Rupa Chaturvedi

Human Centered AI Institute

Founder

Vybe Snacks

Stanford University

Adjunct Lecturer (Product Design)

Miraj Sustainable Racing Club

California's first sustainable racing club

Founder & President

Reforge

Co-created the "Generative AI Products: How to get from Idea to MVP" course for product managers, design and user research leaders, consultants and founders. Understand AI by getting hands-on with this practical course taught by industry experts.

Partner

Uber

Head of Merchant & Ads Design

First Round Capital

Product & UX Design Mentor

Google

UX Design Manager

Amazon

I manage and lead a team of UX and Personality designers focused on Conversational AI within the Alexa Shopping group in Amazon. Collectively, my team and I conceptualize, deliver design and strategy to help launch customer experiences that span upper funnel, inspiration and product discovery; product evaluation and research, and post purchase needs of our customer. We are fierce advocates for our customers and leverage multiple sources of data from qualitative to quantitative to guide our intuition and measure our efficacy. The impact we have generated is a combination of customer experience vision, strategic frameworks and mental models as well as design systems for interaction with Alexa by voice and devices in the context of shopping.

Sr UX Designer, Alexa Shopping

Lead UX Designer for Augmented Reality (AR) experiences at Amazon

Sr UX Designer

Sentient Technologies

Helped launch an AI-enabled shopping product that will change the way shoppers shop online. 
Conceptualized and designed multi-channel user experiences for a breakthrough visual search technology product - redefining how consumers shop online.

Helped launch a breakthrough AI enabled online shopping product within 5 months.
Contributed from conceptualizing the UI and product strategy/features to final implementation through whiteboard sketches, wire-frames, high fidelity prototypes and design specifications.

Followed a thorough user centered design process to gather insights into shopper behavior and expectations as well as iterative design based on feedback from user testing.

Head of Design - Visual Intelligence

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

I'm building a world-class AI education institute that puts humans at the center of the AI revolution. Our mission is to empower professionals worldwide to create AI solutions that deliver tangible value for both businesses and end users. We're committed to making AI education accessible, enabling people from all backgrounds to help shape technology's future.

Hard truth for UX designers: if your role looks the same in 2 years, that’s a red flag.

If your value is defined by producing UI artifacts (wireframes, mockups, and redlines) you are in a precarious position. AI models are already exceptionally good at pattern matching and interface generation.

But if your value is defined by system design, you have never been more necessary.

There is a shift from "designing for the user" to "designing for the system."

When an AI agent acts on behalf of a user, it doesn't need a UI. It needs:

- Behavioral Specs: What is the acceptable range of autonomy for this model?
- Adaptive Context: How does the system pivot when the user’s intent is ambiguous?
- Human-in-the-Loop Protocols: When must the human step in for oversight?

These are design responsibilities. They require moving upstream to shape what the system learns and how it decides.

This is exactly why I developed the Advanced AI & Agentic Design curriculum. We stop looking at screens and start looking at system behaviors. We focus on defining constraints, designing for non-deterministic outcomes, and building trust in autonomous flows.

The designers who survive this shift will be the ones who can define the guardrails of the systems we are building. Learn more here: https://bit.ly/3MjqTzM

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

Google's Head of Product announced a shift from "writing-first to building-first culture."

Microsoft's CPO said "prompt sets are the new PRDs."

Product management went through a transformation in the past 18 months that UX designers are just starting to feel.

When you can see a shift happening in an adjacent discipline, you have visibility others don't. The question is whether you use it strategically.

I've been mapping what the PM precedent signals for UX roles—and how designers can position themselves while the industry is still figuring out what these roles look like.

Check out my latest newsletter for more on this:

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: Redefining UX Value: The Shift from Execution to Influence by Rupa Chaturvedi • 5 min read

Redefining UX Value: The Shift from Execution to Influence

Meta, Google, OpenAI, Anthropic - they're paying AI PMs up to $600K+.
Why? Because these PMs aren't writing PRDs anymore. They're architecting intelligent systems - designing model behavior, shaping evaluation frameworks, defining how AI thinks and decides.

The role has evolved from coordination to creation. And the market is paying accordingly.

Designers have a unique opportunity here. System thinking, behavioral specification, mental models - these are already in our DNA. Now it's about applying them to intelligence architecture.

Product's transformation is our preview. They're 12-18 months ahead on this curve, and their playbook is completely visible. We can see exactly which capabilities the market values and how to develop them.

In this week's issue, I break down what designers can learn from Product's transformation - the specific capabilities commanding these salaries and strategies for positioning themselves effectively.

Open article: The $600K Question: What AI PMs Know That UX Designers Don't (Yet) by Rupa Chaturvedi • 6 min read

The $600K Question: What AI PMs Know That UX Designers Don't (Yet)

I got a message this week from a UX Director at a FAANG company 6 weeks after completing MXDAI:

“Org changes have been constant here, and the structure is getting flatter every quarter. The expectations on designers have shifted too. My team and I are being pulled into more conversations about how the AI behaves, not just how it looks on the surface. PM and Eng expect us to have a clear point of view there, and if we don’t, we’re not really influencing the product. MXDAI helped me step into those conversations with more confidence. It’s made a noticeable difference in how I show up and how my team gets included.”

What resonated with me is how common this has become.

Across companies, designers are being asked to take on a level of strategic influence that isn’t written into the job description but is now core to how teams move forward. 

As orgs continue to flatten, leaders and ICs are figuring out how to stay relevant in a landscape where expectations rise even as layers disappear. The people who can bring clarity to messy AI questions and ambiguous decisions are the ones carrying a different kind of weight.

This is the work we focus on inside MXDAI.

We’re currently the number one AI design course on Maven, and now you know why.

Maven also extended the promo for one more day today, in case you’ve been considering joining the next cohort - take advantage of the 25% tuition discount - offer expires tonight/

If you’re facing similar changes or want to get ahead of what’s coming, feel free to reach out.

cc Maven

There’s been so much talk lately about PMs vibe-coding prototypes and PRDs being replaced with “just build something and show me.”
But here’s what I keep coming back to: designers need these skills just as much as PMs do, maybe more.

Our stakeholders are adopting AI tools at a pace that’s hard to ignore. The workflows between design, product and engineering are shifting fast. If designers don’t build fluency in this space, they’ll get left behind.

Vibe coding isn’t about learning to code. It’s about learning to build.

When you can build with AI tools, even scrappy prototypes, you collapse the distance between an idea and something you can actually interact with. You get to explore AI behaviors and edge cases hands-on instead of trying to explain them through diagrams and long documents.

And as you experiment with different tools, you start developing a deeper understanding of the underlying tech, the constraints, the limitations and what’s truly feasible. That knowledge changes how you design. It sharpens your instincts. It gives you language and clarity your stakeholders instantly recognize.

This is also where designers make a shift. You stop worrying about perfect wireframes and start focusing on how to validate your assumptions. You move from being the person who “hands things off” to becoming a strategic partner who brings real, testable workflows to the table.

Designers who lean into this aren’t just speeding up their process. They’re shaping how AI products come to life.

If you’re ready to invest in these skills, take a look at MXDAI: https://bit.ly/48o50YD 
We learn by doing. You’ll explore a range of AI tools, build real workflows, and leave with a portfolio-worthy project that reflects how AI design actually happens today.

NOTE: Currently, Maven is offering a flat 25% discount on the next cohort and its valid only for this. week.

Anne T. Griffin

Product Management | AI and Blockchain

I help companies pinpoint where AI can create defensible advantage and help them move faster than the market, not just keep pace. I focus on shipping AI products that deepen retention, drive account expansion, and become meaningfully hard for competitors to replicate.I work with founders and product leaders who need someone who can operate with high agency: someone who can walk into ambiguity, talk to customers, understand data and technical constraints, and turn that into a product direction the company can actually ship.What this actually looks like in practice:• Identify the specific workflows, pains, or decisions where AI can create real leverage• Validate through lightweight prototypes before major engineering investment• Ship capabilities that meaningfully create value for customersHow I approach the work:• Research the market, competitive landscape, and emerging alternatives to understand where the space is moving• Apply futures practices to identify where AI can create durable, long-term advantage• Analyze the company’s value chain to pinpoint where AI can amplify strengths or remove friction• Work directly across product, engineering, data, design, and GTM so alignment happens during the build, not after• Reduce cognitive load for founders and teams instead of adding to itI have 14+ years of experience building products in 0 to 1 startups and in Fortune 500 giants in multiple industries, including AI and blockchain. I've also served as interim Head of AI / Data Science operations for a scaling startup. I've worked across B2C, B2B2C, and B2B SaaS. Translating strategy and technical topics into a message people can understand is one of my super powers, and that has given me the opportunities to guest lectures at Columbia and West Point.I also teach Jumpstart Your AI Career for Pearson on O'Reilly. I love exploring the realities and possibilities of emerging tech in my writing as a Forbes Contributor on the topics of AI and Strategy. My insights on AI and tech have been highlighted in Rolling Stone and The Atlantic. My product blog: https://productmindlab.substack.com/My Talks: https://www.annetgriffin.com/talks-lectures

Senior Product Manager

- Lead product vision and strategy for a AI/ML product for a cross-functional team to rebuild customer trust and mitigate risk of churn
- Increased ARR by $480,000 by leading a team to build self-serve features on the core product experience, removing the dependency to onboard with the customer success team
- Owned the roadmap and prioritized key initiatives to increase revenue and enable new generative AI product
- Established user-centric practices with continuous discovery user research, implementing with ideal customer personas, using insights to de-risk and prioritize new features and key investments sharing insights
- Developed best practices for cross-functional collaboration with marketing, sales, engineering, design, and customer success
- Mentored a junior, first-time product manager team member, accelerating their growth to a promotion

Today in Forbes: There are over 3,000 AI courses on Coursera alone, and a lot of AI experts popping up every day. How are companies supposed to find the right AI training for their workforce? I'm writing about enterprise AI training/upskilling, and I talked to people leaders and AI educators to learn what to look for and what outcomes are possible. This article is great for leaders who are doing their budgets for 2026 now and considering enterprise AI training.

Thank you to the leaders who spoke with me: Edwin Trebels, Founder of LangOptima, Mike Russo, Head of Product at Auction.com, Pari Katyal, Director of Product, Bola AI. Your advice here and outcomes will be incredibly helpful for other leaders to understand what's possible.

And thank you two the amazing AI educators I spoke to who build AI training programs and shared their insights: Helen Lee Kupp, Founder of Women Defining AI, and Mariena Quintanilla, CEO and AI Educator at Mellonhead.

#ai #aieducation #aitraining #artificialintelligence #leadership

Anne T Griffin

AI Product Leader and Product Futures | I help teams move from ambiguity to shipped AI products and real competitive advantage | Teaching AI for Pearson on O’Reilly and writing about AI in Forbes

Ask: If you consider yourself "non-technical" (whatever that may mean to you), what was your favorite AI class or workshop you took in 2025? What was it, why did you like it, and what skills did you gain and did you get to apply those skills at work yet? 

Writing a new article and this is for research. Please share with friends.

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