Becoming an AI PM | Aman Khan (Arize AI, ex-Spotify, Apple, Cruise)

Aman Khan is Director of Product at Arize AI, an observability company for AI engineers at companies like Uber, Instacart, and Discord. Previously he was an AI Product Manager at Spotify on the ML Platform team, enabling hundreds of engineers to build and ship products across the company. He has also led and worked on products at Cruise, Zipline, and Apple. In our conversation, we discuss: • What is an “AI product manager”? • How to break into AI PM • What separates top 5% AI PMs • How to thrive as an individual-contributor PM • Common pitfalls to avoid when building AI products • The importance of energy and curiosity in product roles • Much more — Brought to you by: • Pendo—The only all-in-one product experience platform for any type of application: https://www.pendo.io/lenny • Vanta—Automate compliance. Simplify security: https://vanta.com/lenny • Paragon—Ship every SaaS integration your customers want: https://www.useparagon.com/lenny Find the transcript at: https://www.lennysnewsletter.com/p/becoming-an-ai-pm-aman-khan Where to find Aman Khan: • X: https://x.com/_amankhan • LinkedIn: https://www.linkedin.com/in/amanberkeley/ • Website: https://amanalikhan.com/ Where to find Lenny: • Newsletter: https://www.lennysnewsletter.com • X: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ In this episode, we cover: (00:00) Aman’s background (06:16) Understanding AI product management roles (13:29) Getting started as an AI product manager (18:14) Building a portfolio and standing out (22:31) Why product management is not dead (28:56) How to thrive as an AI product manager (35:42) Finding good ideas that are AI-oriented (39:27) Be careful not to automate away every customer experience (42:53) What separates top 5% AI PMs (46:55) Key habits for long-term IC success (52:48) The importance of energy in meetings (57:00) Wandering vs. waiting (01:01:41) Amplifying signal through AI tools (01:03:18) Just have fun (01:05:36) Lightning round Referenced: • AI Resources and Tools for PMs (Updated Oct 2024): https://open.substack.com/pub/amankhan1/p/ai-resources-and-tools-for-pms-updated • Unlocking the AI PM Dream: Your Roadmap to Success: https://amankhan1.substack.com/p/unlocking-the-ai-pm-dream-your-roadmap • Arize: https://arize.com/ • Ryzen: https://www.amd.com/en/products/processors/business-systems/ryzen-ai.html • NotebookLM: https://notebooklm.google/ • Figma: https://www.figma.com/ • Cursor: https://www.cursor.com/ • Replit: https://replit.com/ • Excalidraw: https://excalidraw.com/ • Vercel: https://vercel.com/ • v0: https://v0.dev/ • How Airbnb Proved That Storytelling Is the Most Important Skill in Design: https://www.inc.com/yazin-akkawi/the-surprising-technique-airbnb-uses-to-better-sell-an-experience.html • Brian Chesky’s new playbook: https://www.lennysnewsletter.com/p/brian-cheskys-contrarian-approach • Midjourney: https://www.midjourney.com/ • Dall-E: https://openai.com/index/dall-e-3/ • Introducing the Realtime API: https://openai.com/index/introducing-the-realtime-api/ • Intro to Large Language Models | Andrej Karpathy: https://www.youtube.com/watch?v=zjkBMFhNj_g • Watch Me Build an App in 60 Minutes With o1 and Cursor: https://www.youtube.com/watch?v=9Zmhe6_T-xU • Greg Isenberg on LinkedIn: https://www.linkedin.com/in/gisenberg/ • Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor • Spotify: https://open.spotify.com/ • Instacart: https://www.instacart.com/ • How to grow a subscription business | Yuriy Timen (Grammarly, Canva, Airtable): https://www.lennysnewsletter.com/p/transform-your-subscription-growth • When Identifying the Problem Isn’t Enough: Lessons from Boxed Cake Mix by Ann M. Aly, TechFlow Director of Human Centered Design: https://www.techflow.com/when-identifying-the-problem-isnt-enough-lessons-from-boxed-cake-mix/ • Waymo: https://waymo.com/ • The Ikea effect: https://thedecisionlab.com/biases/ikea-effect • Blue Apron: https://www.blueapron.com/ • Unorthodox PM wisdom: Automating user insights, unselling job candidates, logging every decision, more | Kevin Yien (Stripe, Square, Mutiny): https://www.lennysnewsletter.com/p/unorthodox-pm-wisdom-kevin-yien • LeBron James: https://en.wikipedia.org/wiki/LeBron_James • The Secrets Behind Lyft’s Dynamic Culture: https://www.forbes.com/sites/marissaperetz/2018/05/16/the-secrets-behind-lyfts-dynamic-culture/ • Aparna Dhinakaran on LinkedIn: https://www.linkedin.com/in/aparnadhinakaran/ ... References continued at: https://www.lennysnewsletter.com/p/becoming-an-ai-pm-aman-khan Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Lenny may be an investor in the companies discussed.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  What if the product manager came to the meeting with prototypes? What if you come to the design team and instead of a PRD, you actually already have your mocks? With AI, it's super feasible for a product manager to come to a meeting and say, "Hey, I already have some ideas here. I wanted to mock them up this way." They're probably wrong, but at least the starting point now looks a little bit higher resolution.

• 0:20Lenny Rachitsky?

  For people that want to pivot their career to be an AIPM, what helped you move in that direction?

• 0:27Speaker 00

  It's almost counterintuitive, but I actually think it's probably easier now to break into AI product management than it was before. There are these incredible videos that are being put out right now on YouTube on how to build an app in like an hour. That would not have been possible even a year ago. Before, you actually probably needed to have more of a foundation and background in machine learning to get a shot at one of these companies, building AI products.

• 0:51Lenny Rachitsky?

  What have you seen separates the typical AI product manager from, say, the top 5%?

• 0:57Speaker 00

  Really, the question you have to ask yourself is...

• 1:04Lenny Rachitsky?

  Today, my guest is Aman Khan. Aman is Director of Product at Arise AI, and over the course of his PM career, he's focused on building products in the AI space, including at Spotify on the ML platform team, and roles at Cruise, ZipLine, and Apple. He's also very intentionally stayed an individual contributor, which feels like a trend, especially with the rise of AI tooling making PMs much more productive, and companies cutting back on management layers. And so, in our conversation, we go deep on these two topics: how to get into AI and how to become an AI product manager, what the different types of AI product managers are, how to thrive as an AIPM, and what Aman has learned about how to be successful

• 1:45Lenny Rachitsky?

  and continue his career as an individual contributor PM long-term. When I asked people on Twitter and LinkedIn who their favorite individual contributor product manager is, Aman was near the very top of the list, and so I was really excited to get him on the podcast and to learn from his experience. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes, and it helps the podcast tremendously. With that, I bring you Aman Khan.

• 2:16Lenny Rachitsky?

  Amon, thank you so much for being here and welcome to the podcast.

• 2:20Speaker 00

  Amazing. Thank you so much for having me, Lenny. It is truly an honor to be here.

• 2:24Lenny Rachitsky?

  So let me give a little context on this conversation. I put out a call on Twitter and LinkedIn asking people for their favorite IC product managers and you came up near the top of the list across both Twitter and LinkedIn. So I knew that I needed to meet you and you're super interesting in a couple of ways. One is if I think about the Venn diagram of some of the most interesting trends in product right now, you're kind of at the center of AI and staying IC, an individual contributor for a long time. And my sense is a lot of PMs are thinking about how do I get into AI and how do I do more AI work? Two, there's this trend of just like ICs, super ICs, less managers. And you've been doing AI for a long time. You've been in IC for basically your whole career, very intentionally. So

• 3:09Lenny Rachitsky?

  with that, there's a few things I want to spend our time on. One is how to get into AI, how to become an AIPM essentially. Two is how to thrive as an AIPM. And three is how to thrive as an IC outside of AI, but I know AI plays into that broadly. How does that sound?

• 3:28Speaker 00

  Yeah, that sounds great. I mean, I think that was like a crazy moment of just seeing how many people piled onto that, to those posts. And then, you know, some of our discussion back and forth on this thread. And I thought it was like super interesting. It was like this combination of, you know, product and AI where I just happens to be like, I think where the space is headed or, you know, what seems to be catching so much attention. So yeah, I'm super excited to dive into that and try and share a little bit what, you know, that I've learned along the way as well.

• 4:00Lenny Rachitsky?

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• 4:45Lenny Rachitsky?

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• 5:24Lenny Rachitsky?

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• 6:08Lenny Rachitsky?

  when you go to vanta.com/leni. That's V-A-N-T-A dot com slash leni.

• 6:17Lenny Rachitsky?

  Let's start with getting into AIPM, becoming an AIPM. There's this term that we hear a lot in AIPM. There's like bootcamp certifications, become an AIPM. What's the simplest way for people to understand what that means, other than just it's a PM that works with AI? Is there something more concrete that you think about when you see that title?

• 6:34Speaker 00

  So product manager is responsible for bringing together, you know, design, engineering, the biz dev people, operations, sales, what have you at the organization and going and shipping impact. So you're responsible for representing the customer and ultimately getting to a solution to solve their problems. I think in addition to that, the AI component is, I really break it down into maybe three flavors of AI product management. So the first is AI platform PMs. And that's kind of where I find myself. These are people who are building tools for AI engineers. So for context, you know, I work at a company called Arise. We're a observability and evaluation platform for artificial intelligence. We've been around for a few years.

• 7:19Speaker 00

  We started with machine learning and, you know, sort of ranking, regression, classification models, basically any recommender system or black box you might find in an application. And we've slowly been translating and pivoting over into broadly speaking, any type of AI. These days, it's a lot of large language models. And so I think that, you know, with the rise of all of these tools that are being built on top of, you know, OpenAI's APIs or Anthropic APIs, basically any tools on top of the large language model providers, there's, it's actually pretty clunky. Like these, these interfaces are pretty new. We've only really had people building on top of large language models for a couple of years. And so the whole space is really nascent and the tools that you would use to build

• 8:02Speaker 00

  on top of and understand, is my app doing the thing I expect it to do is, is really, really early. So that's sort of the space I'm, I'm focused on around, you know, enabling AI engineers to understand the impact and, you know, if you're an AIPM at another company, one of our customer companies, you understand that, you know, when you go to leadership, that my, my app is actually doing something and doing what I expect it to do on the end business. I think on top of that, there's also AI product PMs. And AI product PMs are really the flavor of PM where the core product is centered around AI. And an example of that would actually be something like a chat GPT.

• 8:43Speaker 00

  It's the core kind of tech or actually another good example would be, you know, you had Rise on and Notebook LM is a really great example of that, too. And what I mean by that is the core experience is enabled by the model underneath the hood. That's sort of the secret sauce. It's like, you know, you have these researchers and engineers really pushing the boundaries of technology forward in AI. And then your job is really to package that technology and make it consumable for either a business or enterprise or a consumer to really utilize that tech in some way. So that's sort of the AI powered PM role where the core competency, the core tech is really the, you know, what you're packaging and distributing.

• 9:26Speaker 00

  I think the third type of PM here is really, you know, the one we were talking about a little bit earlier, which is this concept of like you're an AI powered PM. And to that end, I think that you're going to be enabled by AI technology across the entire stack of the role you might already be doing as a product manager. And we'll get into like a little bit what that means as well. I have some ideas and thoughts around that. But really what what an AI powered product manager in my mind does is you're not really responsible for building the core model from the ground up. Maybe you don't have the access to the resources or research teams that you might have at like a Google or OpenAI, but you can still utilize large language models or models of any kind, really,

• 10:10Speaker 00

  to build an experience that is best for your customers. And that's really, I think, where a lot of PMs will also start trending towards as AI becomes more pervasive from a technology standpoint. It almost feels a little bit like AI will be as common as the database to some degree for SaaS applications. And so I think that's really where, you know, if you really break it down, I kind of see in the future, you know, in the near future, most PMs are probably going to be one flavor of an AI product manager, either building tools for other PMs or other other companies that are deploying AI. Maybe you're behind one of, you know, the cutting edge models that's going to go and, you know, be the next Notebook LM. Or you're building around, you know, a transformer of some kind or a GPT model

• 10:54Speaker 00

  that's doing some part of the work that you would want to do to solve a customer's problem.

• 10:59Lenny Rachitsky?

  Let's actually make it even more real. What are some tools you use in your PM work to be more efficient and productive?

• 11:06Speaker 00

  I'm obsessed with Cursor. I'm obsessed with Replit. These are tools I use all the time to just really build a prototype and try to understand myself. What's possible? That kind of is is super enabling for a product manager to show up with a functional prototype. It's not going to be the thing you go and ship in production, but at least the buttons work. And maybe it's like wired up, you know, reasonably correctly to tell to tell a story. There's a really great tool. A lot of folks might be familiar with Versale if you're trying to create a landing page. So Versale now has a sort of starting point called V zero, which allows you to type in a prompt and get a really beautiful landing page on top of that. And so, and it doesn't have to be just a landing page.

• 11:49Speaker 00

  If you prompt it correctly and iterate with it, you could actually get a pretty good working UI as well. So I think that kind of gives you a good starting point for some of those initial mockups you might be having with the design team. I also think if you're designing interfaces, you might want to use AI for graphic design. Perhaps you're trying to come up with a logo or you're trying to come up with something that, you know, resembles almost like the user story you want to tell in some way and make it like a visual user story. I think that becomes so much more approachable with tools like Mid Journey or even Dolly. And it's really at your fingertips to how well can you prompt this thing to get you the output that you want? So to me, it really depends.

• 12:30Speaker 00

  I think if you're an experiences company, you're a little, you're, you might trend a little bit more visual. Tools like image generation might be really powerful, too. So that's one example. And then I think even for like 3D modeling, you know, there's some emerging tools there. I'm definitely not the expert on that domain, but there's a lot in terms of, you know, if you're building physical products, that's gotten a lot easier as well.

• 12:53Lenny Rachitsky?

  Okay, awesome. I want to come back to kind of where we started here. So you've shared three types of AI product managers.

• 13:01Lenny Rachitsky?

  We've been focusing on the third, which I wanted to get to, and I love that we went there, which is just how to be more productive, efficient, better as a PM using all these amazing tools that now exist. The first two are, just to refresh folks' memory, one is becoming kind of basically an infrastructure PM. That's something that you're doing, basically building like the base models and tools. And then the other is building the UX and actually consumer experience of a product that happens to integrate AI to make it better. So I'm guessing when people think AIPM, that's probably where they're like, I want to build products that deeply integrate AI. For people that want to pivot their career to be an AIPM, what helped you

• 13:44Lenny Rachitsky?

  move in that direction? What would you recommend folks try to do and learn to be able to get a job in one of those two buckets?

• 13:53Speaker 00

  I feel a little bit like an outsider on the space myself. So I studied, you know, I wasn't related at all. You know, the field I studied was mechanical engineering. I didn't really take computer science courses, or I had to learn a lot of that on my own. And I didn't take like machine learning or AI courses either. I don't have a PhD or masters in the subject. But coming back to the, to both types of product managers you just described, there's the AI PM who's building infrastructure for other AI engineers, and there's the AI powered product manager who's building AI products, really. And I think in both cases, you care about the end customer. At the end of the day, you really want to be in love with the problem. I know

• 14:35Speaker 00

  you already said that. That was like a great, great, great quote in my mind as well of, if you're in love with the problem, you're trying to push the boundaries of what's possible with technology to solve that problem. And for me, I just, I really became kind of obsessed with trying to help really technical users, AI engineers, data scientists, with problems that I thought were, you know, not super challenging. Like, how do I build a dashboard to understand how my model is working? That can't be that hard to do, right? And then as you get deeper, the complexity sort of starts to emerge in that part of the stack. And you have to realize you're pushing, you're pushing, you're actually responsible for pushing technology forward in some ways. You're trying to see what's possible and keep pushing the space forward to solve that customer problem.

• 15:21Speaker 00

  I think the same thing is true for AI product, you know, product managers, meaning, you know, you're really trying to design the best customer experience and really solve your customers' problems. And I think if you are obsessed with that and you spend time just trying to realize, I mean, what would an ideal experience look like that I'm trying to solve? You'll kind of find tools along the way to help, uh, you know, un- unbox that really, that, that problem. So I think if we like, take, take an example of that, like, let's imagine that you're, you know, you're working for a company that, um, you know, might, might be having customers that have like customer support problems or people coming in with complaints. And when you think about like the surface area of customer support, it's, it's not that great.

• 16:04Speaker 00

  Like you usually have to, you know, type in some questions with a chatbot that's like writing routing, you know, perhaps incorrectly, you know, you to some document to go solve a problem. Or if you're trying to call in, you have to like describe your problem, but you're not really sure if you're being heard correctly. Uh, you, you, it might be super long wait times. And if you're the product manager of that experience, I think an ideal product experience really looks like a customer reaches you with a problem and you're able to really, you know, solve that problem for them. And it doesn't really matter what's in between. You, you kind of want to reduce the friction of that as much as possible. And so now, when you think, okay, let's assume that I'm starting with a phone call. There's a ton of tools that, that are starting to emerge.

• 16:49Speaker 00

  And I think a really cutting edge one from the last couple of weeks has been OpenAI releasing a real time API. And the real time API is basically a voice API where you can provide some text and almost have this real time experience with a bot that is actually AI generated. And if you use, and if you're a consumer, you could even try that out in the application yourself. You can open up ChatGPT and if you're a plus subscriber, you can try this, uh, cutting edge sort of voice chatbot experience. And why is this interesting? Because if you're a consumer and you're, and, and you're trying out technology and you're trying out AI technology and trying to push the boundaries of what's possible, I think you can kind of have that like light bulb aha moment of,

• 17:32Speaker 00

  I can take this thing that kind of feels like it's like early, but it's, could be something here and go take it to my team and say, you know, maybe it's possible for us to use this thing. And so I think that's really what, uh, th- this whole space is about. I want to underscore that it's really, you know, you're really driven by your own curiosity. And your curiosity can push you in a lot of different directions in terms of the types of tools you might want to pick up. Or, you know, for yourself, or even implement in your own product. So I think like it truly is this opportunity for for people to, you know, see what drives them and try and find the tools that that really help, you know, make that experience possible.

• 18:14Lenny Rachitsky?

  To pull on this thread a little bit more, say someone wants to like apply, I want to be an AIPM. There's kind of two questions here. One is, what do you recommend they specifically learn, skill wise, technical wise, to have some chance at becoming an AIPM? If that's like a thing versus just like, hey, just your PM, build awesome products and they happen to integrate AI, that might be the best solution, like if that's your advice, definitely say that.

• 18:42Speaker 00

  I think you're hitting on something on a point that's super relevant to today, which is it almost feels, you know, really competitive now to be in tech and to be a product manager. And the struggle is, you know, really, to your point, what are the skills I should have in the, you know, to really kind of even apply for this role in the first place? And then how do I stand out as an applicant? I kind of feel like these are maybe two distinct things. It's, you kind of want to start with the foundation of what is, what is machine learning, what is AI? What's the, the, the, the knowledge that has really powered this evolution in technology? And you kind of want to keep driving in that direction with what are your interests? So if there's really two dimensions, you're trying to understand,

• 19:26Speaker 00

  okay, what are the things I need to know? And then how can I use that in the, the problems I'm trying to solve or the industries that interest me? So I think there's like this propensity of you want to be driven by that curiosity. So start, you could start with your fundamentals of looking at videos on YouTube of, you know, Andrej Karpathy talking about the foundation of LLMs. It's this great, amazing resource. He put out this video, you know, a little while ago. And it's about an hour long, but you know, you could put it into Notebook LM, maybe you get like a more succinct version. But the idea is that you can, you know, really understand the technology in terms of how it works and what the boundaries are. And then I think that the other dimension is just trying to use the tools to figure out yourself. How can I push the boundaries of what's possible?

• 20:12Speaker 00

  So I think the combination of those two things are really what drive the skill level here. There's no, maybe, maybe to bring this back to an earlier point, there, there is no program. You know, there's no college degree on product management. So there definitely isn't a college degree on AI product management. And so I think the way that you stand out is through showing interest in the space and, and building your own skilled set and skilled stack around what is the foundation of AI and how do I apply it to the industry I'm interested in? And that's actually related to the second point of how do I stand out as an applicant? And it kind of feels like this moment where you can actually go and have a, you know, almost like a portfolio of products

• 20:54Speaker 00

  that you've tried to build and maybe they're just prototypes, but they really help you stand out to a hiring manager that might be deciding, you know, who's the person I want to bring on board? And maybe like, you know, to zoom out for a sec, as someone who's been a part of the like hiring process for AI PMs before, I think the hiring process is really designed to understand sort of three things about a person. And that's can this person do the job I'm hiring them to do? Are they excited to do the work that we do here? And do I like to work with them? And so I think by having this portfolio where you've, you know, if you have that foundation of, of AI and ML, of at least being able to describe what the technology can do.

• 21:39Speaker 00

  And then you have this portfolio of products who are actually answering both of those questions for the hiring manager, even before they talk to you. So you're kind of shortcutting the process by showing them how you think and how you like to spend time and what your interests are or hobbies are. And then all you have to do is really nail that phone interview. Uh, and you know, as long as you're, you know, like kind of match the culture of the company, I think you've actually shortcutted part one and part two, which is what most interview processes are designed to do, which is why they're like this sort of, you know, you have to go talk to like three different people to see, can you do marketing? Can you do engineering? Can you do, you know, like core product management? And so I, that's really my advice is really, you could start with building your skilled stack. And, you know, starting with the foundation up.

• 22:24Speaker 00

  Let your curiosity drive you and then turn that into a portfolio that you can use as an applicant to stand out.

• 22:31Lenny Rachitsky?

  So what I love about this is basically the, I wouldn't say the hack to get hired as an AIPM, but just like the way you will come across as clearly this person is worth paying attention to is you've actually built things with AI, like actual products, especially now that it's much easier to do as a, you know, you can use tools like the ones you mentioned, Cursor, V0, Replit. You can storyboard out your ideas using the stuff you mentioned, Midjourney and Dolly and things like that. So I love that. It's super tactical. So it's almost like if you're applying for an AIPM role and you don't have products that you have built and ideally like put out into the world, you're not going to have a good time.

• 23:11Speaker 00

  I actually think it's probably easier now to break into AI product management than it was before. So let me kind of hit on that point a little bit more, which is before you actually probably needed to have more of a foundation and background in machine learning to get a shot at one of these companies, building AI products. They required a depth of knowledge in machine learning and, you know, types of models. And you were probably more deeply involved in like, what should this, the training data look like? And the split of the data and how do I launch this thing and all of this infrastructure? But really now, an AI product manager is someone who's building experiences around or for other AI product people.

• 23:52Speaker 00

  And so I'll, I'll kind of, you know, an example there would be, there are these incredible videos that are being put out right now on YouTube on how to build an app in like an hour. And, uh, and, and, you know, I credit Greg Isenberg. He's really kind of like pioneered some of this format of, you know, he'll, he'll show up and just like, here's how I built a product within like 45 minutes and kind of how you use the same tools we just described. And I kind of have this like tongue in cheek example a little bit too, that's, that's pretty relevant, which was, I was trying to describe Replit to someone, to, to a friend of mine, who actually, you know, was basically saying, oh, like, I don't really have time to learn another tool right now, there's, it feels like there's so much in the space. And I think there's really nothing better than just showing someone what's possible.

• 24:37Speaker 00

  So I opened up my phone and Replit, you can just go to as a URL on your, on your phone. And what you can do is type in a prompt to their Replit agent and it will literally build a website for you and host it within a matter of seconds. And what's really funny is I just kind of built this like example of like, build me a signup page for this newsletter. And it did actually a pretty reasonable job on FirstPass, but there's things you want to do to keep iterating on it. So they kind of prompted again, oh, make it look a little bit nicer, use these colors. And within five minutes, I had a working prototype for a signup page that I built on my phone. That would not have been possible even a year ago. And I think the way that the technology is trending is things will keep getting easier.

• 25:20Speaker 00

  And as a product manager, your curiosity is going to keep pushing you forward so that you can be the person out there saying, hey, did you see this cool thing that I tried, you know, that I, that I just pulled up? And, you know, you're really the one that's almost the expert on, uh, what's the cool new thing that you can go and apply to your company? So I think that's really part of the role too, is like being interested, genuinely curious, curious of the space too.

• 25:41Lenny Rachitsky?

  I'm really happy you shared that. And that's, reminds me, I'm just going to go on a tangent here, I want to get your take on this. I had this kind of hot take a month ago or so, that there's this sense that as AI tooling emerged, that product managers are screwed. Why do you need product managers when you could just build things, engineers could use all these tools, designers, like what's the point of a PM in a world where AI can just build things for you? And I've realized it's exactly the opposite, that you may not need any other function if you have a PM, because if you think about it, what are these AI tools amazing at? They're amazing at building things, you tell them what to build, they build them. The hardest part becomes knowing what to build, finding opportunities, problems people

• 26:26Lenny Rachitsky?

  need solved, and then articulating it very clearly to an AI tool what to build, and then having the taste and sense of what is good and great and what will work in the market. And that's like exactly the job of a product manager. So I'm curious to hear your take if you agree with that. Basically, that PMs are the best positioned function to thrive in this world.

• 26:47Speaker 00

  Yeah, I totally believe that. I think that there's a sort of like feeling that executives might have or like VPs at companies might have of like, we need to get into AI. But the challenge is that, you know, there's this inclination towards, you know, doing the same thing that's working so far. And so I think the role of an AI PM in this type of organization is really to be the representative of how can we use these tools to their highest leverage. And so if you kind of combine the earlier notes of like, you know, you know, what this technology is capable of, you know, the customer problems deeply, you're the representative of the customer at the company, you're really in the best position to get the point across of what should go and get built. And I think that's, that's a really

• 27:31Speaker 00

  powerful, you know, position to be in at a company. And then I'll kind of actually build on like, one of the core product skillsets that, you know, people, you mentioned on your podcast too, which is influence. And what this, these tools really allow you to do is like up level, like max out that influence. Meaning you can now communicate ideas, kind of coming back to the prototype note to design, you can communicate ideas engineering, and you can communicate ideas to the higher ups at the company around what should go and get built. So I think, you know, when you can, when you're able to translate the idea to the person that you're trying to communicate it to, these tools are really incredible at that. And I think it allows an AI product manager to be super high leverage.

• 28:12Speaker 00

  So to me, it's like, I totally agree, like being an AI product manager feels like the highest leverage position you could be in at the company right now, especially in the age of AI.

• 28:23Lenny Rachitsky?

  Awesome. Okay, I'm glad we agree there. And what you just mentioned, we were talking about Mahika before we started recording, and one of her superpowers and welding to her episode is that she is designer engineer PM. She can just do a lot of all of it. And that partly has been why she was has been so successful at Pigma and influencing leadership to build these products that they were like, I don't know if we need a slides product. And so now everyone can be a Mahika, basically, that you can build and design as a PM. So anyway, I think we've gone down that road far enough. I want to shift a little bit to talking about how to thrive as an AI PM. Say, you got into this role, you're building with AI tools, or you're building platforms for folks

• 29:07Lenny Rachitsky?

  to build on. Let me ask kind of this, let me try it this way. What have you seen separates the typical AI product manager from say, the top 5% AI product managers?

• 29:20Speaker 00

  We kind of talked about like, what are AI product managers? You know, how do you build AI powered products around what the fundamental technology is? I think there was this really interesting moment where, you know, about two years ago, actually, almost roughly to this time, ChatGPT launches. And I think everyone who kind of tried it out, you know, was was pretty impressed by a couple of things. There was the interface, super easy to use, it felt really intuitive. The model was pretty capable. It felt almost like human like, of course, that was actually an earlier model than what's even available today. And when you look back on it, it's almost like looking at like the old iPhone or something like, you kind of have to like have this moment of, wow, that was really impressive at the time. But now if you try to use it, you're like, this thing sucks. You know, like, it's like, it doesn't even do half the stuff I

• 30:05Speaker 00

  could, you get kind of conditioned to, you know, the technology continuing to get better. But when that moment happened, and it did kind of feel like this iPhone moment around AI products, it was really interesting to see what happened next. And what I mean by that is, you know, we said in a, in sort of in the landscape, at a place where we get to see where a lot of other companies are building. So we have, you know, customers that are super well known, household brands, Spotify, and Instacart, and these sorts of companies that people love and use every single day. And what ended up happening was, you know, we talked to a lot of folks of like, well, what are you, what are you doing around, you know, building around this technology?

• 30:48Speaker 00

  This really game changing sort of shift in AI. And the first thing that everyone seemed to build was actually another chat GPT, but on top of their own data. And for some reason, every everyone gravitate towards this particular use cases. All the AI product managers I knew were like, oh, we're building like an internal chatbot on top of our knowledge base, and it's going to be able to answer questions and it's going to be great. And when you kind of look at like the the products that were built, like how much usage do they really have is is pretty, I think, like, not very well understood. Like, was that the right thing to do? So coming back to your earlier question, like, how do you how do you kind of go and

• 31:29Speaker 00

  thrive as a, you know, be of top 5% AIPM versus, you know, maybe an AIPM that isn't as stellar? I actually think it's kind of coming back to that to that earlier point of don't do what everyone else is doing. Just because it feels intuitive to go and like replicate this interface that feels really great and feels, you know, everyone's bought in because they're familiar with it. Like, you really have to think, is this the thing our business needs right now? Is this the problem that we need to go and solve? And I think if you look deeper at that, you'll actually find that the interface for AI might look really different. It won't necessarily look like a chatbot. It might look like you're trying to optimize or speed up a part of the process that humans

• 32:13Speaker 00

  have to do today, that you can make their life easier. And for us, that was data analysis. We have to look at a lot of data to make decisions within our own company. And so we decided to try to automate that. There is there is sort of, you know, we did also ship a small chatbot just to understand how the tech work. But on top of that, our interface around AI looks so, so different. And I think that a lot of the cutting edge sort of experiences around AI kind of look like that, too. They don't really always resemble chatbots. And and I think that that's really the question you have to ask yourself is, what's the right interface when I'm designing a product like this?

• 32:47Lenny Rachitsky?

  So what I'm hearing is if your team is building something that's very similar to some other to a foundational models product, for example, probably a red flag, probably not going to be a huge opportunity. So optimize for things that feel different and new. Anything else you want to add there because I have a question about that?

• 33:04Speaker 00

  Yeah, I think there's, there's like, so that's, that's almost like a point of like, what do people do for the last two years? And now there's this moment of this actually kind of happening again. And this moment is sort of happening around the term of like AI agents. And I think again, like, you know, I think if you really look at it, like, I get, I actually bring up like Yuri's point again, because I was listening to that episode. I thought that was so insightful of like, he gets so many emails every single day of like, we're AI for this, we're building an AI agent for that. But again, you're sort of trying to fit this technology to solve a problem that, you know, you're not really describing the problem, you're describing the solution, an AI agent to do something.

• 33:45Speaker 00

  So if you look at it, you know, does it really, I'd really ask yourself, does it make sense to build an AI agent within our company? Or is it just better to allow the foundation model companies to build this agentic layer within their technology? And then your job is to make that experience so amazingly seamless in your existing product that it doesn't even feel like AI in the first place. And I think that's really powerful. That's the area where product managers can truly innovate. Because let's be honest, you're probably not going to have those, these cutting edge researchers that can go and design a model from the ground up, or maybe design some new technique to build a next agent, you know, framework. But what you can do is take that technology and find a

• 34:29Speaker 00

  way to apply it in your organization. And that's where I think the role of the AIPM really stands out.

• 34:35Lenny Rachitsky?

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• 35:16Lenny Rachitsky?

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• 35:43Lenny Rachitsky?

  I imagine a lot of product leaders are hearing this and be like, thank God, I need everyone on my team to hear this because I am guessing every PM and every company is like wants, is like looking and proposing all these ideas, all these AI-based ideas, just because it's like, oh, we gotta do AI. Here's an idea, here's an idea. And there's all these people chasing AI products. And so I think this advice is really important is, and this has come out a number of times, people just try to keep reminding folks, focus on the problem you're solving and AI is a tool to solve it, not AI for blank, just because. How have you found ways to find really interesting, actually good ideas for how to leverage AI within your company or companies you've seen as like hackathons? Is it like, here's we have our goals and just like make sure there's AI parts

• 36:26Lenny Rachitsky?

  to a solution? Is there anything practically that you find helpful in finding good ideas that are AI oriented?

• 36:34Speaker 00

  There's sort of like three things you could do in your company that I think will really, you know, if you try to implement this tomorrow, you'd probably see, start seeing those ideas coming back. So the first one is, you actually brought up an earlier point of,

• 36:51Speaker 00

  how do I measure, you know, what, what, what should I be measuring here? And I think that PMs kind of gravitate towards metrics. And I actually think that, you know, every AI PM actually needs a metric. And every PM within a business is tasked with moving some business metric, but there actually isn't one for building prototypes with AI. Which is really interesting. I've like talked to so many companies and I'm like, how do you measure what the impact is of AI within your business? They're like, oh, well, we're not expecting it to like move a business metric, it's not moving revenue. So then how do you really measure if what you're doing is working? And I think that's where you kind of need a metric of like, how many shots are you taking in the first place? And that kind of ties into like the next point, which is, I think hackathons are great. I think that getting people to be hands-on in the first place,

• 37:37Speaker 00

  it really removes that feeling that this this technology is not approachable. So the goal is really to get everyone in the organization to try to use this thing. And I think that's really actually a great position for an AIPM to be in as well. So oftentimes, you know, I think I think I think there's like this aversion sometimes to hackathons because like taking away, taking away from company time. But what you can do is try to come with some ideas of problems to be solved and then see like, how can I use AI to actually solve those problems? What you're going to come out with is maybe a list of 10 problems and nine of them, you try to apply AI towards and it doesn't work. It's like this thing doesn't work as well as I thought it would, or it's like, you know, you're

• 38:17Speaker 00

  trying to get a very specific answer, but it doesn't actually lead to, you know, like AI doesn't actually do a good job of that. I actually have an example here of, we actually did our own hackathon a couple of weeks ago. And the engineering team had all these ideas and one of them was this Slack bot that actually alerted a person that was on call for a problem. So we thought it was going to be so simple, like if someone posted like a support channel, hey, I'm having a problem with this thing, the Slack bot would take that question and actually ping the right person. We thought, oh, this is going to be great. This is a perfect use case for AI and we'll kind of give access to this table and we'll look at problems, classify them, and then ping the right person. It turns out, uh, that's actually a really hard problem to do because there's so much context that is

• 39:00Speaker 00

  missing in, you know, well, this this person was working on this problem two weeks ago, but now they're working on this other project and some other team took over. And I think the challenge there is really like identifying the right problems to solve in the first place. And a good intuition to build around that is through hackathons, through coming with problems and then seeing where the ideas actually stick versus where they actually, you know, aren't, aren't super great. And then I think the last kind of point here is Really obsessing about the details of the user experience in the first place. And you're looking for problems to go and be solved with AI.

• 39:40Speaker 00

  But I think part of that is really looking at like, what are successful AI products today? And you can probably try a few, name a few, but a good example of that might be, and really, if I kind of zoom out, like, the goal is really to find experiences where AI is actually magical. And what do they get right? So like, an example of that might be like, there's this like fun, like funny anecdote of what a lot of people are trying to do with AI is like automate the job away entirely. And there's, there's this story of, you know, Betty Crocker, like actually, you know, launching this, this cake mix,

• 40:19Speaker 00

  where all you have to do is like mix water and they, all you have to do is mix water and you could, you know, kind of bake a cake with just like one ingredient. All you need was this cake mix. And it turns out that actually like tank their sales. So all they have to do is, you know, basically change the instructions so that all you have to do is add eggs. And that one thing kind of created this effect where their scale, their sales skyrocketed because they realized that the customer actually wants to have a little bit of control over the experience. And you can kind of see that even now, if you've like taken, you know, if you've been, if you've been able to like take a Waymo or a self-driving car, like the car is fully self-driving, but you can still control the air conditioning, you can still control the music.

• 40:58Speaker 00

  And so you want to kind of leave some knobs and levers for your customer to feel like they're still in control of the experience. And that's kind of like the IKEA effect applied to AI, like people feel more empowered when they can, when they actually have an impact on the end experience versus everything being taken care of them. So that's just like one insight we realized from looking at successful AI products versus ones that try to automate everything away. And I think if you're like, looking at the space, you're going to find so many more examples like that.

• 41:25Lenny Rachitsky?

  That's such an important point, that even if you can build a product that is fully automated, you may not want to. And that Betty Crocker example is really interesting. It reminds me of like Blue Apron and all these food, food making. I have, I have a friend who's like, who told me that he cooks, he's cooking a lot these days and just like finding all this time to cook. And then it turns out he's using Blue Apron. And it, it feels to you like you're cooking and you can tell people, hey, I'm cooking a lot, but, but it's not, you know, it's, it's not quite the same.

• 41:53Speaker 00

  Yeah, but actually, if you remind, I could like probe on that like that's a really interesting point with like Blue Apron because like if you look at that product, what's the problem that they're trying to solve? Is it, are they trying to get people to be fed or like, you know, eat food? I don't think so, actually. Like, I think if you're really trying to solve that particular problem, you probably built something closer like DoorDash, which is just you push a button and food shows up. And Blue Apron, on the other hand, is trying to get people to feel like they're getting closer to cooking or feeling closer to the experience of making something. And I think that's, that's sort of what, you know, really amazing AI products do as well. They're making your experience or the, the product, you know, AI makes your product easier

• 42:36Speaker 00

  to use and it brings the barrier to creation down. And I think that's really what it's good at, not necessarily just trying to automate the, the problem away.

• 42:45Lenny Rachitsky?

  Such an important point. Again, coming back to your main point here is just focus on the problem you're solving and AI could help you solve it, may, may not. Okay. We went on tangent from advice you were sharing on what separates typical AIPMs from five percent, top five percent PMs. And what else you, what else you got? What else you got on that list?

• 43:08Speaker 00

  Oh, actually, I'll kind of seal this one a little bit from our friend Kevin Yen, who I think he had this advice when he was on, on your pod, which really resonated with me actually at a personal level, which is you have to be able to walk and chew gum. So as an AIPM, your, your job is, is not to go and ship AI products, it's to go solve customers' problems. I think we've come back to that a little bit. But you're constantly going to be, you know, pushed by your team and your company to go and solve a business metric, you know, move a business metric in some way. The goal though, is to make space for the other things we were kind of talking about, which is prototyping, you trying the tools firsthand yourself.

• 43:52Speaker 00

  Making space for your team to, you know, have hackathons and try the tools themselves as well. Breaking down product experiences that are really great. So as an example, like we did a teardown of the Notebook LM product just yesterday as part of our company. So we like livestreamed it. And we're going to do this, you know, probably every week or two, where we'll take a cutting edge AI product and have a webinar around it and try to break down how it works. And the goals there are, you know, to really understand the space better ourselves. But by the way, none of those three things are going to move your KPI or business metric, right? So I think you come back to that point of you have to be able to walk and chew gum. You have to continuously

• 44:34Speaker 00

  deliver customer value while also creating space to iterate and fail and find that the experiment that you tried to launch and people really excited about may not work, but you know, in the process you learn something. And that's, I think, like a really powerful takeaway, which is to really stand out as an AIPM, you have to accept this technology is changing really fast. It's, you know, you might think it's going to do something great, or maybe you have a bad product experience. It's like, uh, I think you had a point earlier as well, which was like, you know, to, to be a really great chef, you have to, you know, you have to have a lot, you know, occasionally you're going to have a bad meal. I think that's going to have this, that's going to be the same thing here with your AI product diet. You're going to try some bad experiences. You're going to have some, some failures, but the goal is to keep iterating.

• 45:18Speaker 00

  And that's how AI gets better. I think that's how companies can deploy AI better too. So don't give up on the North Star. Just find ways to make space to have AI sort of propagate within your organization. And that's, I think, really stellar AIPMs do that.

• 45:34Lenny Rachitsky?

  I feel like this metaphor of walking and chewing gum doesn't communicate the difficulty of what you're, of Kevin's, uh, now that I think about it, of what he's trying to describe. Doesn't feel hard to walk and chew gum. I wonder what a better metaphor would be.

• 45:47Speaker 00

  Yeah, well, I think.

• 45:49Lenny Rachitsky?

  And.

• 45:51Speaker 00

  Oh, that's a good point.

• 45:52Lenny Rachitsky?

  Maybe gum bubbles and dance.

• 45:53Speaker 00

  Yeah. Yeah. I don't know why that is the, like, that's the expression, but it's always meant to like describe something hard that you realize like, you can't do more than one thing.

• 46:03Lenny Rachitsky?

  Anyway, we don't need to solve it right now.

• 46:08Lenny Rachitsky?

  Okay, so I want to talk about being an IC, being successful as an IC. Before we get to that, is there anything else along these lines that you think would be really valuable to share or get into about how to be successful as an AIPM specifically that we haven't touched on? I know we've talked about a lot of things now.

• 46:24Speaker 00

  Your organization might want to do something and you're trying to get them to do something else. And that's really the challenge in this type of role is there is so much buzz, there is so much excitement around AI that knowing what the right thing to build is really what this job needs to kind of convey. So I think when you take all of that signal and try and put it together and solve that customer problem, that's really what being a successful AIPM is at the end of the day. So that's really, I think that's the hard part about the job, but also maybe the most important impactful part of it.

• 46:56Lenny Rachitsky?

  I love that. Okay, so let's put AI to the side for a moment, but not totally off to the side. I imagine we're going to touch on it in this next area. And this next area is talking about how to be a really successful IC. You've very consciously decided to stay an individual contributor and not move up the ladder of product management and director and VP and all these things. And there's a specific skill set that it takes to be successful and to thrive as an ICPM. Most people either can't move up the chain and become really successful ICs long term, or they don't want to and they don't even think it's an option. So here's my question here. What are some of the biggest habits, mindsets,

• 47:38Lenny Rachitsky?

  lessons you've learned about how to be really successful as an IC long term?

• 47:44Speaker 00

  When I think about my own like career journey here, it's so much of that comes down to like what drives you personally. And I'm just obsessed with solving that, you know, customers' problems. And so to do that, you know, that might mean I have to spend a lot more time trying to get into the weeds and get into the details. So I think that there's kind of really three areas, you know, kind of like three things that come back to me of like what the hard part about being an ICPM is and how you can kind of break through that. So I first want to like set the tone a little bit, which is Being a CPM is really hard. It's, it's, uh, you know, I made a point earlier of like, it's become easier to break into product management to some degree.

• 48:28Speaker 00

  If you can use these tools and now you have all these tools at your disposal to go build the next prototype. But I think the bar just got higher for product managers within a company and what the impact needs to be. And by the way, that's always going to compete with your, you know, being able to like jump on a quick call last minute, or try to unblock someone, or, you know, have some like internal stakeholder discussion to figure out what to go do next. And so I think the challenge is, uh, you know, you have a really hard job. There's constant signal, things are constantly changing. How do you really power through that? So I think that there's really three things I think about there, which are, uh, energy, waiting versus wandering, and then amplifying the signal to make a decision.

• 49:12Lenny Rachitsky?

  Ooh.

• 49:12Speaker 00

  So, yeah, so, so maybe to even just kick off like, energy can, I, I really think about this like, this was maybe, you know, the, one of the most important things I realized, like working from our, with our CEO, a little bit over a year ago, which was energy can count a lot when you're not sure which direction to go. If you kind of show up to a meeting and you're, you're bringing a little bit more of that energy, you'll find that like a lot of friction tends to go away versus if you show up and you're a little bit, you know, a little bit down or a little bit, you know, not as enthused of, about an idea. Like people pick up on that and we're still dealing with people today. And I think that, you know, even if you just change that mindset a little bit of bringing a little bit of that extra energy,

• 49:56Speaker 00

  you'll find that that can actually break down barriers and people like that. The conversation feels like it's like flowing, feels like a dinner table conversation versus a hard conversation, even if it might be something about something tough. So I think to me, there's this concept of like, when you're, you know, you might still be, you know, faced with this challenge of. I'm not sure what the right decision is and I'm, you know, I'm struggling to really kind of, you know, do this analysis and really get something going. And I think that, I think accepting that that happens to everyone, it sort of feels like a product block as opposed to like a writer's block, if that makes sense. We're like, you know, as a, as a writer, you might be trying to get to that like next paragraph and,

• 50:38Speaker 00

  and as a product manager, you're really trying to get to that next idea or that next milestone. So I can give you an example, like an example there as well, which is,

• 50:47Lenny Rachitsky?

  Yeah.

• 50:48Speaker 00

  Um, you know, we had this moment a little over a year ago where we were not sure which direction to take a product feature. And we were, we were kind of faced with this decision that felt pretty existential, which is like, how much do we want to, you know, invest in L L M's and like the sort of new wave of large language model tech versus our, what our existing customer base was. And it wasn't immediately clear what the decision should be. And so the energy I kind of just brought was, you know, I'm just going to be our like outbound salesperson and just start writing LinkedIn messages to people that have the title AI in their LinkedIn profile. So I just went on it and LinkedIn and literally just started like finding ways to get them on a phone call. So I'd like,

• 51:29Speaker 00

  you know, write some copy and iterate on it. And I had to like sit with our sales team to like, understand, how do you, how do you do this? Like I max out my like five LinkedIn messages a day. Like, what are you trying to do here? And I think what, what that really accomplished was sort of two things. One, you know, I did kind of learn a little bit of like what goes into this role in terms of, you know, how to message our problem and product more, you know, in a way that actually got people engaged. But two, it also demonstrated to the team that I was like willing to get into the details with them. I was willing to spend time, you know, even when I was like trying to push on our day job of, you know, building a product and keeping it growing. And I think that counts for a lot when the team is already feeling, you know,

• 52:12Speaker 00

  like they're not sure which direction to take something. And so just being that like player coach and just having that mentality of showing up. Bringing the energy can move the bar so much higher for the whole team to operate. So that's kind of the example I give of like, you know, you're kind of like being LeBron James. Like you're telling, you're coaching people, you're kind of like drawing up the play, but you're also just trying to be, you know, like as involved in, uh, you know, all of the tough stuff as well. And, and I see that happen. I think that that really comes from leadership from our CEO as well. Like he'll be tired, I can tell, but it's just when he shows up to a meeting, like he just doesn't show. You just have to kind of bring that energy.

• 52:48Lenny Rachitsky?

  So what I'm hearing is there's kind of two things you're sharing here, which is awesome. So one is there's like actual energy in a meeting of staying positive and energetic. And then two is actually just doing the thing to figure, help solve the problem. Like getting into sales, like becoming the salesperson potentially, reaching out, doing customer development in your own, kind of going rogue a little bit. In that first bucket, what does it look like to bring the energy? Is it just like volume? Is it just like being bright?

• 53:16Speaker 00

  I actually think this depends a lot on the person. Like I think that's actually like a personal, personal thing. So, uh, what I mean by that is like, you know, yeah, I'm, I, for me, that might mean like, I'm showing up, I'm super enthused, I'm really like, you know, I'm bringing my version of energy. But to other people, that might mean, you know, smaller things like just asking how someone is doing, trying to kind of keep, keep the tone of a meeting more like positive, I think to some degree. So to different people that might resemble different things. But I, I actually think this comes back a little bit to an earlier point of, humans are really good at picking up on these like subtle signals with other people. And you kind of want to just be putting out this like subtle like energy where people feel like you are engaged.

• 54:01Speaker 00

  You're in it, you know, a hundred percent. So I think that's part of it. I think it's like the, the ideas, you know, for other people to feel like, you know, uh, you, you're bringing the energy level of the room up versus bringing it down.

• 54:13Lenny Rachitsky?

  I have a, I had a PM I was working with at one point that is, they're pitting me that every meeting you walk into, he's just like, solve some problems. Woo, let's do this. Like he comes in just positive and, and energized. And that just changes the whole feeling.

• 54:28Speaker 00

  I remember this like early Lyft anecdote. I have some friends from like the earlier days at Lyft. And, uh, I think this may have been in the self-driving car division, but like they would literally, I'm not indicating this was like their ritual, uh, where they would actually end the meetings with like the phrase. Make it happen. And I thought that was so powerful because it's so simple, but it's like, all right, we're gonna do this. It was like one of their values and we're gonna, you know, we walk away from a decision and we're gonna make it happen. And I think even just something as small as that could be like a contribution back to the culture for your team. And maybe there's like a point there of like building culture too. Like you get to determine the culture of the people around you. You get to build a culture of the team and that can

• 55:11Speaker 00

  really work its way out. Like there's top-down culture, there's values, but you get to kind of drive what, you know, people in the room are feeling. And, and I think that's really, really powerful, especially in the role of a PM where everyone kind of looks to the PM for making a decision or solving a problem, even if it's a tough one to make. But, you know, you get to kind of drive the energy that you're bringing to that. So.

• 55:32Lenny Rachitsky?

  Absolutely. So, okay, so your first piece of advice for doing well and doing and thriving as an ICPM is essentially that energy can count for a lot. That if things aren't actually going smoothly, you can pull people through that by bringing energy, which is both like meetings and being positive and bringing, you know, energizing folks in discussions and also just like doing the work yourself to like get to the core problem and helping people see that you're actually putting in your own effort and time to solve the problem.

• 56:07Speaker 00

  Yeah. And I'll like, even just to riff on that like second point, like you're, you know, I think that there's a, there's a, there's this component of like when you are doing the thing with someone and you pair with them on a problem, you have a lot more empathy for what they do as well, because they'll describe to you like what's challenging or what's hard about that job. And I think that there's this like feeling that at least that, you know, teams I've been a part of where like there, there is no job that isn't important, right? And so you kind of, you know, as a PM, you're, I think if you're like spending that time with with someone like that, that also that means that you're learning something from them and you're learning, you're learning,

• 56:50Speaker 00

  you know, having empathy for what they might be doing day in and day out, but you're also pushing back and contributing and trying to make, you know, the the whole team kind of push along better as well.

• 57:00Lenny Rachitsky?

  Awesome. So let's keep talking about other things you found helpful and helping you be really successful in ICPM. You mentioned this term wandering versus waiting. Maybe we go in that direction or if there's anything else.

• 57:11Speaker 00

  I actually, I think this one is so, so powerful, which is like the concept of waiting versus wandering. And like, to me, this is this is super relatable again from the the standpoint of trying to figure out what to go do next. So we kind of talked about like energy, bringing energy, but that still doesn't actually solve the problem of where should we go. That's just the the latent like energy you're going to bring to solving a problem. But like, at the end of the day, you as the product manager have to figure out where do things go? What's the problem to be solved? And how do we solve it really for a customer? And I like, there's this like thought exercise, this like zoom out of it, you know, it kind of feels a little bit like, you know, if you're, you're all

• 57:56Speaker 00

  kind of like at a camp where you're trying to figure out, okay, where do we go send the scouts to go like, take the rest of the camp and like move things along? And like, there's definitely this, this, you know, inclination towards executives and companies, like especially broader companies to sort of do what's been working so far. And that can often mean the like, let's just wait and see. And I think that's super interesting from the concept of AI, right? There was this feeling of should we wait and see where things go? Or do we go and try and figure out what direction to move our our team? And most companies will maybe wait, you know, might lean towards waiting to see how things pan out. And we're seeing that even with AI. They're like, oh, we'll just wait

• 58:41Speaker 00

  for the next OpenAI model to come. And then we'll go like build a product around that. Like this one, I keep hearing that there's like this rumor of like some other model or we're gonna wait and see like, but I think at the end of the day, there's times when waiting might make sense to see what technologies get built initially. But then there's also this component of wandering and trying to figure out where should they, where should we go? Where should we take the team? And to me, I actually think the role of a PM is to be that wanderer. And I have this like story of like, we, you know, it was this moment in the, in the company's history where I, I was like, I was like grabbing a beer with one of my, our engineering managers.

• 59:22Speaker 00

  And he was like, look, man, like, I, I kind of show up and I'm like, I maybe I wasn't bringing a hundred percent of my energy, you know, at this end of the workday. And I was like, oh, like, just, I'm just not sure where to take things and like what we're doing right now. And it was so interesting to hear his perspective of, in, in his world, everything was actually going pretty reasonably well. It was like, we kind of knew, like, he had his roadmap, he knew what to go build, he had the next feature, you know, the next like three weeks of sprints planned out or something like this. And he was, he was like, oh, the team's actually doing really great, the morale is really high. And yet on the product side, we were, we were like confused, we were not, we were really unsure about what to do. And I think it's, it can be hard to be that wanderer.

• 1:00:04Speaker 00

  It felt, it felt really tough to be like out there in the unknown, just trying to like, find any sort of signal that we could bring back and say, okay, here's where we need to go and take, you know, the, the next features and next company, next part of the company. And that, that part was, was really tough, but I actually think that's where, you know, I kind of tiered to an earlier, kind of like part of the discussion where, where an AI PM can really stand out is in being a natural wanderer and naturally feeling a little bit like their role is to push the boundaries of what the company thinks is even possible. And to do that, you sometimes have to be in this space that feels really squishy.

• 1:00:46Speaker 00

  And I remember like talking to our founders of, I'm not sure what we should be going and doing next. And it was actually really reassuring to hear from them, like they, I remember having this conversation and, and Aparna, our, our chief product officer was like, that's what building zero to one really feels like. It kind of feels like you're not sure what the right decision is, or where the right decision, you know, where the right direction to go is. But at the same time, you kind of know when you get there. And so you just have to keep wandering and iterating until you feel that drag of like the product pulling you in that direction. And so I think there's just this like feeling comfortable with not being sure what the right decision is and just wandering and trying to figure things out.

• 1:01:30Speaker 00

  Uh, while the rest of the camp might have to wait and see what that next move is. So that to me, I thought was like this, this really visceral feeling of, of, uh, you know, like where, where do we go? Where do you go from here?

• 1:01:42Lenny Rachitsky?

  So my takeaway here is if you're feeling like you have no idea where your product is gonna go, maybe be okay with that. And in your experience, you eventually find, find the path as you wander. And with AI tools, making it much easier to prototype and design and ideate. Theory makes that a little less stressful because you can actually just try stuff.

• 1:02:04Speaker 00

  Yeah, and I think that's like the amplifying the signal with like through the noise with AI. Like the signal can be super sparse, you get back at times too. And then what you can do is like, you know, there's really powerful tools like we use Gong, uh, for instance, to like, I understand like what are maybe prospects or, or really engineers to me, it's like potential customers. What are they talking about? What is their pain point? And I can't go be in like a hundred meetings, right? Like every single week, but what I can do is take those transcripts. And we literally did this, we fed them into some of these large language models that have super long context windows now. And what you can do is actually pull out what's some of those common problems that come up. You know, ask, having a conversation around that can be really powerful too. Now you can do it with voice too.

• 1:02:49Speaker 00

  So you can like pull all of that in, maybe you want to turn it into a notebook LM episode. Uh, but what you can do is actually just find ways to find signal through the noise. And that kind of gives you, uh, an ability to almost have like a superpower. Because you can be in so many places at once, uh, and, and you kind of use technology to your advantage to get that signal back. So I would really try to find ways to scale yourself up with AI and come back with that signal.

• 1:03:18Lenny Rachitsky?

  Anything else along these lines of things that have helped you be really successful? As we ramp up and approach our very exciting lightning round?

• 1:03:28Speaker 00

  Product management can kind of feel pretty serious. You're like, there are some big decisions that sort of weigh on your shoulder. But I honestly, I remember having this discussion with one of our board members, actually. And he's a serial entrepreneur. He's taken companies public. And I was like, what advice do you have for me as like a PM, you know, early in this company? And I was so surprised by the feedback he had, which was just have fun. And I think if you let that drive you and you keep learning and you're kind of keeping this curiosity and building products for customers that you care about, it's just going to help you go so much further. And I just think it's just more fun to have, you know, to be the, to be like high energy. It's just more fun to, you know, like really care about the thing that you're working on.

• 1:04:13Speaker 00

  And I think if you're constantly learning and having fun, you're going to iterate so much faster too. So that's really my, my note is like, just, just have fun along the way. It really is about that journey. And yeah, sometimes you're wondering, but have fun with that too.

• 1:04:25Lenny Rachitsky?

  I love that so much and it resonates so deeply with me. As I've shared a couple of times on this podcast, the folks that listen probably have heard this, but I have this little post-it that I put right in front of me as I do podcasts that just says, have fun.

• 1:04:38Speaker 00

  Yeah.

• 1:04:39Lenny Rachitsky?

  And it's like the lamest little post-it.

• 1:04:42Speaker 00

  Is it like really torn up at this point from, or is it like?

• 1:04:45Lenny Rachitsky?

  It's like, you know, I just bent a post-it in half and just wrote have fun on the edge. And then it just sits here. I don't know. Post-its are meant to like, you know, stick to stuff, but this is how I decided to use it. This also came up recently in this episode that I think is going to come out right before this, around public speaking. This course that I took called Ultra Speaking, the biggest piece of advice they have is speaking should be fun. So just think about how do you have fun while you're doing this, even though it feels really scary? And that works really well. So I really love that.

• 1:05:14Speaker 00

  It's just more fun than not having fun.

• 1:05:17Lenny Rachitsky?

  That's like a really silly line.

• 1:05:19Speaker 00

  Yeah.

• 1:05:19Lenny Rachitsky?

  It is. And, and even if it's like very stressful and scary, just reframing it to how do I have fun? Most cases, the end of the world, the end of my career, the end of something really serious, most of the time you can have fun.

• 1:05:34Speaker 00

  Totally, yeah.

• 1:05:35Lenny Rachitsky?

  Awesome. Well, Amon, with that, we reached our very exciting lightning round. Are you ready?

• 1:05:42Speaker 00

  Ding ding ding.

• 1:05:43Lenny Rachitsky?

  Ding ding ding. There's a ding that comes that we overlay.

• 1:05:46Speaker 00

  I know.

• 1:05:46Lenny Rachitsky?

  So I always have to resist not saying ding ding ding.

• 1:05:49Speaker 00

  I know, yeah. Yep, I'm ready. Let's do it.

• 1:05:53Lenny Rachitsky?

  First question, what are two or three books you've recommended most to other people?

• 1:05:56Speaker 00

  I really loved Short History of Millie Everything by Bill Bryson. I don't know if that's a, you know, that book to me is so, is so interesting because I'm a bit of a nerd around like science. I used to read a lot of like fiction growing up too. And I think weirdly enough, Bill kind of tells this like story of the history of science, really, and how we know the things that we know. And he kind of tells it from the perspective of learning about the scientists that discovered these things. So for instance, you learn that like Newton was kind of an asshole to like the coworkers he had or, you know, or like Darwin, was it maybe perceived as like such an amazing scientist at the time? Like, and so a lot of, and a lot of these scientists, like their discoveries don't become famous.

• 1:06:40Speaker 00

  It's almost like being an artist where like you realize the relevance of a scientist's discovery years later at times and people don't get credit for things that they discovered. So to me, it was really interesting to hear, to one, listen, to read more about

• 1:06:56Speaker 00

  the scale of the universe and how long we've been here. And I think, I think it just puts a lot of things into perspective of like our time here, how we spend it. And even the age we're living in now with AI, like it's such a blip in the cosmic scale. And then you also get this, like these really fun anecdotes from scientists along the way. So that one I, I recommend to like almost everyone, uh, cause it's pretty easy read as well. And then I think another one, which is maybe like a little bit more in the like career lens is this book called Designing Your Life, which is written by these, actually, um, you know, one of the founders of IDEO and these, these folks are Stanford professors in the design lab. And what's really powerful about this for me is it's actually pretty practical.

• 1:07:40Speaker 00

  So it comes with exercises that I remember I did myself as well, when I wasn't sure which direction to go in my career, that helped me really figure out, you know, the most powerful exercise and like takeaway from this book for me was basically in like the first or second chapter, I think, you write out one page on the meaning of work to you and like, what does work mean? Is it a way for me to make money? Is it a way for me to feel fulfilled with what I do or how I spend my time? And then you write out one page on the meaning of life. And what's really powerful is it's really, really hard to do those two things. And then you have to find the overlap between the two. And I think that exercise is so clarifying. And I recommend it to anyone when they feel like stuck in their career.

• 1:08:23Speaker 00

  Because it can at least, kind of coming back to like the energy point, can give you like a direction to go, even if you're not sure how to get there just yet. And so I, I, I just, I love both of those books because they're, they're really like shifting in from a perspective standpoint.

• 1:08:36Lenny Rachitsky?

  I love that second book. I read it and it was really meaningful to me, but it's been long ago and I forgot it now. But I remember it was really great. And so I'm glad you brought that up. Next question, do you have a favorite recent movie or TV show you really enjoyed?

• 1:08:49Speaker 00

  I, I don't usually binge watch TV. I gotta be honest, like I, I'm not a binge watcher, but it's been a little rainy in New York lately. So we've had a little more time inside on weekends and I've been obsessed with the Tour de France documentary on Netflix. I don't know if, if you've seen that, I don't even know if it gets like pushed up that highly in the Netflix algos. But I, I think it's super cool. Like one, I love cycling. So for me, it's like, you really realize that competitive level of cycling is just such another level than I even realized or gave credit to. And then two, kind of coming back to like the characters and the story. I think they're all just so interesting to hear, like what motivates them to be at this like extremely high level. It's actually the same producers as Drive to Survive, which I know people really got into as well around like F1.

• 1:09:33Speaker 00

  But yeah, highly recommend it. And it's, it's intense. I'm going to kind of start there. Like I didn't realize what I was going to get to, but it just ramped up in more and more intensity. And yeah, really enjoyed it.

• 1:09:46Lenny Rachitsky?

  Is there a favorite product you've recently discovered that you love? Maybe an AI product, maybe not.

• 1:09:51Speaker 00

  So I think we talked a little bit about like AI products that help you prototype. Replit is incredible. It's so easy to use. You know, V zero and these are all like really like, I think they create really polished products at the end of the day. But the product that really that I've been like using and having a ton of fun with is Webson. I think it creates this like almost playful version of the prototype in the first place you might be trying to build. Or just something so crazy and wacky and zany that you're not even sure it's possible. And it's so hard to describe. I remember even, you know, we, I used to show a presentation from some of the founders of Webson. At, you know, an AI meetup here. And even they, when they were like showing how to use the product, they literally just went on Reddit.

• 1:10:35Speaker 00

  And they were just looking at the, at the Webson subreddit that has like so many posts on it. The presentation was just them like looking at the top like three or four and trying to describe what they saw. So I, I, I thought that was like super, I, I've just been obsessed with it lately, just to like push the boundaries of what's possible. I also do have another product as well. Initially, when I thought about this question, I was like, what's like the product I've been using the most lately? And this is, this one's going to sound kind of, kind of weird. But I'm a little bit old school and I, I actually like, like you, I like to like write notes and like physical notebooks. And so I was, you know, like, I'm always looking for like, oh, what's like a fun, you know, like a really practical notebook to use.

• 1:11:20Speaker 00

  And this was, this is really weird, but I was recently given a notebook from actually like an AI meetup here. And I opened it and it's made from recycled apples. And when you open the notebook, it smells like apples. Which is really interesting because like, I didn't think that that would like impact me as much as it did. But it created this interesting feedback loop where I just really love using the notebook. Because when I open it, I like have this like positive experience immediately, like sensory experience immediately that it's like, oh, it just smells so great. And then you like, want to keep using it and, you know, coming back to it. So I thought that was really interesting to create this like. Feedback loop in my head of like, I, I enjoy like using that notebook now. I'm not sure

• 1:12:04Speaker 00

  what that means if when I run out of papers in this one, if I'm going to buy another, but that was, that was really funny. I didn't expect it like that as much.

• 1:12:10Lenny Rachitsky?

  You're making me hungry. I can almost smell it. What is the brand of this notebook? In case folks want to look it up?

• 1:12:16Speaker 00

  It's called Appheel, A P P E E L.

• 1:12:21Lenny Rachitsky?

  Amazing. Okay. I need it. I need that. Two more questions. Do you have a favorite life motto that you often come back to, find useful in work or in life? I feel like you're gonna have a good one.

• 1:12:32Speaker 00

  There is like specifically one that I ended this essay that I wrote a while back with called, I read a bunch of self-help books you don't have to, and I like share it with my friends. It's literally just called that. That you are not sure what to do when they're in that next phase of their career as well. And the quote is from Steve Jobs,

• 1:12:51Speaker 00

  which is, "Your time is limited, so don't waste it living someone else's life." And I thought that was so powerful because when you think about it, like there's, there's always this, I feel like there's a lot of like career pressure for some people to like, get that next job or start a company or like do something, you know, super crazy. And, and at the same time, I think what's been really powerful for me has been to reassess what my goals are and what, what life I want to live and not feeling the sort of feeling of what other people's projections of that life are. And so that, that quote in particular has always been something I've come back to, which is like, what do you, what sort of life do you want to live?

• 1:13:37Speaker 00

  And thinking about that really deeply and making decisions along the way based on that. So.

• 1:13:41Lenny Rachitsky?

  I truly love that sentiment. And it came up recently in another conversation with Jam Nichols. But let's move on. Actual final question. So as I was researching you, I was Googling your name. And when I Google your name, there's a cricket player very prominently comes up. Curious how much that bothers you, that there's this player that is number one on Google in many ways.

• 1:14:05Speaker 00

  Oh my God.

• 1:14:06Lenny Rachitsky?

  Tell us about how that feels.

• 1:14:07Speaker 00

  This is gonna sound crazy, but I, I was like thinking, I literally, I was thinking about this. Yesterday, it's gonna sound crazy cuz I I was like, oh, like, the immediate thought that came to mind was my parents really didn't optimize my name for SEO. And the only thing I'm gonna do now, when I think about, you know, when I have kids, like, they're gonna have some unique names cuz it gets so much harder. Like, you have to type in like Ahmad, God, San Francisco, or Berkeley, or something to like, get that to pop up. So, yeah.

• 1:14:41Lenny Rachitsky?

  So it does bother you.

• 1:14:41Speaker 00

  It works a little bit.

• 1:14:42Lenny Rachitsky?

  Take away here. Yeah.

• 1:14:43Speaker 00

  Okay. Well, we'll iterate all that for the next.

• 1:14:45Lenny Rachitsky?

  Or it's a, this is a goal. I feel like you have the chance to beat, beat this guy.

• 1:14:49Speaker 00

  Totally, right? Or, you know, maybe another way to look at it is like, if I, if we still keep using search engines, and it's funny cuz my partner works at Google, the future might look like, what if we, you know, what if we're using L L M's more? Kind of gives me a second shot here to like, be part of the training there in a way. So, yeah.

• 1:15:07Lenny Rachitsky?

  Amazing. I love the silver lining there. Amon, this was amazing. I think this is gonna be helpful to so many people trying to get into AI, trying to thrive as an A I P M, or just wanting to stay down the I C track. We went through so many things. I, there's like, my notes were very long and we touched on basically everything. So, thank you so much for being here. Two final questions. Where can folks find you if they want to reach out and maybe follow up on some of this stuff? And how can listeners be useful to you?

• 1:15:35Speaker 00

  LinkedIn's probably the best way. I'm not super active on X, though, you know, might, might spend a little bit more time there with LinkedIn easily. And then to that note, yeah, how can listeners be helpful? I think like, my, my goal was to try to be as helpful for folks that are trying to figure out how to get to this next part of their career, whether it's involving AI, or they want to pivot into it, or they want to thrive as an AI product manager. So, love to hear stories of people that are interested in this, in this part of their career or this career path. And I think like, the thought I'll leave people with is, I'll, I'll respond to anyone that messages me and, and but I, I do have one condition there, which is like, if you're cold, cold emailing, cold messaging, kind of coming back to like, how to stand out. I think there was, you know, this, this note from John Dory spoke at the college I went to.

• 1:16:20Speaker 00

  And he put his email up on the board and his like note was, I'll email anyone who emails me as long as you send me your three, top three favorite books, movies, podcasts, or YouTube, or like videos that impacted you in some way. And I'll do the same for you. And so I actually did that, emailed him and got back his top three as well. So I, I want to kind of carry that forward and, you know, would love to hear from folks. Send me your top three, whatever pieces of content they might be, and I'll do the same for you.

• 1:16:49Lenny Rachitsky?

  That's an amazing collection you're going to build. I'm, I want to see all these things too. I love that idea. It's almost like a mini lightning round. What a clever idea. Uh, Aman, thank you so much for being here.

• 1:17:02Speaker 00

  Thank you so much, Lenny. This has been awesome. Really, really had fun with this one.

• 1:17:05Lenny Rachitsky?

  Same for me. Bye, everyone.

• 1:17:09Lenny Rachitsky?

  Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.