and how to keep an agent safe and affordable in production.
What you get here
Concrete deliverables, not slides.
Explore
Where this capability fits
Building with AI in Design & UX?
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