Fragmented design
Visual variants, states and rules spread across files and conversations.
DDS DEMO · ILLUSTRATIVE EXAMPLE
Organizing a digital insurance ecosystem.
A demonstration of how we organize a product system. Data and screens are illustrative: they show decisions and deliverables, not client results.
DDS
SECTORInsurance and financial servicesDemonstration scenario with fictional data.
This example does not attribute results to a client. Explore patterns, states and rules to understand how we work.
THE CHALLENGE
When every team solves the same problem differently.
Slow-to-maintain frontend
Components that look alike but do not share structure, behavior or QA criteria.
Avoidable regressions
Every new screen reopens decisions the system should solve once.
THE DDS DELIVERY
A foundation connecting decisions, files and code.
01
Audit and system map
Inventory of patterns, states, decisions and regression risks.
02
Library and patterns
Base components and reusable solutions for the most repeated flows.
03
Repo and framework
Tokens, code structure, examples and documentation so design and frontend work in sync.
04
AI-ready governance
Guidelines, rules and guardrails to keep the system consistent as it evolves.
BEFORE
Scattered decisions
Duplicate files, inconsistent names and questions that return every sprint.
AFTER
Shared system
A shared language for designing, building, reviewing and letting an AI agent continue the work.
THE CONTEXT
An operation with repeated decisions every day.
Internal portal for teams managing policies, customers and claims.
The same interaction uses different names, states and behaviors across flows.
Create a foundation that reduces repeated decisions and can keep evolving.
INTERACTIVE SAMPLE
An illustrative product workflow.
Compare a fragmented starting point with the governed delivery. The records are synthetic; the interaction model is the point.
View
Operations portal / Claims
Claims queue
Open cases128Fictional sample data
Avg. response2h 14mWithin target
System coverage84%Governed flows
Claims queueUpdated 4 min ago
CL-2048Home · Water damageIn review$ 12,480
CL-2047Auto · CollisionApproved$ 4,820
CL-2045Business · TheftNeeds info$ 28,100
EXAMPLE FINDINGS
What becomes a system rule.
States without shared semantics
When teams use different colors for the same status, a semantic scale defines a shared rule.
Inconsistent table actions
Menus vary in position and priority. A table pattern documents order, focus and responsive behavior.
Empty states without a next step
Screens without data offer no guidance. Add clear copy, a primary action and accessibility criteria.
From a finding to a maintainable rule.
These are inspectable excerpts from this DDS demonstration. The download contains the sample contract, a decision record, agent instructions and a handoff checklist. It is not a client repository or a complete Figma library.
One state, one meaning.
The starting example uses three labels for one state. The decision is to separate the status identifier from its translated label and visual treatment.
claim.status.in_review
English: In review
Español: En revisión
Meaning: received, awaiting reviewA small contract, implemented.
The form above accepts POL- followed by four digits. Invalid input stays editable; a valid submission adds a fictional record locally. Nothing is sent to a server.
export function validateClaimReference(value: string) {
return /^POL-\d{4}$/.test(value.trim());
}Instructions with boundaries.
An agent gets a defined task and acceptance criteria. Rules guide the work; automated checks and human review verify it.
Task: add a claim field.
Reuse the existing form and status contract.
Preserve labels, error associations and keyboard access.
Run validation tests. Ask before changing status semantics.
Never connect this demo to customer data.A change has an owner and a check.
A status change requires design and engineering review. The delivery includes the agreed checks and maintenance instructions, not a promise that every regression disappears.
Before merge:
[ ] Shared status identifier and translated label
[ ] Invalid, valid and empty states reviewed
[ ] Keyboard interaction checked
[ ] Validation tests pass
[ ] Design + engineering approve the changeFor your product, we agree the actual files, stack, reviewers and acceptance checks before implementation. Private work is shown only with permission.
DECISION AND DELIVERY
Choose which risk you want to remove first.
Each delivery solves a different layer of the problem. You can start by ordering decisions, taking them into code or leaving a system ready to evolve with teams and AI agents.
01 · ORDER
DesignReduce ambiguous decisions
Audit, state map, tokens and Figma ready to validate decisions.
Reduces the risk of revisiting the same decisions every sprint and finding inconsistencies too late.Continue with Design02 · CONNECT
Design + repoTake the system to frontend
Aligned visual system, starter repo and implementation examples.
Reduces the risk of design and code evolving with different names, tokens and states.Continue with Design + repo03 · IMPLEMENT
BuildAccelerate repeated flows
Framework, priority patterns and a frontend-ready delivery.
Reduces the risk of rebuilding complex components and accumulating QA regressions in production.Continue with Build04 · GOVERN
Govern AIPrepare the system to scale
Guidelines, rules, guardrails and context for design and development agents.
Reduces the risk of the system losing consistency as teams, products or automation grow.Continue with Govern AINeed to organize an existing system?
Tell us what exists and what you need to receive. We will propose the right delivery layer, without a mandatory sales call.
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