About | Dhanashree B

ABOUT DHANASHREE,

I've always been drawn to problems that are harder than they look.

The kinds of problems where the surface answer is obvious and the real answer takes three weeks of asking the wrong questions first.

In design, those are my favourite problems, the ones that aren't UI problems at all, just wearing a UI costume.

That instinct is why I've spent five years deliberately choosing the most complex spaces I could find: clinical oncology workflows, a $100M+ commerce platform, and AI features that have to earn user trust before they can work.

The mess isn't a side effect. It's where the design actually matters.

DESIGN PHILOSHOPY

How I approach every problem

Start with the system, not the screen

Most UX problems are system problems wearing a UI costume. Before designing any surface, I map the ecosystem stakeholders, constraints, data flows, and decision points.

At Greenworks: 3 weeks building a UX operating model before a single wireframe, making $200M+ platform consistency possible.

Research as decision support, not decoration

40+ user interviews per engagement, to eliminate

opinion-led debates and replace assumptions with evidence before design begins.

At Alleo: 20+ oncologist interviews revealed the real problem was IA, not UI complexity, redirecting 3 months of design work before it went the wrong direction.

Design for constraint, not around it

HIPAA regulations, safety-critical automotive interactions, and multi-literacy transit. Constraints are the sharpest design tools; they force precision that unconstrained work rarely achieves.

Alleo · Yanfeng · MIT Media Lab

The constraint was the brief in every case.

Measure everything worth caring about

Every project starts with: what would need to be true for this design to have worked? Metrics are the language that earns design a seat at the strategic table.

~17% revenue lift · +30% conversion ·

~60% UI inconsistency ↓ · +30% engagement

HOW I WORK & WHAT I USE

Core Competencies

UX Strategy & Operating Models

Structure makes a better design inevitable

I build the governance infrastructure teams need before they need it, operating rhythms, decision frameworks, cross-functional alignment, and OKR-connected measurement.

UX Operating Model

Design Governance

Experience architecture

IA · Service Design

OKR Alignment

Roadmapping

Figma

Miro

Jira

Notion

PROOF

GW · $100M+ · 10+ programmes

~60% delivery ↑

Village.Co · zero-to-one UX infra

Confluence

Research-Led Discovery

Insights that eliminate opinion-led debate

40+ user interviews per engagement. Research as decision support, not a phase. Clinical-grade rigour applied equally to commerce and AI products.

User interviews

Usability testing

Heuristic eval

Affinity Mapping

Funnel Analysis

A/B experimentation

NPS · CSAT · TCR

GA4

Maze

Amplitude

UserTesting

Dovetail

Tableau

PROOF

Alleo · 20+ oncologist interviews

Yanfeng · 50+ studies

Village.Co · 40+ user interviews

AI Tools & Emerging Tech

I design for AI. I design with AI.

Two distinct capabilities: designing for,

AI (trust systems, explainability, confidence indicators) and

designing with AI (rapid prototyping, synthesis, documentation).

AI interaction models

Explainable AI (XAI)

Error & fallback flows

Trust signal architecture

Confidence indicators

Agentic UX patterns

Figma AI

Claude

ChatGPT

Lovable

Cursor

Perplexity

PROOF

AI-Garage · end-to-end model

Lentra · AI Workflows

Alleo · clinical AI decision systems

Design Systems & Craft

Systems engineers quickly adopt

WCAG 2.1-compliant component libraries, design tokens, motion, and micro-interaction design.

Built for adoption, not documentation.

Design systems

Component libraries

Design tokens

WCAG 2.1 / ADA

Motion design

Interaction craft

Responsive design

Figma

Sketch

ProtoPie

Adobe CC

Principle

PROOF

Alleo · 3 Product · ~60% inconsistency ↓

GW · tokens · web + mobile

Village · 0→1 Design System

Currently Exploring

Agentic UX patterns

Designing for AI systems that act on behalf of users, not just surfaces that respond

to them.

How do you show intent, progress, and failure modes for an agent that's working in the background?

Active

Vibe coding interfaces

How natural language-to-UI tools like Lovable and v0 are changing the designer-developer handoff model.

If a PM can generate a working prototype, what does that mean for what design needs to own?

Exploring

WCAG 3.0 readiness

What the proposed cognitive load provisions in WCAG 3.0 actually mean for enterprise dashboard design, especially in clinical systems, where information density is unavoidable but overload is dangerous.

Reading

Relevant to AI-Garage and the next generation of commerce automation at Greenworks.

Using Lovable in practice, the implications are bigger than a new tool category.

Direct overlap with Alleo clinical UX and future healthcare platform work.

EDUCATION

Credentials

MS Human-Computer Interaction · Indiana University

GPA 3.9 / 4.0 · Indianapolis, IN

BDes User Experience · MIT World Peace University

GPA 8.95 / 10 · Pune, India

EXPERIENCE

Where I've worked and what I owned

Early 2025 · Now

Senior Lead UX Designer · Greenworks Tools

$100M+ DTC Commerce Platform · AI Interaction Design · Charlotte, NC

DTC commerce at scale operates with razor-thin conversion margins; every point of friction in the purchase funnel is measurable revenue loss. At a $100M+ platform size, IA decisions and AI interaction models aren't UX problems; they're business-critical infrastructure. Most design teams get called in after the funnel breaks. The challenge was to embed design upstream before it did.

Built the UX operating model, research standards, and AI interaction framework from scratch, establishing governance across AI-Garage, PLP, PDP, cart, checkout, loyalty, and account.
Ran full-funnel CRO-informed IA redesign, implemented behavioral diagnostics and A/B experimentation cycles, and designed the end-to-end AI trust signal architecture, so AI features earned user confidence before they could affect purchasing decisions.

~15–17% digital revenue lift

2%+ sustained conversion improvement

~12% cart abandonment reduction

~20% engagement increase

AI interaction model designed

2024 · 2025

Lead UX Designer · Village.Co

B2B + B2C SaaS Platform · PLG Activation · Remote US

Early-stage SaaS products fail most often not from bad ideas, but from UX that never surfaces the value fast enough. Onboarding drop-off is a silent revenue killer; users churn before reaching the moment that would make them stay. As the first and only designer, there was no existing UX infrastructure, no validated research, and no framework connecting design decisions to business outcomes.

Built UX infrastructure from the ground up - 40+ user interviews and 10+ usability studies grounded every decision before a wireframe was drawn.
Restructured core IA and redesigned the activation flow end-to-end using progressive disclosure and time-to-value reduction.
Delivered annotation-rich Figma systems that eliminated engineering ambiguity — closing the design-to-delivery gap that had been the primary velocity bottleneck.

~30% feature adoption increase

~30% platform engagement growth

~60% delivery velocity improvement

2023 · 2024

UX Designer & Strategist · Yanfeng (Tesla · Jeep · Toyota)

Automotive HMI · Android Automotive OS · Novi, MI

In-vehicle interfaces that overload drivers with cognitive demand don't just fail usability standards; they create measurable safety risk. Automotive HMI operates under a constraint most UX designers never encounter: every interaction decision must be defensible in a context where the user is in motion, attention is fractured, and the consequences of failure are physical. Designing for Android Automotive OS across multi-display, safety-critical environments for three OEM partners simultaneously required a research rigour that consumer UX rarely demands.

Conducted 50+ usability and behavioral studies measuring cognitive load, task performance, and AAOS safety compliance, establishing a research-backed foundation for every interaction decision.
Applied cognitive load analysis and in-motion testing protocols to constrain and validate interface complexity before it reached production.

50+ behavioral studies

AAOS-aligned across 3 OEM partners

Human-machine Interaction

Safety-critical cognitive load research

Autonomous Vehicle Experiences

2021 · 2022

Lead UX Designer · Propero (Shopify)

E-Commerce & Retail UX · Shopify Platforms · Pune, India

Commerce UX without a consistent process creates quality variance that compounds at scale; each inconsistent handoff creates rework, and every unclear spec adds development time. For a consultancy managing multiple simultaneous Shopify product launches, the absence of a shared UX framework was the single biggest drag on delivery quality and time-to-market.

Designed and shipped Shopify-based B2B and B2C storefronts applying CRO-informed IA, content hierarchy, and user-centered checkout patterns.
Established standardised UX processes, wireframing templates, and engineering handoff documentation across all client engagements, building a repeatable system that eliminated variance.

~40% reduction in design iteration cycles

Consistent time-to-market across launches

2021 · 2022

UX Designer · Lentra AI (HDFC · ICICI · Axis Bank)

Fintech · B2B Enterprise Lending · Pune, India

Financial UX operates under a dual constraint that most product designers never confront simultaneously: the workflow must be simple enough for users navigating high-stakes decisions, and compliant enough to pass regulatory audit. AI-assisted lending platforms for India's largest private banks added a third constraint, the AI output had to be comprehensible to loan officers who were not technologists.

Applied user-centred design and iterative wireframing within compliance boundaries to simplify multi-step lending and loan-management workflows.
Collaborated cross-functionally with Engineering, Sales, Marketing, and Innovation teams, aligning UX decisions with commercial and technical requirements and reducing development timelines while improving adoption.

~25% product adoption improvement

~30% user retention improvement

~40–50% development timeline reduction

2021 · 2022

MIT Media Lab · India Initiative × Harvard

Public Transit UX · Behavioural Design · Social Impact

Fragmented public transit UX was creating accessibility and usability barriers for 30M+ multilingual commuters, a population that spans literacy levels, languages, and digital fluency.

The constraint: improving usability without rebuilding infrastructure. No new systems, no budget for new hardware. Purely design-led behaviour change within the existing environment.

Led a cross-institution design initiative applying design thinking, systems thinking, and nudge-based behavioural interventions to improve transit usability at a population scale.
Collaborated with MIT and Harvard researchers to ground every intervention in evidence, translating academic behavioural economics into applied UX decisions.

30M+ commuters served

~30% user retention improvement

Nudge-based accessibility interventions