Trust as infrastructure
Designing for the 11pm questions: what happened, and how do I know?
Financial Operations Workbench at Zuora
Design strategy lead · 0->1 · Collaboration Tool · AI
Conceptual images. Consumer facing storefront UX/UI designed with Forms Builder
SUMMARY
Description
An operations workbench (and the trust infrastructure that earned its adoption) for the people who run subscription businesses at scale.
The Problem
Five tools for one job. The work was scattered, and the proof of it was nearly impossible to reconstruct.
My Role
0-to-1 design strategy lead. End-to-end UX/UI across operator workflow, audit surface, and platform integration.
Clients
Anthropic, Microsoft, the New York Times, Zoom, and others.
Outcome
Designed for two, publisher and viewer.
1 Operators running cyclical work
Accountants, analysts, payment-team and billing-operations managers. Monday morning, the question is "where do I start?", and the answer used to live in five different places.
"I need to be able to explain what happened. To my manager, to an auditor, to myself at 11pm when something looks wrong."
Every operator I spoke with said some version of this. They didn't want speed. They wanted the answer to hold up.
2 Auditors reading the trail
Internal and external both, and they need different things by design. The auditor isn't there for the daily back-and-forth. She's there to assess whether a process can be defended.
Architecture: workflow, platform, trust
Glass box, not black box
Workflow layer
Tasks become trackable, team visibility immediate, and the Slack-and-email coordination that used to hold things together quietly disappears.
Platform layer
Built inside Zuora's existing widget system so the workbench felt native from day one. New patterns proposed as upgrades to the platform, not competitors.
Trust layer
An auto-generated activity log that doubles as an audit trail. Same source of truth, different views by access. Visibility unlocks consolidation. Consolidation unlocks AI readiness.
For multi-site enterprise clients, this meant building structure once and theming it across sites, instead of duplicating effort five ways.
The decision I pushed back on
Inside the platform, not alongside it
The obvious senior move was to propose a separate, branded UI. I made the call not to. Zuora's widget system was already where users went every day; building inside it let the workbench inherit the visual trust the platform had already earned, and the bandwidth saved went into the trust layer.
Trust first, AI second
The organization was investing heavily in agentic AI. The pressure was to move faster on AI, not slower.
I redirected. Trust infrastructure first, AI features after. Same data layer, sequenced differently. Operators in high-stakes work won't adopt a system they can't inspect or explain. Build the inspection layer first, and AI lands on a foundation people already trust.
In high-stakes work, a system earns trust by being inspectable, not by being smart.
That sequencing turned out to be the strategic argument the executive layer needed.
What we've built
My Tasks: where the day starts
Four filter cards at the top: blocked, highest priority, recently assigned, all attention needed. Each shows a count (5 blocked, 3 highest priority) and clicks to filter the list beneath. Stats and navigation simultaneously. The cognitive cost of triaging at 8am: zero.
Timeline: the trust layer in detail
For operators, an activity log: what happened, when, who touched it. For auditors, the same data as an audit trail, generated automatically as work happens. Views are curated by access permission.
When users can see what the system did, they begin to depend on it. Once that dependence is built, AI lands on a foundation users trust.
Internal auditorsees operational depth. External auditor sees a scoped, defensible record. Granularity in compliance is a security consideration: more context widens the surface area for scrutiny without serving the audit. Designed as a data-model decision, not a permissions bolt-on. It's a privacy-by-design moment.
3 Drawers as connective tissue
Eight features, one interaction model for depth. Click any task, process, or control and a drawer opens, without leaving the page.
The most-iterated component in the system: multi-tab variants, page-bridging behavior, scroll affordances, none of it visible to the end user, all of it load-bearing.
Outcome
A common reconciliation workflow with integrated automation
70%
Of design-partner users said Timeline made them more willing to consolidate into the workbench
85%
Of that group open to agentic AI when Timeline made the reasoning inspectable
My Tasks + Notifications
Adopted as standards by other Zuora product teams
Added to the design system as net-new contributions
NYT, Airbnb, Lyft
Called this the most exciting item on the 2026 roadmap
REFLEXTION
Where the research changed me
Going in, I assumed the team's first instinct (move fast on AI features) was the wrong tempo, but the right direction. Field research changed the picture. Trust infrastructure isn't a phase before AI. It's the design problem AI assumes someone else has already solved, and almost no one has.
Capability without inspection isn't adoption. It's exposure.
Where this opens up
Train agents on the reasoning patterns logged in Timeline
What happened, who decided, and how the decision was made. The third layer is what teaches an agent to act like the team.
Mobile companion for review and approval
Phase 1: notifications. Phase 2: full task management. Phase 3: a conversational AI agent that understands the same workflow data operators have come to trust.
A glass-box pattern library beyond finance
The trust principles transfer. Clinical decisions, legal review, AI-mediated work generally. The patterns we built want a wider home.
Back to top