Microsoft CPO: If you aren’t prototyping with AI you’re doing it wrong | Aparna Chennapragada

Microsoft CPO: If you aren’t prototyping with AI you’re doing it wrong | Aparna Chennapragada

Lenny's PodcastMay 18, 20251h 1m

Aparna Chennapragada (guest), Lenny Rachitsky (host), Narrator, Narrator

AI-driven product development and rapid prototyping (“prompt sets as the new PRDs”)Agents: definition, capabilities, and how they change software and workNLX (natural language interfaces) as the new UX and its design principlesDifferences between consumer vs. enterprise product building, especially around governanceThe evolving roles of product managers, engineers, and “software operators” in an AI worldFrameworks for zero-to-one products (tech, behavior, and business model shifts)Career lessons, failure (Google Now), and “living one year in the future”

In this episode of Lenny's Podcast, featuring Aparna Chennapragada and Lenny Rachitsky, Microsoft CPO: If you aren’t prototyping with AI you’re doing it wrong | Aparna Chennapragada explores microsoft CPO explains why AI prototyping and NLX will reshape products Aparna Chennapragada, Microsoft’s Chief Product Officer, shares how AI is transforming product development, enterprise software, and the future of work. She argues that every product builder should be rapidly prototyping with AI and treating prompt sets as the new PRDs, while distinguishing between “solve” and “scale” phases of product building.

Microsoft CPO explains why AI prototyping and NLX will reshape products

Aparna Chennapragada, Microsoft’s Chief Product Officer, shares how AI is transforming product development, enterprise software, and the future of work. She argues that every product builder should be rapidly prototyping with AI and treating prompt sets as the new PRDs, while distinguishing between “solve” and “scale” phases of product building.

She introduces concepts like agents (autonomous, multi-step, naturally interactive tools) and NLX—natural language interfaces—as the new UX, with their own emerging design primitives such as prompts, plans, and showing work. Aparna also explains why PMs and coding are far from dead; in a world flooded with ideas and prototypes, tastemaking, editing, and computer science-thinking become more valuable.

Drawing on experiences from Google, Robinhood, and now Microsoft, she discusses enterprise constraints (governance vs. usability), how she operationalizes “living one year in the future” via Microsoft’s Frontier program, and lessons from past failures like Google Now. She closes by imagining co-working environments where humans and AI agents collaborate in real time to produce far more than either could alone.

Key Takeaways

If you’re not prototyping with AI, you’re building too slowly.

Aparna insists that new features and products should come with live demos and prompt sets; AI drastically shortens the time to first demo and improves communication within teams, even if deployment and scaling still take time.

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NLX—natural language interfaces—are becoming the new UX layer.

Conversational products aren’t just “the model leading the product”; they require deliberate design of prompts, plans, follow-ups, and how much internal reasoning to expose, just like buttons and menus in GUIs once did.

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Agents are defined by autonomy, complexity handling, and natural interaction.

Good agents can take delegated goals, execute multi-step, non-trivial tasks asynchronously, and interact through rich, natural modalities (not just chat), for example, preparing a persuasion strategy for a high-stakes meeting.

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Separate “solve” mode from “scale” mode in zero-to-one work.

Early on, teams must tolerate chaos, wide lurches in direction, and avoid premature metrics and over-optimization; only after finding a real ‘set timer and play music’ use case should you lock into scaling and hard metrics.

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AI increases the supply of ideas, so editorial taste matters more.

As engineers, designers, and others can prototype rapidly with AI, PMs and leaders must lean into tastemaking and editing, earning influence by judgment rather than title, or risk shipping Frankenstein products.

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Coding and computer science understanding are not obsolete—just shifting abstraction levels.

AI will turn many more people into ‘software operators’ working at higher levels of abstraction, but the underlying CS mental models remain crucial for specifying, debugging, and reasoning about complex systems.

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Update your priors: AI improves faster than your habits.

Aparna notes that many people underutilize AI because they still judge it by last year’s limitations; she even built a Chrome extension that asks on every new tab, “How can you use AI to do what you’re going to do right now? ...

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Notable Quotes

In this day and age, if you’re not prototyping and building to see what you want to build, I think you’re doing it wrong.

Aparna Chennapragada

NLX is the new UX.

Aparna Chennapragada

Prompt sets are the new PRDs.

Aparna Chennapragada

Being early is the same as being wrong.

Aparna Chennapragada

Excel is proof that non-coders also have to program.

Aparna Chennapragada (relaying an Excel PM’s insight)

Questions Answered in This Episode

How should teams practically redesign their product development process around AI prototyping and prompt sets without creating chaos?

Aparna Chennapragada, Microsoft’s Chief Product Officer, shares how AI is transforming product development, enterprise software, and the future of work. ...

Get the full analysis with uListen AI

What are the most promising new NLX “UI elements” you’ve seen beyond prompts, plans, and showing work, and how should designers approach them?

She introduces concepts like agents (autonomous, multi-step, naturally interactive tools) and NLX—natural language interfaces—as the new UX, with their own emerging design primitives such as prompts, plans, and showing work. ...

Get the full analysis with uListen AI

Where is the line between helpful agent autonomy and uncomfortable loss of control for users and enterprises, especially around governance and compliance?

Drawing on experiences from Google, Robinhood, and now Microsoft, she discusses enterprise constraints (governance vs. ...

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How can aspiring PMs and engineers best cultivate the kind of editorial taste you say becomes critical in an AI-saturated idea space?

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If you were rebuilding something like Google Now today with current AI capabilities, what would you do differently in product scope and interface design?

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Transcript Preview

Aparna Chennapragada

I have a cheesy Chrome extension. Literally, whenever I open a new tab, it just says, "How can you use AI to do what you're going to do right now?"

Lenny Rachitsky

How do you see the future of product development being different?

Aparna Chennapragada

If you're not prototyping and building to see what you want to build, I think you're doing it wrong. It becomes even more important to have the territorial and taste-making at the heart of it, because otherwise you just have a Frankenstein product.

Lenny Rachitsky

There's this acronym that you taught me, NLX. What is that?

Aparna Chennapragada

Natural language interface. NLX is the new UX. Often I hear, uh, product builders say, "Oh, yeah, with AI, like, the model leads the products." That doesn't mean it's not designed. You and I are having a conversation. It's a podcast. I'll have another conversation, uh, at Microsoft and that's a meeting. Conversations also have grammars, they have structures, they have UI elements. They're invisible. What are the new principles, new constructs in natural language as a interface?

Lenny Rachitsky

I just saw that Cursor hit 300 million ARR in two years. Interestingly, you guys were very well positioned to do really well in this AI coding tool space. You guys had Copilot, the first tool in the world at this stuff. So ahead of everyone. What happened?

Aparna Chennapragada

I would say-

Lenny Rachitsky

Today, my guest is Aparna Shenapragada. Aparna is chief product officer at Microsoft, where she oversees AI product strategy for their productivity tools and their work on agents. Previously, she was chief product officer at Robinhood; vice president at Google, where she worked on Google Lens, Search, Shopping, augmented reality, AI Assistant; and a lot more. She was also a longtime engineering leader at Akamai, and on the board of eBay and Capital One. In our conversation, we chat about how working in B2B is like being Jean-Claude Van Damme doing the splits across two moving trucks, how she's operationalizing her team living in the future so that they're building towards where things are going, why people still need to learn to code, why the PM role isn't going anywhere, why NLX is the new UX, and so much more. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of a bunch of products, including Linear, Superhuman, Notion, Perplexity, and Granola. Check it out at lemmysnewsletter.com and click BUNDLE. With that, I bring you Aparna Shenapragada. This episode is brought to you by Eppo. Eppo is a next generation A/B testing and feature management platform built by alums of Airbnb and Snowflake for modern growth teams. Companies like Twitch, Miro, ClickUp, and DraftKings rely on Eppo to power their experiments. Experimentation is increasingly essential for driving growth and for understanding the performance of new features, and Eppo helps you increase experimentation velocity while unlocking rigorous deep analysis in a way that no other commercial tool does. When I was at Airbnb, one of the things that I loved most was our experimentation platform, where I could set up experiments easily, troubleshoot issues, and analyze performance all on my own. Eppo does all that and more with advanced statistical methods that can help you shave weeks off experiment time, an accessible UI for diving deeper into performance, and out-of-the-box reporting that helps you avoid annoying prolonged analytic cycles. Eppo also makes it easy for you to share experiment insights with your team, sparking new ideas for the A/B testing flywheel. Eppo powers experimentation across every use case, including product, growth, machine learning, monetization, and email marketing. Check out Eppo at geteppo.com/lenny and 10X your experiment velocity. That's geteppo.com/lenny. This episode is brought to you by Pragmatic Institute, the trusted leader in product expertise. Pragmatic Institute helps product professionals turn ideas into impact through proven courses, workshops, and certifications designed for real world success. For over 30 years, they've trained more than 250,000 product leaders at companies like Google, Microsoft, and Salesforce, equipping them with practical strategies to build and scale market winning products. Pragmatic's full-time instructors each bring over 25 years of hands-on leadership experience, teaching strategies proven to deliver real world results. And it's not just about what you learn, it's also about who you learn it with. Completing a course connects you to an active community of over 40,000 product professionals. You'll engage in meaningful conversations, collaborate with peers and mentors, and gain direct instructor access to refine your strategies and stay ahead of trends. Get 20% off with code LENNY20 at pragmaticinstitute.com/lenny. Aparna, thank you so much for being here and welcome to the podcast.

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