Firm leadership
Partners & directors
Analyze financial data to identify trends and patterns; generate reports and presentations; automate administrative tasks that pull them away from client relationships.
Case study
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Staff Product Designer · AI Systems · Fintech
I build AI-native products and design infrastructure for professional workflows at scale. Currently at Intuit, making enterprise accounting feel effortless for 10,000+ firms.
10K+
Accounting firms onboarded in 4 months
15+
Product teams aligned
40%
Feature adoption, Client Insights
Agentic AI · Books Close · Fintech
Defined how to show where close work stands, where accountants provide input, and the setup and collaboration an agent needs — so agents can help deliver monthly books close faster.
60%
Less close prep time
3×
Faster blocker detection
100%
Human-in-the-loop
Analytics · AI-native · Fintech
Transformed QuickBooks from a siloed per-client based reporting system into a queryable, firm-wide intelligence platform — giving accounting firms their first portfolio-wide view across 250–1,800+ clients.
40%
Feature adoption
250+
Clients per firm
0
External BI tools needed
Redefined how Intuit's GenAI behaves for professional accountants — moving it from a generic chatbot to a context-aware, multi-tenant intelligence engine with three foundational architectural principles.
↑ Client health checks: hours of navigation → seconds of query
Broke a multi-month executive deadlock with a functional coded prototype — securing investment for a 100+ person org and a product adopted by 10,000 firms within 4 months of launch.
↑ 10,000 firms adopted · 100+ person org secured · Enterprise market unlocked
Transformed work management from fragmented features across QBO, Mailchimp, and TurboTax into a unified L1 platform capability — defining the design architecture, operating model, and governance framework for 15+ offering teams.
↑ 15+ teams aligned · FY23 + FY24 roadmaps defined · DACI operating model established
I'm a Staff Product Designer at Intuit, where I've spent the last several years making some of the most cognitively complex professional workflows feel effortless — accounting operations, enterprise-level practice management systems, and AI-powered financial intelligence for tens of thousands of firms.
My work lives at the intersection of product strategy, systems thinking, and craft. I don't just design screens — I define frameworks, align organizations, and build the design infrastructure that lets teams move faster and more coherently.
I'm looking for my next challenge at a company building something ambitious — where design has a seat at the strategy table.
Outside work
Sports and the outdoors found me late — they weren't part of how I grew up — but that's exactly what made falling in love with them meaningful. Picking things up from scratch, getting better at something unfamiliar, figuring out how to push further than you thought you could: that's genuinely fun to me. It's the same instinct that pulls me toward new food, new places, and new experiences whenever I can find them. Dark chocolate and a strong coffee are non-negotiable constants in all of it.
Baking is my other outlet — there's something satisfying about a process that requires precision and rewards patience, which probably says something about how I approach design too.
I care a lot about doing what's right, even when it's inconvenient. And if a friend needs me, I show up.
Expertise
Craft
AI-native product designSystems
Multi-tenant architecturePlatform
Design systems & governanceStrategy
0→1 product visionLeadership
Cross-functional alignmentDomain
Fintech · SaaS · EnterpriseMethods
Research-led discoveryTools
Figma · Prototyping in codeOpen to Staff and Principal IC roles across Bay Area and remote.
AI Architecture · Multi-tenant · Staff IC
Redefining how Intuit's GenAI behaves for professional accountants — from a generic single-user chatbot to a context-aware, multi-tenant intelligence engine with cross-client @ mentions.
Intuit's GenAI was built for small business owners — but professional accountants managing hundreds of client files needed an AI that understood multi-tenant context, permission boundaries, and professional-grade responses.
I advocated for the accountant persona, defined three foundational AI architectural principles, and designed a two-level delivery roadmap — culminating in the @ mention feature that enabled cross-client queries from the IAS dashboard in seconds instead of hours of file navigation.
Intuit's GenAI framework was originally built for Small Business Owners — people who benefit from basic guidance like tax term explanations and simple categorization tips. When professional accountants, who manage hundreds of clients simultaneously, used this same AI, the results were jarring.
The AI couldn't distinguish between the accountant and their client. It gave CPAs advice meant for beginners. It had no concept of "I'm working across 200 client files right now." And it forced accountants to manually hop into each individual QuickBooks file — one at a time — to perform any real professional work.
I identified this gap, named it the "Identity Crisis," and argued to the business that we were actively alienating our most powerful users.
Before defining how Intuit Intelligence should behave in IAS, I ran qualitative research with partner-to-mid-level accountants across accounting firms — exploring how AI fits into professional practice today, their willingness to adopt it, and what they'd trust an IAS chatbot to do.
Firm leadership
Partners & directors
Analyze financial data to identify trends and patterns; generate reports and presentations; automate administrative tasks that pull them away from client relationships.
Review & compliance
Managers & seniors
Review financial statements for accuracy and compliance; identify and correct errors; perform risk assessments and audits with AI-assisted review, not replacement.
Day-to-day execution
Staff & associates
Data entry and transaction processing; basic financial analysis; routine reports and client communications — the repetitive work they'd most want automated first.
Users expected the chatbot to be a trusted advisor — not just a task automator. They wanted intelligence that understood their firm, their workflow, and their clients.
Understand me
Recognize the firm's history and unique needs — industry focus, client mix, software stack. Understand current workflow and context: what task am I on, what's my goal? Proactively surface issues and opportunities from firm data with actionable recommendations.
Go beyond summaries
Provide insights with context and explanation — not just data dumps — so accountants can make decisions and have better client conversations without re-processing raw numbers themselves.
Be my partner
Help me work faster by automating tedious tasks and offering intelligent suggestions at the right moment — augmenting expertise, not replacing professional judgment.
Earn trust first
Be transparent about how the AI works, what data it uses, and how it reaches conclusions. Security and explainability were prerequisites before firms would let AI anywhere near client books.
These insights directly informed the product direction: persona-aware responses for accountants, @ mention scoping for multi-client context, and architectural guardrails around permissions and data sovereignty — translating research expectations into shippable IAS Intelligence.
Research surfaced four user expectations — trust, human empowerment, tangible value, and workflow context. These three architectural principles translated those insights into system-level rules for multi-tenant AI — not surface-level UI fixes.
Each context has its own conversation space — IAS and QBO chat threads stay completely separate so accountants can share screens with clients without leaking firm intelligence.
Access scales based on entry point — universal portfolio authority in the IAS Dashboard, automatically narrowing to single-client scope inside an individual QBO file.
The AI is an interface, not a loophole — it strictly inherits each user's existing RBAC and cannot see or act beyond what the human is authorized to do.
A two-level delivery roadmap — first establishing the accountant persona and embedding AI in the IAS dashboard, then shipping the @ mention solve that unlocked true multi-tenant queries in Intuit Assist.
Making the AI recognize who it's talking to — establishing the accountant as a distinct persona so the AI stops giving CPAs beginner-level advice, then embedding intelligence directly in the Accountant Suite.
IAS embedding
Client scope chip
Level 1 fixed the identity crisis and shipped a pragmatic path: persona-aware responses inside the IAS dashboard, with a scope chip that anchors queries to the right data environment and expands into a searchable client picker.
The hero feature — typing "@" to scope a query to any client file and get a specific, data-backed answer without leaving the IAS dashboard.
@ mention picker
Scoped answer
Level 2 unlocked true multi-tenant AI: an accountant tags @Tracy's Framing, asks why raw material costs spiked, and gets a specific answer — misclassified vendor invoice, amount, and document number. Cross-client synthesis without leaving the IAS dashboard. A task that previously took 45–90 minutes of manual file navigation now returns in seconds.
The three architectural principles I defined became the governing framework for how Intuit AI behaves for all professional users — a reusable foundation that any future AI feature in the accountant ecosystem builds on.
Cross-client workflows that previously required hours of manual file navigation were reduced to seconds of natural language query.
The hardest part of this project wasn't the design — it was the advocacy. Convincing a business that its most powerful AI feature was alienating its most valuable users required framing the problem in business terms: these accountants manage the majority of data in the Intuit ecosystem, and if they don't trust the AI, adoption fails.
Platform · 0→1 · Enterprise · Staff IC
When Intuit needed to break into the enterprise accounting market, the strategy existed only in documents — stalled for six months. I ended the deadlock with a functional coded prototype that secured a 100+ person business unit and 10,000 firm adoptions in 4 months.
QBOA dominated small-firm accounting but couldn't run mid-to-large practices — firms stitched together ~11 tools while leadership debated a 40-page strategy for six months.
I built a functional coded prototype of the full Intuit Accountant Suite — consolidating client management, service delivery, data intelligence, and team management into one unified platform — and used it to break the executive stalemate and fund a new business unit.
QBOA had become the dominant accounting software for small firms — so dominant that the market was effectively saturated. To generate meaningful new revenue, Intuit needed to move upstream into mid-to-large accounting firms: a completely different customer with far more complex needs.
The existing QBOA couldn't run a firm. It couldn't manage teams, track service delivery across hundreds of clients, or give partners the visibility they needed to run a practice at scale. Research showed these larger firms were stitching together ~11 different tools just to operate. For six months, leadership couldn't agree on how to move. I decided to change the medium.
Four strategic pillars that became the product roadmap foundation — each solving a distinct fragmentation pain for mid-to-large accounting firms.
End-to-end client lifecycle — lead generation, onboarding, and active service delivery in a single persistent profile with 360° client health visibility.
Service queue and accounting work in one screen — eliminating the hundreds of daily context switches between management tools and QuickBooks.
Client Console leverages dormant firm data for proactive next-best actions — elevating accountants from reactive bookkeepers to strategic advisors.
Real-time workload distribution, role assignment, and staff productivity visibility — so partners can see over- and under-utilization before it becomes a delivery problem.
A functional, high-fidelity coded prototype — not a slideshow, but a clickable system navigating from client acquisition through service delivery to AI-powered insights in a single session. Seeing the 11-tool burden consolidated moved the conversation from "should we do this?" to "how do we start?" within weeks.
Marketing & onboarding
Sign-in & acquisition
HomeBase — firm dashboard
Client AI profile
Every client in one unified roster — accounting solutions, products, attached apps, and billing type visible at a glance. No CRM required.
Client list — unified roster
HomeBase — firm-wide intelligence
Service delivery meant working client-by-client through planning, checklists, transaction review, and financial statement prep inside each client file — with no firm-wide view of where close work stood across the book.
Firm-wide Books Close overview
Client-by-client manual close
300 clients queryable across expenses, revenue, ratios, and AR past due — with colour-coded anomaly signals and AI drill-down per client.
Portfolio table
AI anomaly drill-down
Design provocations for workload distribution — roster performance and weekly capacity planning before delivery problems surface.
Team roster & performance
Capacity planning
I established a Co-Development Framework with leaders from mid-to-large accounting firms to ensure we were solving their most expensive problems before committing to production. I ran intensive workshops to map the 11-tool fragmentation in detail — those workshops directly produced the four pillar structure.
The prototype I built ended a six-month strategic stalemate and secured investment for a dedicated 100+ person organization. The suite launched and reached 10,000 firm adoptions within 4 months — positioning Intuit as a credible competitor in the large-firm market for the first time.
Analytics · AI-native · Data Platform
Transformed QuickBooks from a siloed per-client based reporting system into a queryable, firm-wide intelligence platform — giving accounting firms their first portfolio-wide view across 250–1,800+ clients.
Client Console is an AI-native analytics platform that gives accounting firms a queryable, portfolio-wide view across every QuickBooks client file — without external BI or manual exports.
Unlike per-client reporting tools that leave firms blind at scale, it surfaces anomalies, trends, and segmentation-specific dashboards in one firm-wide intelligence layer.
QuickBooks was built around a fundamental unit: the individual client file. For a firm with 500 clients, getting a portfolio-wide view wasn't a feature gap — it was an impossible task. Firms were paying for external BI tools, building custom Excel macros, or simply going without the visibility they needed.
Two personas from 27+ CAS research interviews — staff and director levels, both living inside the same siloed-client-file problem.
Jane Horton
Sr. Accountant
Responsibility
Prospects new clients, scopes engagements, produces complex work, reviews simple work, and serves as client point of contact.
Personal goals
Passing the regulation portion of the CA CPA exam — with the same attention to detail her client work demands every day.
Opens client files one at a time — no portfolio-wide view without hours of manual review.
Stella Medina
Director
Responsibility
Leads client engagement PODs — prospecting, scoping, producing complex work, reviewing simple work, and acting as primary client contact.
Personal goals
More time away from Saturday catch-up work. Building firm relationships and supporting colleagues' growth.
Oversees hundreds of clients but reviews them in isolation — firm-wide intelligence was impossible at scale.
Benchmarked portfolio analytics across accounting platforms, BI tools, and AI-native dashboards — mapping what firms actually used before we defined the white space Client Console would own.
Fathom
Accounting analytics
Tellius
AI-native analytics
Microsoft Fabric
Enterprise BI
Airtable
Flexible data views
The gap was clear: every tool solved one slice — per-client KPIs, external BI, custom spreadsheets, or AI chat — but none offered native, portfolio-wide querying inside QuickBooks.
Six principles that governed every design decision — from data architecture and interaction patterns to how AI surfaces what matters.
Users customize dashboards to match individual workflows — pulling any client data into custom views without external BI or manual exports.
A comprehensive, queryable view across every client file — giving accountants firm-wide visibility for strategic decision-making at scale.
Industry, risk tier, and service type — dashboards that mirror how each firm actually organizes and reviews their book.
Quick data processing and seamless dashboard responsiveness — accountants work without interruption, regardless of portfolio size.
Complex data as intuitive, high-density narratives — critical anomalies surfaced first, with accountants in control of what they see.
AI flags clients trending toward trouble before they become crises — shifting accountants from data processing to proactive advisory.
Client Console replaced the per-file loop with a firm-wide analytics layer — every client in one queryable table, with the customization accountants expect from professional tools.
Financial insights
Customize metrics
Every manipulation accountants expect from a professional analytics tool — built in, not bolted on with external BI.
Filter & search
Column controls
Data transparency
Date range
Custom periods
Accountants query any client data in natural language, filter by custom fields, and drill into AI-surfaced anomalies — all without leaving the Console or opening individual client files.
By unlocking portfolio-wide querying, Client Console established a clear value floor for the paid Intuit Accountant Suite tier — the first capability no competitor matched in the accounting software space.
Every firm had been flying blind across hundreds of clients, reacting instead of anticipating. Client Console gave accountants a trading-floor view of their entire portfolio — shifting them from reactive firefighting to proactive advisory.
The next generation moves from a queryable data table to a fully agentic practice management layer — proactively identifying what matters, ranking it by urgency, and generating analysis alongside the accountant in real time.
1 of 5
Console overview
2 of 5
Anomalies feed
3 of 5
Advisory Agent — prioritized list
4 of 5
Client analysis — inline expand
Future direction
Advisory Agent — Conversational dashboard construction
The accountant uploads a timesheet screenshot. The Advisory Agent reads the image, extracts metrics, proposes additional columns, and builds the dashboard schema — waiting for confirmation before populating.
The hardest part wasn't the design — it was making the problem undeniable. No competitor offered portfolio-wide financial scanning; I built the case from scratch through research, white space framing, and positioning siloed data as revenue risk. Client Console became the first product to give accountants a trading-floor view of their entire client portfolio — shifting them from reactive firefighting to proactive advisory.
Design Systems · Platform · Cross-ecosystem · Staff IC
I led the transformation of work management from a secondary feature being built independently by 15+ product teams into a unified, centrally-architected L1 Platform Capability. I solved two problems at once: the product fragmentation users felt, and the engineering redundancy Intuit was paying for across QuickBooks, Mailchimp, TurboTax, and beyond.
My contribution
As Intuit grew its product portfolio, every team was solving the same problem independently. QuickBooks had its own task feature. Mailchimp had its own. TurboTax was building one. Each solution was slightly different, none talked to each other, and collectively they represented enormous duplicated engineering investment — and a user experience that felt incoherent.
I delivered a responsive component library designed to be resilient across the full range of Intuit's surface area — from narrow sidebar widgets (330px) to tablet views (768px) to full dashboard contexts (1024px).
I designed comprehensive resilience specs for Empty, Loading, and Error states across all components. The non-happy path is where design systems typically fail in production — building these specs explicitly ensured a consistently high quality bar across all 15+ Intuit SKUs.
The hardest design problem wasn't the UI — it was governance. I designed the IPTM Design Working Model to answer how 15+ teams could build what their users need while maintaining platform coherence, defining three engagement scenarios:
Scenario A — Use as-is
Teams with standard use cases plug into existing IPTM components without modification. Zero coordination overhead, maximum consistency, fastest time to implementation.
Scenario B — Co-design shared extensions
When a team needs a capability that could benefit others — like Recurring Tasks — they co-design it with the IPTM team so it becomes a shared platform extension. Governed contribution, distributed benefit.
Scenario C — Partner-led contributions
Offering teams with unique domain needs build their own extensions, with IPTM owning the common UI and services layer. Maximum flexibility at the edges, coherence at the core.
I drove the FY23 Development Roadmap — prioritizing the core services and widget library that would unlock the broadest adoption. For FY24, I defined the Discovery Roadmap focused on the next capability tier: Project Templates, Custom Fields, and Portfolio Health tracking for mid-market users.
Unified work management across 6 Intuit products and 15+ offering teams under a single design vision and operating model. Established the DACI operating model as the standard for how Intuit platform teams and offering teams collaborate on shared capabilities.
Agentic AI · Books Close · Service Delivery
The main work was defining how to show users where the work was at, getting users started on where they need to provide their input, all the setup to have the agent start working, and the collaboration needed to get information from different sources — putting all of this together in a world where an agent can help accountants deliver monthly books close faster.
Month-end books close spans every client file in a firm — but accountants had no consistent way to see where the work was at, where they still needed to provide input, or what had to happen before an agent could start working.
This project put those pieces together: surfacing work status across the book, guiding users to the input the agent still needs, designing the setup flow so the agent can start working, and the collaboration patterns to pull information from different sources — all in service of helping accountants deliver monthly books close faster.
Month-end close hadn't changed in decades — accountants still worked client-by-client through static checklists, planning steps, transaction review, and financial statement prep inside each client file. Partners had a firm-wide Books Close overview — but it showed period, due date, and status, not where the work was at across the book, where they needed to provide input, or what setup was still required before an agent could start working.
Firm-wide Books Close overview
Client-by-client manual close
Two personas from CAS research — a senior accountant reviewing close work and a staff accountant executing it, both living inside the same client-by-client checklist problem during month-end crunch.
Benchmarked close management across accounting platforms, automation tools, and in-ledger review — mapping what firms actually used before we defined the agentic layer Books Close would own.
Double
Month-end close platform
Ramp
Real-time close automation
FloQast
Enterprise close management
Xenett
In-QBO close review
The gap was clear: every tool accelerated one slice — per-client close, spend coding, enterprise checklists, or in-file review — but none proactively detected blockers, ranked a firm's queue, or prepared work across every client before the accountant logged in. Biggest of all, none of them owned the GL of the client.
Five problems this work had to solve — from showing where the work was at to pulling information from different sources, all toward monthly books close delivered faster with an agent.
Define how to show users where the work was at — across every client file in the close book, not one checklist at a time.
Get users started on where they need to provide their input — so the agent is not blocked waiting on information only an accountant or client can supply.
All the setup to have the agent start working — the steps and states that must be in place before the agent can run across a client file.
The collaboration needed to get information from different sources — connecting what lives in the ledger, with the firm, and with the client into one close workflow.
Putting all of this together in a world where an agent can help accountants deliver monthly books close faster.
Each screen maps to one part of the work — showing where the work was at, getting users to where they need to provide input, the setup to have the agent start working, and the collaboration to get information from different sources.
Work in progress Screens below are intentionally blurred — this product is still in development and cannot be shared in full fidelity.
Books Close dashboard
Close progress & ready for review
Define how to show users where the work was at — across task lists, kanban stages, and firm-wide status views.
Firm-wide close status
Close task list
Kanban view
Get users started on where they need to provide their input — surfacing what the agent is blocked on and what only an accountant or client can supply.
Books Health Check
Inline analysis
The collaboration needed to get information from different sources — pulling together what lives in the ledger, with the firm, and with the client.
Matched reconciliation
The main work was defining how to show users where the work was at, getting users started on where they need to provide their input, all the setup to have the agent start working, and the collaboration needed to get information from different sources.
Putting all of this together in a world where an agent can help accountants deliver monthly books close faster.