Bridging complex government and enterprise content systems with modern web architecture.
As a contract Staff Product Designer, I connected UX strategy and hands-on design engineering with React, TypeScript, and Tailwind CSS.
I architected automated editorial ingestion workflows and high-density SaaS dashboards, connecting content processing with the controls editors need to inspect and manage incoming items.
Automated editorial ingestion reduced the time associated with manual content tagging.
Analytics, event operations, and component foundations across Upgather.
Connect the dashboard, filters, KPI details, report comparisons, and sharing in one analytics journey.
“What has arrived, and what needs attention?”
Source → Queue → Review
Make incoming items, source context, and processing state easy to scan in one workspace.
“Are these tags relevant to this story?”
Suggested tags → Editorial review → Confirm
Separate machine suggestions from approved metadata. Keep correction and override close to the item.
“Where is work moving or getting stuck?”
Queue signals → Filters → Item detail
Connect high-density summaries to the underlying content, with clear loading, partial-data, and recovery states.
“Is this item ready for the right audience?”
Review → Permission check → Release
The proposed distribution model preserves editorial approval and makes the release state explicit.
Turn a dense content pipeline into an understandable workspace.
Connect incoming content, metadata, and editorial decisions so operators can prioritize without losing context. Keep the source, item status, and next action visible together.
Organize around the editor’s task, with detail available when it is needed.
Assist classification while keeping publishing with people.
Use AI-assisted tagging to propose metadata. Structured controls let editors inspect, correct, and approve suggestions; automation should support editorial judgment.
Automate repetitive suggestions while preserving human review of content and release.
A proposed architecture keeps the queue and item detail aligned.
A typed ingestion state would connect incoming items, tagging suggestions, and review panels. Version checks and explicit processing states would help prevent stale updates from replacing an editor’s work.
Sample route ready.
Keep streaming updates visible without interrupting an active editorial decision.
A suggestion remains editable until an editor approves it.
Proposed guardrails include source attribution, editable tags, and explicit approval. Summaries should retain source context, and uncertain classifications should return to a person.
Editor review required before handoff.
Illustrative workflow. No content is sent or published.Preserve an accountable review step before metadata or content is released.
Connect React, TypeScript, and Tailwind CSS through a shared contract.
Map design tokens to typed components for queue rows, filters, review panels, and status badges. Document error and recovery states; evaluate keyboard order, contrast, and announcements against WCAG AA criteria.
<EditorialReviewCard
itemTitle="Technology update"
/>action/primaryspace/cardradius/cardUse constrained, accessible primitives so dense screens stay consistent.
Measure the friction removed from editorial work.
The supplied outcome is a 40% reduction in manual content-tagging latency. Pair that measure with correction rates, review effort, and publishing accuracy to understand the quality of the workflow.
Distinguish faster tagging from system ingestion speed and end-to-end publishing time.
A working React example pairs typed props, design tokens, and an explicit review state.
| Design token | Value | Tailwind |
|---|---|---|
| action/primary | #7c3aed | bg-[#7c3aed] |
| surface/default | #ffffff | bg-white |
| space/card | 24px | p-6 |
| radius/card | 12px | rounded-xl |
Review the suggested metadata before continuing.
The source matches the local preview’s review toggle.
type EditorialReviewCardProps = { itemTitle: string };
function EditorialReviewCard({ itemTitle }: EditorialReviewCardProps) {
const [reviewed, setReviewed] = useState(false);
return (
<article className="rounded-xl border border-[#d9dce2] bg-white p-6 text-[#222225]">
<h4 className="text-lg font-semibold">{itemTitle}</h4>
<p className="mt-2 text-sm">Review the suggested metadata before continuing.</p>
<button type="button"
className="mt-5 min-h-11 rounded-lg bg-[#7c3aed] px-4 py-3 font-semibold text-white"
aria-pressed={reviewed}
onClick={() => setReviewed(value => !value)}>
Review editorial item
</button>
<p className="mt-3 text-sm" role="status">
{reviewed ? 'Preview reviewed. Nothing published.' : ''}
</p>
</article>
);
}The reported 40% reduction in manual content-tagging latency is the specific outcome of the automated editorial ingestion workflow. It is distinct from end-to-end publishing time.
Evaluate classification corrections, source traceability, queue recovery, and editor understanding of approval states. Confirm that faster processing does not introduce extra review work.
Explore the Upgather event-platform case study ↗