← Lenny's Podcast: Product | Career | Growth
Lenny's Podcast: Product | Career | Growth
Becoming an AI PM | Aman Khan (Arize AI, ex-Spotify, Apple, Cruise)
01:17:34
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- [00:00]
A
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.
- [00:21]
B
For people that want to, say, pivot their career to be an aipm, what helped you move in that direction?
- [00:27]
A
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.
- [00:52]
B
What have you seen separates the typical AI product manager from, say, the top 5%?
- [00:57]
A
Really? The question you have to ask yourself is.
- [01:04]
B
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 AI pm, and what Aman has learned about how to be successful and continue his career as an individual contributor PM long term. When 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. Aman, thank you so much for being here and welcome to the podcast.
- [02:20]
A
Amazing. Thank you so much for having me, Lenny. It is truly an honor to be here.
- [02:24]
B
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 an IC for basically your whole career, very intentionally so. 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?
- [03:28]
A
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 some of our discussion back and forth on this thread and I thought it was like super interesting. It was like this combination of product and AI where it just happens to be like, I think where the space is headed or 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 that I've learned along the way as well.
- [04:00]
B
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- [06:35]
A
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. 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 with the rise of all of these tools that are being built on top of OpenAI's APIs or anthropic APIs, basically any tools on top of the large language model providers. It's actually pretty clunky. 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 on top of and understand is my app doing the thing I expect it to do is really, really early. So that's sort of the space I'm focused on around enabling AI engineers to understand the impact. And if you're an AI PM at another company, one of our customer companies, you understand that when you go to leadership, that 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 ChatGPT. It's the core kind of tech. Or actually another great example would be you had Ryzon and NotebookLM 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, and distributing. I think the third type of PM here is really the one we were talking about a little bit earlier, which is this concept of 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 a little bit what that means as well. I have some ideas and thoughts around that. But really 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 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 companies that are deploying AI. Maybe you're behind one of the cutting edge models that's going to go and be the next notebook lm, or you're building around a transformer of some kind or a GPT model that's doing some part of the work that you would want to do to solve a customer's problem.
- [11:00]
B
Let's actually make it even more real. What are some tools you use in your PM work to be more efficient and productive?
- [11:07]
A
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 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, Vercel, if you're trying to create a landing page. So Vercel now has a sort of starting point called V0, which allows you to type in a prompt and get a really beautiful landing page on top of that. And so it doesn't have to be just a landing page. If you prompt it correctly and iterate with it, you can 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 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 midjourney or even Dall E. 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. 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.
- [12:54]
B
Okay, awesome. I want to come back to kind of where we started here. So you shared three types of AI product managers. 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 the actual 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 say, pivot their career to be an aipm. What helped you move in that direction? Slash, what would you recommend folks try to do and learn to be able to get a job in one of those two buckets?
- [13:54]
A
Now 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, you know, 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 master's 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 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 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. I think the same thing is true for AI product product managers, meaning 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 what would an ideal experience look like that I'm trying to solve, you'll kind of find tools along the way to help unbox that really that problem. So I think if we take an example of that, let's imagine that you're working for a company that might be having customers that have customer support problems or people coming in with complaints. And when you think about the surface area of customer support, it's not that great. You usually have to type in some questions with a chatbot that's routing perhaps incorrectly 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. There 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 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 are starting to emerge and I think a really cutting edge one from the last couple 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 can even try that out in the application yourself. You can open up ChatGPT, and if you're a Plus subscriber, you can try this cutting edge sort of voice chat bot experience. And why is this interesting? Because if you're a consumer and you're, 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 I can take this thing that kind of feels like it's like early, but it 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 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.
- [18:15]
B
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 European build awesome products and they happen to integrate AI, that might be the best solution. Like, if that's your advice, definitely say that.
- [18:42]
A
I think you're hitting on something on a point that's super relevant to today, which is it almost feels really competitive now to be in tech and to be a product manager. And the struggle is really, to your point, what are the skills I should have in the. To, 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 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, okay, what are the things I need to know? And then how can I use that in 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 Andrej Karpathy talking about the foundation of LLMs. It's this great, amazing resource. He put out this video a little while ago and it's about an hour long, but you know, you could put it into Notebook LM and 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. 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 building your own skill 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 almost like a portfolio of products 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 who's the person I want to bring on board. And maybe like to zoom out for a sec, as someone who's been a part of the 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 AI and ML of at least being able to describe what the technology can do, and then you have this portfolio of products, you're 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 and hobbies are. And then all you have to do is really nail that phone interview 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 that's really, my advice is really you could start with building your skilled stack and, you know, starting with the foundation up. Let your curiosity drive you and then turn that into a portfolio that you can use as an applicant to stand out.
- [22:31]
B
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 PM. You can use tools like the ones you mentioned, cursor v0replit. You can storyboard out your ideas using the stuff you mentioned, Mid Journey and Dall E 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 a products that you have built and ideally like put out into the world, you're not going to have a good time.
- [23:12]
A
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. Companies building AI products, they required a depth of knowledge in machine learning and, you know, types of models and you are 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. And so 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 you know, I credit Greg Eisenberg. He's really kind of like pioneered some of this format of, you know, 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 pretty relevant, which was I was trying to describe replit to someone to a friend of mine who actually, you know, was basically saying 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. So I open 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 relet 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 first pass, but there's things you want to do to keep iterating on it. So then it 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. 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 try? You know, that I just pulled up and you know, you're really the one that's almost the expert on what's the cool new thing that you can go and apply at your company. So I think that's really part of the role too is like being interested, genuinely curious. Curious of the space too, too.
- [25:42]
B
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 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 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.
- [26:48]
A
Yeah, I totally believe that. I think that there's a sort of like feeling that executives might have or like VPs and 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 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 a really powerful position to be in at a company. And then I'll kind of actually build on one of the core product skill sets that you mentioned on your podcast too, which is influence. And what these tools really allow you to do is up level, max out that influence, meaning you can now communicate ideas 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. 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.
- [28:23]
B
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 we'll link 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 Figma and influencing leadership to build these products that they were like, I don't know if we need to slides product. And so now everyone can be a Mexica 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 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?
- [29:20]
A
We kind of talked about like what are AI product managers? You know, how do you build AI power 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 you know, 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. Like, you know, you get kind of conditioned to, you know, 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 sit 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 we talked to a lot of folks of like, well, what are you doing around building around this technology? This really game changing sort of shift in AI. And the first thing that everyone seemed to build was actually another chatgpt but on top of their own data and for some reason everyone gravitated 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 products that were built like how much usage do they really have 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 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 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's sort of, you know, we, we did also ship a small chat bot 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 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.
- [32:47]
B
So what I'm hearing is if you're 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 than new. Anything else you want to add there? Because I have a question.
- [33:04]
A
Yeah, I think there's, there's like. So that, that's, that's almost like a point of like, what do people do for 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. 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 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 framework. But what you can do is take that technology and find a way to apply it in your organization. And that's where I think the role of the AIPM really stands out.
- [34:36]
B
This episode is brought to you by Paragon, the developer platform for building native customer facing integrations with third party apps. Our native integrations on your product roadmap Whether it's to ingest context from your user's external data and documents, or to sync data and automate tasks across your users other apps, integrations are mission critical for B2B software products today. But building these integrations in house cost an average of three months of engineering, according to the 2024 State of Integration Survey, which results in difficult roadmap tradeoffs. This is why engineering teams at Copy AI, AI21 and over 100 other B2B SaaS companies use Paragon so they can focus their efforts on core product features, not integrations. The result? They've shipped integrations seven times faster, all while avoiding the never ending maintenance that comes with rolling your own integrations. Visit use paragon.comlenny to see how Paragon can help you accelerate your products integration roadmap today and get $1,000 in credit on their pro and Enterprise plans that's use P A R A G O N dot com. 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 got to 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 is like hackathons. Is it like here's we have our goals and just like make sure there's AI parts to a solution. Is there anything practically that you find helpful in finding good ideas that are AI oriented?
- [36:34]
A
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 how do I measure, you know, what, what, what should I be measuring here? And I think that PM's kind of gravitate towards metrics and I actually think that, you know, every AIPM 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, it really removes that feeling that 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 there's like this aversion sometimes to hackathons because it's 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 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 bottom 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, we'll classify them and then ping the right person. It turns out that's actually a really hard problem to do because there's so much context that is 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 know, you were looking for problems to go and be solved with AI, but I think part of that is really looking at, like, what are successful AI products today. And you can probably, you know, try a few and name a few. But, you know, a good example of that might be. And really, like, 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 Java way entirely. And there's, there's this story of, you know, Betty Crocker like actually, you know, launching this cake mix where all you have to do is like mix water and 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 needed was this cake mix. And it turns out that actually like tank their sales. So all they had 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, 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 self driving car, like the car is fully self driving but you can still control the air conditioning, you can still control the music. 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.
- [41:25]
B
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 delivery, food making. I have, I have a friend who's like tell who told me that he cooks, he's cooking a lot these days and just like finding all this time to cook and then 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.
- [41:54]
A
Yeah, but actually if you, 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'd probably build something closer like doordash, which is just you press 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 product know. AI makes your product easier 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 problem away.
- [42:45]
B
Such an important point. And 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 a tangent from advice you were sharing on what separates typical AIPMs from 5%, top 5% PMs and what else you, what else you got? What else you got on that list?
- [43:08]
A
I'll actually, I'll kind of steal this one a little bit from our friend Kevin Yin, 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, you're, your job 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 pushed by your team and your company to go and solve a business metric, move a business metric in some way. The goal though is to make space for the other things we were talking about, which is prototyping, you, trying the tools firsthand yourself, making space for your team to have hackathons and try the tools themselves as well, breaking down product experiences that are really great. So as an example, we did a teardown of the Notebook LM product just yesterday as part of our company. So we live streamed it and we're going to do this 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 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. So I think I come back to that point of you have to be able to walk and chew gum. You have to continuously 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 might 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, I think you had a point earlier as well, which is like, you know, 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 failures, but the goal is to keep iterating. 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 AI. PMS do that.
- [45:34]
B
I feel like this metaphor of walking and chewing gum doesn't communicate the difficulty of what you're. Of Kevin's, 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. Yeah, well, I think it's. And bubbles. Maybe gum. Bubbles and dance.
- [45:54]
A
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, doesn't make sense. You can do more than one thing.
- [46:04]
B
Anyway, we don't need to solve it right now. 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.
- [46:23]
A
Now 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, that's the, the hard part about the job, but also maybe the most important, impactful part of it.
- [46:56]
B
I love that. Okay, so let's put an 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 skillset 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, or they don't even think it's an option. So here's my question here. What are some of the biggest habits, mindsets, lessons you've learned about how to be really successful as an IC long term?
- [47:44]
A
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, customer's 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, 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 an ICPM is really hard. It's, it's, you know, I made a point earlier of like, it's become easier to break into product management to some degree if you can use these tools. And now you have all these tools at your disposal to go build a 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, 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 energy waiting versus wandering, and then amplifying the signal to make a decision.
- [49:13]
B
Ooh.
- [49:14]
A
Yeah.
- [49:14]
B
So.
- [49:15]
A
So maybe to even just kick off, like, energy. Can 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 bring 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 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, you'll find that that can actually break down barriers and people, like, 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. Where, like, you know, as a writer, you might be trying to get to that, like, next paragraph. 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, 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 kind of faced with this decision that felt pretty existential, which is like, how much do we want to invest in LLMs and the sort of new wave of large Language, model, tech versus 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 I'm just going to be our outbound salesperson and just start writing LinkedIn messages to people that have the title AI in their LinkedIn profile. So I just went on LinkedIn. I literally just started, like, finding ways to get them on a phone call. So I'd like, 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, 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, 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, you know, all of the tough stuff as well. 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 it. You just have to kind of bring that energy.
- [52:49]
B
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?
- [53:16]
A
I actually think this depends a lot on the person. Like, I think that's actually like a personal, personal thing. So 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 the 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, 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, you're bringing the energy level of the room up versus bringing it down.
- [54:14]
B
I have a, I had a PM I was working with at one point. That is the epitome that every meeting he walks into, he's just like, solve some problems.
- [54:21]
A
Woo.
- [54:22]
B
Let's do this. Like he comes in just positive and, and energized and that just changes the whole feeling.
- [54:28]
A
I remember this like early lift anecdote. I have some friends from like the earlier days at Lyft and I think this may have been in the self driving car division, but like they would literally, I'm not even kidding. This was like their ritual 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 going to do this. It was like one of their values and we're going to, you know, we walk away from a decision and we're going to 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 really work its way up. 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 as. 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.
- [55:32]
B
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 and, you know, energizing folks in the, 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.
- [56:07]
A
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, 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, 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 whole team kind of push along better as well.
- [57:00]
B
Awesome. So let's keep talking about other things you found helpful in 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.
- [57:12]
A
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 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 latent, like, energy. You're going to bring to solving a problem. But, like, at the end of the day, you as a 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 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, 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 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 for the next open AI 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 going to 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, there was this moment in the. In the company's history where I was like, I was, like, grabbing a beer with one of my engineering managers, and he was like, look, man, like, I kind of show up and I'm like, maybe I wasn't bringing 100% of my energy, you know, at this end of the workday. And I was like, like, I'm just not sure where to take things and what we're doing right now. And it was so interesting to hear his perspective of. 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, the next, like, three weeks of Sprints planned out or something like this. And 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. 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 next features and next next part of the company. And that, that part was. Was really tough. But I actually think that's where, you know, kind of to an earlier kind of like part of the discussion where, where an AIPM can really stand out is in being a natural launderer 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 the space that feels really squishy. And I remember like talking to our founders of. And 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 Aparna, 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 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, you know, like, where do we go? Where do we go from here?
- [61:42]
B
So my takeaway here is if you're feeling like you have no idea where your product is going to 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.
- [62:04]
A
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 for instance, to like understand like what are maybe prospects 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 eat 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 the most 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. So you can like pull all of that in. Maybe you want to turn it into a notebook LM episode. But what you can do is actually just find ways to find signal through the noise. And that kind of gives you an ability to almost have like a superpower because you can be in so many places at once and 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.
- [63:19]
B
Anything else along these lines of things that have helped you be really successful. As we wrap up and approach our very exciting lightning round, product management can kind of feel pretty serious.
- [63:30]
A
You like, there's some big decisions that sort of weigh on your shoulder. But I honestly, I remember having this discussion with one of. One of our board members actually and who's. He's a serial entrepreneur. He's taking 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 know, 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, to be the, to, to be like high energy. It's just more fun to, you know, like really care about the thing that you're working on. 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 wandering but have fun with that too.
- [64:25]
B
I love that so much. And it resonates so deeply with me as I've shared a couple times on this podcast to 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.
- [64:38]
A
Yeah.
- [64:39]
B
And it's like the lamest little post. It just sits here.
- [64:42]
A
Is it like really tore it up at this point from. Or is it like, it's like, you.
- [64:46]
B
Know, I just bent a post it in half and just road, 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 he 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, all 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.
- [65:15]
A
It's just more fun than not having fun. That's like a really silly life. But yeah, it is.
- [65:20]
B
And even if it's like very stressful and scary, just reframing it too. 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.
- [65:34]
A
Totally. Yeah.
- [65:35]
B
Awesome. Well, aman with that we reached our very exciting lightning round. Are you ready?
- [65:43]
A
Ding, ding, ding, ding, ding, ding.
- [65:44]
B
There's a ding that comes that we overlay.
- [65:46]
A
I know.
- [65:47]
B
So I always have to resist not saying ding, ding, ding.
- [65:50]
A
I know. Yeah. Yep, I'm ready. Let's do it.
- [65:53]
B
First question, what are two or three books you've recommended most to other people?
- [65:57]
A
I really love Short History of Nearly 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.
- [66:11]
B
And.
- [66:11]
A
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 learned that like, Newton was kind of an asshole to like the coworkers he had or, you know, or like Darwin wasn't maybe perceived as like such an amazing scientist at the time. Like, uh. And so a lot of. And A lot of these scientists, like, their discoveries don't become famous. 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 they discovered. So to me, it was really interesting to hear, to one listen to read more about 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 because it's pretty easy read as well. Um, 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, you know, one of the founders of ideo, and these folks are Stanford professors in the design lab. And what's really powerful about this for me is it's actually pretty practical. 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, 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 just. I love both of those books because they're. They're really, like, shifting in from a perspective standpoint.
- [68:37]
B
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?
- [68:49]
A
I don't usually binge watch tv, I gotta be honest. Like, I'm not a binge watcher, but it's been a little rainy in New York lately, so we've had a little bit more time inside on weekends. And I've been obsessed with the Tour de France documentary on Netflix. I don't know if. Have you 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, 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.
- [69:46]
B
Is there a favorite product you've recently discovered that you love? Maybe an AI product, maybe not?
- [69:52]
A
I. 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, V0 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 web sim. 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 is possible. And, and it's so hard to describe. I remember even, you know, we. I saw a presentation from some of the founders at WebSim 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 and they were just looking at the, at the web sim 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 thought that was like super. 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 the product I've been using the most lately? And this one's going to sound kind of, kind of weird, uh, but I'm a little bit old school and I, I actually like, like you, I like to like write note 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. And this was, this was 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. It's 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. Create this like feedback loop in my head of like I, I enjoy like using that notebook. Now I'm not sure what that means if, when I run out of papers in this one if I'm gonna buy another, but that was, that was really funny. I didn't expect it like that one as much.
- [72:10]
B
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?
- [72:16]
A
It's called Appeal. A P P E E L. Amazing. Yeah.
- [72:22]
B
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 going to have a good one.
- [72:32]
A
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 share it with my friends. It's literally just called that. That 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, 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 at the same time, I think what's been really powerful for me has been to look, 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? And thinking about that really deeply and making decisions along the way based on that.
- [73:41]
B
So I truly love that sentiment. And it came up recently in another conversation with J.M. 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 cricket player that is number one on Google in many ways.
- [74:05]
A
Oh, my God.
- [74:06]
B
Tell us about how that feels.
- [74:08]
A
This is going to sound crazy, but I, I was like, thinking. I literally, I was thinking about this yesterday. It's gonna sound crazy because I. I was like. 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 if, you know, when I have kids, like, they're gonna have some unique names because it gets so much harder, like, you have to type in, like, Ahmad Cod, San Francisco or Berkeley or something to, like, get that to pop up. So.
- [74:40]
B
Yeah, so it does bother my takeaway here. Yeah.
- [74:43]
A
Okay, we'll. We'll iterate all that for the next.
- [74:45]
B
Or. It's a. It's. This is a goal. I feel like you have the chance to beat. Beat this guy.
- [74:50]
A
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 because my partner works at Google, the future might look like, what if we, you know, what if we're using LLMs more? It kind of gives me a second shot here to like, be part of the training data set in a way. So. Yeah.
- [75:08]
B
Amazing. I love the silver lining there. Aman, this was amazing. I think this is gonna be helpful to so many people trying to get into AI, trying to thrive as an aipm or just wanting to stay down the IC track. Uh, 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?
- [75:35]
A
LinkedIn is probably the best way. I'm not super active on X though, you know, might, might spend a little bit more time there, but LinkedIn easily. And then to that note. Yeah, how can listeners be helpful? I, 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 who spoke at the college I went to and he put his email up on the board and his like note was I'll email anyone who emailed 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 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.
- [76:50]
B
That's an amazing collection you're going to build. I want to see all these things too. I love that idea. It's almost like a mini lightning round. What a clever idea. Aman, thank you so much for being here.
- [77:02]
A
Thank you so much. Lanya, this has been awesome. Really, really had fun with this one.
- [77:06]
B
Same for me. Bye everyone. 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@lennyspodcast.com See you in the next episode.