Rupa Chaturvedi

Head of Merchant & Ads Design at Uber, Adjunct Lecturer at Stanford University

I’m a UX Design Leader and AI/GenAI specialist who blends 0→1 invention with platform-scale delivery. I build high-performing global teams, architect systems and information frameworks, and turn ambiguous problems into durable products that move KPIs.Highlights:- 0→1 to v2 at scale: From concept to launch to systematized patterns—GenAI assistants, video discovery, conversational shopping, AR/3D visualization.- Platform UX and IA: Unifying fragmented surfaces into responsive, multi‑platform systems; shaping primitives for workflows, analytics, and monetization.- Design org building: Scaling diverse, distributed teams; codifying operating cadences; partnering with research and content; aligning roadmaps to outcomes.- AI design enablement: Equipping UX orgs to design AI responsibly—expanding influence beyond UI via model evaluation, systems thinking, AI‑first mental models, and AI workflows.Selected outcomes:- Built a 14-person global design org across 3 continents; shipped 80+ features in under 5 months; consolidated a multi‑platform system; meaningful KPI impact.- Incubated 0→1 GenAI initiatives (consumer LLM assistant, Merchant Copilot, AI creative tools, video discovery)—adopted by SMBs and enterprises globally.- Scaled a conversational shopping product from 0→1 to 1M WAUs in under 6 months; 20+ patents granted/published; launched AR “View in Your Room/AR View” with press coverage.- Taught and enabled 1,500+ professionals via a human-centered AI institute; consistent 5/5 ratings; partners include Reforge, Stanford, Maven.Today, I focus on platform UX, AI-assisted experiences, and design org development—bringing product strategy, systems thinking, and responsible AI to enterprise and SMB workflows.

UX Design Manager

Excited to welcome David Eisner, founder of CraftAmplify, as our special guest at our upcoming Circles Community Meetup on Friday.

David will break down frontend coding concepts for designers and then walk through a live demo showing how AI code assistants can help you make enterprise-grade, production-ready frontend updates—without losing quality, structure, or sanity.

If you’ve ever asked:
- How deep into frontend should designers really go?
- How can AI speed things up without creating messy code?
- What does “production-ready” actually mean in the real world?

This session is for you.

Join the Circles community (for product builders and AI designers) to access this event (and the replay) for free.

Comment or DM “circles” and we’ll send you an invitation.

Hope to see you there 👋

Design & AI Leader | Stanford Lecturer | AI enablement for UX orgs | ex-Uber, Google, Amazon

Over 4000 people signed up for my talk on Designing for Trust in AI Agents yesterday.

As the industry continues to dig deeper on what AI agents can do, the question of whether users will actually trust them to do it seems to be top of mind for many of us product builders.

I've been experiencing this firsthand. I've tested Claude Cowork, Cora, Manus, and a handful of other agents over the past few months. They're fast. They're thorough. And I keep finding myself unable to use what they produce.

The pattern I keep landing on: we've designed agents to optimize for speed to output instead of speed to understanding. The industry celebrates execution time. Users care about whether they can actually do something with the result. Those metrics have almost nothing to do with each other.

I wrote up the core ideas from the session in this week's newsletter. It goes deeper on where the trust gap actually lives and why the usual mechanisms (transparency, guardrails, reversibility) don't solve the underlying problem.

If you'd like to watch a replay of the talk, comment AIUX and I will send you the recording link.

This is the AI UX Brief - my weekly newsletter on designing intelligent systems, leadership in the AI era, and navigating the messy reality of AIUX. F

Open article: The Speed Paradox: Why AI Agents Feel Impressive But Unusable by Rupa Chaturvedi • 7 min read

The Speed Paradox: Why AI Agents Feel Impressive But Unusable

In good company. 🙌
MXDAI is now a Top 10 course on Maven across all categories—including AI and Design!

cc Maven

I designed a course for UX designers who already know their craft, but feel that the ground is shifting under it.

If you’ve spent years building strong UX instincts, AI can feel disorienting. Interfaces are changing, workflows are evolving, and even what “good design” means is not what it used to mean. Simply building prototypes with AI tools isn't enough.

This course is not about chasing trends or mastering the latest AI tool. It’s about helping designers re-anchor their thinking in a world where systems are adaptive, outputs are probabilistic, and users are rebuilding their mental models with every new product launch. 

We focus on frameworks that help you reason through AI interactions, not templates to copy. We look at how trust is built (and broken), how responsibility shifts between humans and systems, and how designers can lead these conversations, not just execute on them.

If your goal is to stay relevant by learning a tool, there are faster, easier and cheaper paths. If your goal is to stay influential as design itself evolves, this course will give you the structure and perspective to do that thoughtfully.

I get asked this question a lot lately: Is there still a future for UX designers?

The short answer is yes. But not the future many designers were trained for.

What’s disappearing isn’t design, it’s a specific version of the role that was heavily centered on execution, screens, and predictable workflows. AI has made those parts faster and cheaper.

What’s emerging instead is a different kind of design work.

Designers are being asked to make sense of complex systems. To translate AI capabilities into experiences that fit into people’s lives, workflows, and mental models. To decide when automation helps, when it harms, and how trust is built over time.

This requires a mindset shift, from creating interfaces to shaping interactions, behaviors, and outcomes. From shipping artifacts to influencing product direction earlier and more strategically.

There is a future for UX designers. But it belongs to those who are willing to evolve their thinking about their role, their value, and what it means to design in an AI-first world.

Comment: If you've launched an AI feature only to watch users abandon it, this course might be for you:

Open article: UX Design for Agentic AI Applications by Rupa Chaturvedi on Maven by bit.ly

UX Design for Agentic AI Applications by Rupa Chaturvedi on Maven

The fastest way to lose trust in AI is to take agency away from the user.

In our focus on making AI feel "smart," we've overlooked a fundamental truth: agency is not a nice-to-have, but the foundation of trust. 

Skepticism is a rational response when users feel like AI is happening to them, not with them. This is especially critical in AI-powered workflows where outcomes are probabilistic, not deterministic.

People are far more willing to rely on an AI system if they understand:

- What the system is doing
- How decisions are made
- The boundaries around what the AI will and won't do
- How to steer, correct, or pause the system

People do not want automation that overrides their judgment, they prefer systems that respect it. Trust in AI is not earned by hiding complexity, but by designing interactions where people remain active participants.  

If we want long-term trust in AI products, we need to stop designing "hands-off magic" and start designing for shared control.

Reforge

Senior Lifecycle Marketing Manager

Instacart

Engagement Marketing Manager, CRM

IPSY

Lifecycle Marketing Program Manager, Engagement

Lifecycle Marketing Program Manager, Acquisition

Lifecycle Marketing Specialist, Growth

Path2Imperfection_

•Leveraged Instagram to build a community of over 1.2K followers by providing followers with practical advice including health and wellness tips, recipes, and mindfulness exercises to motivate and sustain physical and mental well-being.

Wellness Thought Leader and Blogger

Transiris Corporation

•	Coordinated Marketing Team members located across North America and Europe
•	Lead strategy, execution and optimization of demand generation email campaigns
•	Generated and uncovers actionable insights from post campaign reporting
•	Defined tasks and manages timelines of marketing projects in Asana
•	Created content for pitch decks, brochures and company website
•	Managed company Facebook and LinkedIn profiles
•	Imported, updated and generated reports of customer data in Salesforce
•	Organized company events and sponsorship at conferences

Marketing Coordinator

Boost Media

•	Developed case studies, infographics and data sheets
•	Managed and contributed bi-weekly to the company blog
•	Created content calendars for collateral, social media posts and event materials
•	Defined social strategy and leveraged Hootsuite to share content on Twitter, Facebook, LinkedIn and Instagram

Social Media Marketing Assistant

Epitaph Records

•	Conducted market research to define influencers and understand industry landscape
•	Generated artist social engagement report for Facebook, YouTube and Twitter
•	Developed social media promotion process for record releases and events

Social Media Marketing Intern

Social Media Club at UC Berkeley

•	Expanded Social Media Club at UC Berkeley's page likes from 12 to 230 likes by promoting content generated by our social justice campaign "Bear Bodies" as well as content regarding campus life at Cal.
•	View digital portfolio: http://kdcoghlan31691.wix.com/smcucbportfolio
•	Developed Social Media Club at UC Berkeley "Harlem Shake" video with over 1,500 views on YouTube

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taplio

The Battle

Rupa Chaturvedi

Kate Coghlan

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Rupa Chaturvedi's LinkedIn Performance

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Performance ScoreRupa Chaturvedi's LinkedIn Performance