First Funders

01 - Shalin/Shaherose A/V
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Shaherose: [00:00:00]

Welcome to the first funders podcast. We're back after the new year, the last time we recorded was in November and so much has happened in the world. So much has happened in the tech industry. So much has happened, of course, in AI that I took a few minutes to think about. Where I want to take the podcast in season two and where I want to go is into the future.

We talked a lot to a lot of VCs and angels about their journey to investing. We talked about lessons learned, mistakes they made, things that went well, and it was all a reflection on the past. And now I want to look to the future because so much is changing so quickly, just in the short period of time from November to today, models [00:01:00] have evolved.

China got into the game. we have a new president. so what I wanted to do is bring people who I admire and trust and love onto the pod to just talk about what they're seeing in the future.

We'll also learn about investing as well. we'll do it all So today we have Shaleen Mantri, someone I've known for a very long time. I think we met 2010, when you were at your startup noise toys.you moved on from that startup and I don't know if you know this, but I I toyed with.

Pitching you an idea. Cause I wanted to actually work with you, but I didn't have an idea. I was just like, I like this guy. I want to work with him Then I saw you go to Uber and from there, skip and eventually Google. And then when I started investing I thought who are founder operator profiles.

that should be on cap table, should be on cap tables and you immediately came to mind. I invited to join in as an investor. And you said yes, which I appreciated. So it's fun to have [00:02:00] invested with you in a couple of deals early and growth stage.

And it's even more fun to see you now in transition. And we can talk about. Where you might be going, or we can keep it secret, but we're excited to have you on the show today. So with that I would love for you to introduce yourself and just share a bit about how you got into investing

How Shalin evaluates angel deals and deploys checks
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Shalin: Yeah, absolutely. I'm humbled by the intro Shaherose and I'm excited to be on the podcast and a little bit nervous. Like I said, but, we'll see where the conversation goes. So a little bit about me. I have been in the Bay Area for a long time. I'm originally from SoCal son of immigrant parents and basically got immersed in sort of Silicon Valley culture, at a, an early point when I came up here for college and I was always beaten down to yeah, you got to start a company or join startups.

So that's exactly what I did, for most of my career. Take And in many ways, I was chasing that startup dream when I started noise toys, which is how we we got connected. And it was that noise was where I first [00:03:00] learned what an angel investor is. I had no idea who an angel investor is, what they do, what's their reason for existence.

I'd heard the term before but it was a pretty foreign concept to me. I thought it was just like, you want money, you go to VCs. I had the fortune when I was doing noise toys. And I'll explain quickly what the, what noise phase was. me and my co founders wanted to connect musicians with their super fans.

We found that music discovery was being relegated to listening to songs on the radio and whatnot at the time. And it was really hard to discover and connect with people like artists you care about. So we were trying a number of concepts. This was early in the iPhone, mobile days.

So we're doing it kind of iPhone iOS first. And we, pitched it the first tech crunch disrupt. We got connected to a bunch of, investors. And we very quickly found ourselves digging ourselves out of a hole because there's a bunch of people willing, especially on the vc circuit, willing to talk to you, especially if you're doing something new and interesting.

But there's very little action that [00:04:00] ended up. Yeah. Happening from it. Frankly, we wasted a bunch of time with VCs. And that was a huge learning moment because we had to go back to the drawing board and connect with people, frankly, who would just mentor us through a very challenging moment in our journey.

Two people that really come to mind. One was this guy, Kittu Kalluri who's a VC now, and Charles Wong, who is the co founder of Guitar Hero. I don't know if you remember Guitar Hero but awesome music game. And both were incredible mentors during the challenge moment. We pivoted the company and during our pivot, both of them said that they would write the first check in into our company.

And in many ways, they believed in us. More than we believed in ourselves or even our idea, and I can't tell you how much their involvement in noise toys meant to me at the time, but still to this day, I come back to that and that really [00:05:00] delicate, sensitive moment. I was in as an entrepreneur and. I remember how amazing they were.

And both of them, became have become great friends. Kid too, for instance, was at my wedding. He took pictures at my wedding. And he is someone I still come back to every few months to be like, Hey I need your help, figuring something out. And so

I invest or how I invest is yeah.

It's coming back to that emotion, frankly, of there's a pay it forward a mentality that I think I have, which is, I want to be there for that next generation of entrepreneurs that is either they're onto something, or they might be experiencing difficulty. And it starts really with a kind of a mentorship, relationship.

And then money exchange is just an excuse to actually participate. The second is. Honoring relationships I've had with people I've worked with. So as I think about, some of the companies I, invested in, these are people I worked with really closely at, [00:06:00] Uber and other places.

And it's just. People I believe in frankly, it's less the idea. It's less the product. It's really about I'm making a bet on this person. And then the final thing I'll say is learning. I I put in small checks into some companies, not because I think I know the right answer. I think this is going to be the next unicorn.

But frankly, it's just an excuse for me to participate to learn. A space that I want to get more into. I have some value to provide. Perhaps there's an angel with my network and my experience, but it's an excuse for me to actually just take you back off of what I think is interesting. Obviously, there's some stuff in there today.

And then all that being said. For me, angel investing is not charity. I think it may seem like, given everything I said, that I'm doing this because I just want to give back the reality is I still have to believe that I can make a return on my investment if I were to do something.

And so that's a constraint, I put on it, but it's not the primary objective, if that makes sense.

Shaherose: I [00:07:00] love that. I love it. Sounds like the true original, description of what an angel is, right? Someone who is a first believer is paying it forward is honoring the people you have previous relationships with and to learn.

I think people only focus on that last piece. And that piece, you can only learn if a company is doing well and is going to lead to some sort of return. So you need all the pieces together. And I think we need people like you supporting founders at that early stage with also the empathy because you've been through it.

So So grateful you, you've stayed active as an investor. Speaking of staying active, how many investments have you made and how long have you been investing? And just for the audience to know, assuming you are still angel investing right now is your check size, any sweet spots to mention love to hear a bit about that.

Shalin: Yeah, absolutely. So I've been investing for about eight years or so. Total number of deals is around 25 to 30 at this point. A lot of [00:08:00] them in the early days came from connecting with a a friend of mine who started. Basically syndicate and has been sending just every now and then deal flow connecting with you showers to, get some of the deal flow that way.

And then as the Uber network evolved and people left Uber, Uber became this, or ex Uber alumni became this breeding ground for startups. And so a lot of my deals came from Uber alums who were starting off doing their own thing. It's an extraordinarily entrepreneurial. Network, as you might imagine.

And some came from that. And more recently it's been folks doing interesting things in AI which we can talk through generally check sizes. I have three categories for check sizes. One's in the kind of 5 to 10 K range. Second is in the, 20 to 30 K range.

And then the third is 50 K plus. I don't normally do more than 50 K. But there's a, a couple of deals that have done that generally, the way I think about [00:09:00] check sizes is the 5 to 10 K is it's what I was saying before. It's the excuse to just put a little bit of money in to get involved.

It's not going to break the bank. It's not going to make, make me financially independent. Okay. But it's really just an excuse to get involved and to learn and to help. Especially in an area where I may not know the business super or I'm not a domain expert. The second check size.

20 to 30 K is where I feel like I do have a little bit of insight that would be useful. And I believe in the opportunity. I might be new to the team. I'm not super familiar with the team, but it's either a product I love or an opportunity I think, exists. And so I want to invest there.

And then the 3rd category is the 50 K range, and those are the ones where I need to be. I need to be banging on the table.

Like I really believe in the founder. I have some personal connection with them or I feel super strongly [00:10:00] that they're going to crush it again. the opportunity is amazing and they're showing traction and so on. They might be a little bit later stage. And so an example of this is my, my own brother started the company and the medical devices space recently.

Yeah. And that's a good example where I've got a family connection. He has a track record of doing incredible things and he was making really good traction with the startup. There's another investment I made in a company called VLO dot AI, which is an AI for bike safety startup that was started by one of the lead AI engineers at Uber, ATG, the autonomous vehicle program back in the day.

And he wanted to solve bike safety with better kind of AI tech. And I believed in the problem. I ride a bike I believed in him and I think there was, a real opportunity to capture that market. So made a fairly big investment, in, in that type of company.

Shaherose: I love that. Can you tell me a bit about.

Shalin: How you decide, right? You touched on it a little bit. Maybe you [00:11:00] believe in the founder, maybe you know them, you believe in the opportunities there, and some angels don't have frameworks, but I'm curious. Do you have a framework that leads you to a no or a yes that you use with every deal? I don't have a structured framework, perhaps the way a VC does.

So it's not yeah, for me, it's not scientific. Like I said, it's, gut. And, again, if I were to classify the things that come to me, it's either I know this person. I literally know this person. I believe in them. I think, whatever they touch, at some point that they're going to do well, and I want to make a bet on this person.

And then the other category is I don't know the team. I don't know the founder, but I believe that they're doing something or have some insight into how to attack a space that is truly unique and differentiated. And, they're going to be successful that way. And I think keeping it simple.

Just like that, right? And not trying to overanalyze, frankly the deals, because [00:12:00] I feel like there was that. Remember that story or that anecdote? There's like a monkey choosing bets in the stock market. If. Like a monkey randomly chose stocks to invest in. It turns out that they do better than the average like mutual fund manager.

Shaherose: I'm probably butchering this, and that may not be true at all. So please don't take that verbatim. But the point is, you just have no idea, chances are most of these companies are going to fail. And you can try to play Midas and touch 1 and you think it's going to do well, but, no one knows. I don't know . Yeah. No, we don't know. And neither, neither do professional VCs who've been in the game a long time. Even if they,

Shalin: that's, they don't that's comforting .

Shaherose: Yeah. I love that. I love that. When I was also, sharing investment opportunities with you as an angel, my first focus was do I know this person?

And have I seen them over the years execute in a way that gives me the confidence and sort of mitigates the [00:13:00] risk on the people side. And so I, I love that for angels because you're not doing this full time, putting some elaborate framework, again, is for what, right? we're here to support what we believe in.

And so I think this guidance of keeping it simple, especially when you're doing it on the side is spot on. I love it. Thank you.

Working at Uber during the early(ish) days
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Shaherose: What's coming up for me is a question that just, you mentioned Uber, you were there five years into the journey of the company and they're doing, the early days really of scale from, and you can correct me, right? Okay. So having been a part of a prolific venture scale unicorn.

That some argue didn't need to be this way, but achieved the outcomes that we all look for in a breakout company. How has that experienced influence, how you invest or how you think in general? Is there anything there that, would be worth sharing for people who are thinking about?

Investing [00:14:00] because you lived the dream.

Shalin: I don't know if it was a dream at the time. It was very hard and it, kicked me in the ass over and over again, but it was the most formative professional experience I've ever had up to this point. Yeah. And look like Uber when I joined, the reason I joined is I really felt like.

It was changing the world, and it had the potential to change the world, and it was cool from a consumer standpoint to press a button. You get a black car, right? We all love that. That was incredible. It was really cool. But I think once my eyes opened up to the. Oh, wow. This could actually create opportunities for millions of people and bring flexible work options to them in places, not just the U.

S. But places like India and emerging markets that for me was a game changer. And how I thought about, the company has potential. Now I was employee somewhere between employee 300 to 400. I was in the first couple of product managers at the [00:15:00] company. And I came into a crazy moment in very early 2014, when it was transitioning for mostly a black car company to Uber X was growing rapidly.

City growth was going exponential, going international. China happened soon after I joined. India happened soon after I joined. And then all the products you know and love, Uber Eats, et cetera. Happened a little bit later. Did I guess I, I learned from that, I saw the company expanding before it was really ready to, and in some ways that goes against my instinct as a human being where I want to feel ready to tackle a challenge before I go do it.

And this was a constant state of, ship launch. Go before you're ready for it. And you know that if you do that, then you'll respond to the updated context, and then you'll figure out what to do. And it required an immense [00:16:00] belief in yourself that you'll figure it out. It required incredible trust with your teammates that you'll be able to figure it out together.

With your team and it required a leap of faith that this is going to be, better for achieving the mission, achieving business, viability and so on and so forth. There were some anti patterns from that experience as well, which is part of doing things before you're ready is a lot of it was VC funded and capital was cheap, at the time and what investors were telling the leadership was, yeah, keep growing growth at any cost.

It doesn't matter. And we had very few financial controls and are maybe literally, but I'm not as familiar with that. But figuratively right in decision making, when I was deciding to, build a feature product the cost [00:17:00] was not. I think we thought about it was like is this cool?

Is it going to make the experience better? Is it, going to help us grow then? Yeah, just go for it. And that, I think, as, it took years and years to unwind or pivot that culture. And it's amazing how much though the company. Became what it was because of the venture dynamics, and that's something that, is a really relevant question, I think, for the next generation of entrepreneurs in the environment we're in, which is how much do you shape your company after the dynamics of like, where capital is cheap and the liquidity exists versus You go your own path.

I don't know. I have the answer, but I do look for signals of how my, portfolio companies are grappling with that. I frankly don't go too deep in it but it is a question.

Not all growth is good growth
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Shaherose: And [00:18:00] meaning you are curious about whether they're adopting the growth at all costs mindset and are you advocating for it? Or are you at least hoping that there's a middle ground or not even going for it. Like where do you land now that you've gone through the journey?

Shalin: Yeah, I think there's, I hope there's a middle ground between kind of growth and like somewhere like responsible growth that You can also own your own destiny.

You're not beholden to investors. I have been part of numerous startups that sort of failed because they were chasing the venture dream. In fact, the company I worked at. Right before joining Uber basically had grown too quickly because VCs wanted it to grow. And it started running out of money and they had numerous rounds of layoffs.

I was one of the people who got laid off from that company. And then I applied to Uber that night, I got laid off and. The [00:19:00] rest is history. I haven't told that actually publicly to too many people. But it's a thing we can talk about some more. And he was coming back to it. I think there's a balance between growing before you're ready and really reaching.

And. Actually ensuring that you're doing it for the right reasons, you're doing it because to learn to because there's a window, or because there you see the competition in the rearview mirror and you just need to be 1st. There's a 1st mover advantage. But growing because.

That's what VCs need to see in terms of traction. We've all seen the story. We know that's how this ends. And so I, if I see that in some companies, if I see, for instance, is valuation is starting to get out of control because everyone's chasing after it. I run the other way. I'm just like, I don't want to be a lemming.

I don't want to be like everyone else. And even if it's a company that I believe in and, subscribe to it's just not, it's just not who I am and how I think I want to [00:20:00] invest.

Shaherose: Thank you for sharing that. I was out with the flu last week and I binged on super pumped.

Shalin: I got through maybe one or two episodes of it and then I just I couldn't watch the rest of it.

Shaherose: That's what happened to me the first time when it came out. I was like, I can't this. This is too close to home. But I got through it and whether it's capturing the truth or not, I can get a sense of the main theme here through that and then through you, which is, move fast, break things, which everyone talks about.

And so I'm always stuck right now that I'm a venture investor full time, that model has played out and led to failure and led to success. And so what are the examples of disciplined growth that you're talking about? And do you have any? I'm curious if you do. Because even just the little things that you, like you said, that like for the right reasons, right?

And so for a founder to discern, what are the right reasons for growth? Okay, this time we're learning. Okay, [00:21:00] this time we're going into a new market, but the margins. Must remain or we pull out in like things like that. I'm thinking, right? Is that what we as investors want to impart on the next generation of founders?

Because the capital is no longer in Zerp era and it has to perform. And so is it about risk mitigation or is it that it has to perform and we still do move fast and break things like I'm not sure.

Shalin: It's such a great question. I want to caveat what I mentioned by saying, yeah, like you said, there are probably scenarios where you want to support a move fast because market is closing or the window is closing.

And now coming back to Uber, if it were more disciplined, it's very possible that Uber wouldn't be alive today. Because it would have gotten regulated out of existence. And so if you take the venture dynamics out there was a moment where, what Uber was doing and what looked we're doing [00:22:00] was in a legal gray area, slash clearly illegal in certain markets, and it had to go quickly to capture consumer hearts and minds.

In order to even have a company at the end of it I think it's important to acknowledge that there isn't a one size fits all thing here. And in a world where a company is truly disrupting either with a new product a technological innovation. A new business model there may need speed might be a critical enabler for long term success.

And it's important that the venture supports that and is aligned with that. Now, the other thing I'll mention is. I think sometimes venture money and even angel money chases after companies because of [00:23:00] early signs of traction. And I found it's really important to be honest. Does the company, does the team have product market fit with their V1 product?

And it's so easy to either just again, follow the leader oh, there's a lead investor, they believe in the team, the company, etc. And we'll invest. There's also, it's also tempting to see early signs of traction oh, look at this exponential chart, or some kind of cohort analysis retention thing.

But to lose sight of basic frameworks, like crossing the chasm, I'm a huge fan of Jeffrey Moore and the crossing the chasm framework. I think it, it stands the test of time as things go. And this idea that technologies have an adoption life cycle. And, if they're disruptive, like they'll first start with like enthusiasts who just want to play with tech, they'll go to visionaries who are willing to bet on the future vision of a tech.

There's this big chasm before you reach pragmatist buyers who will pay for something because it has [00:24:00] value and they'll share it with their friends and so on. And they hit the mainstream and what ends up happening is VCs and investors are in that visionary. Segment. They like see the future.

They believe the team. They know this is like the way things are going to go. And then boom, there's like this chasm that a lot of companies fail because they think that their early traction is actually a leading indicator of mainstream success. But in many ways, those audiences can be different.

And I know you have a marketing background, so you can probably speak better to this framework than I can. But that, when I learned about that framework, it really stuck with me. Because I've really taken my own I know that what kind of buyer I am when I look at technologies, I'm a pragmatist, I'm not the kind of person who's going to be first to try.

technologies, which is weird to say. I feel like that's not a cool thing to say. If you're in the Bay Area, you always want to be like, Oh yeah, I've got the latest, like a gizmo gadget and I'm on the latest, using the latest LLM a du jour. But I am very much a [00:25:00] pragmatist, buyer and Because I'm a pragmatist buyer, I have an instinct for what actually could cross the chasm and become more mainstream because I know if I see it and something has utility and has value.

I'm probably not the only one. So I try not to get too excited about. Signs of traction early on, but to really think about, okay, let me place myself in the customer's shoes, or even just imagine I'm the customer. Would this solve a real problem for me? And that's a lens I look at.

Shaherose: I love that.

I love that. And I can resonate with that too. In some spaces, I am also a pragmatist and in other spaces, I'm an early adopter. And so I know what you mean when you say, okay, as a customer, is this a value would I be willing to pay? And evaluating, opportunities and, new technologies and that is, we can only bring what we know to the evaluation of an opportunity.

And you're doing exactly that. I want to jump ahead [00:26:00] to. Now, this has been juicy conversation on what you've learned, right? And so having, having been someone who's gone through the founder journey, gone through the early days of scaling, a unicorn then going on to starting a new unit at Google, oh, and I skipped the opportunity at the time when you were at skip also, which is like all of those experiences have really shaped.

Exploring the interplay between AI and AVs
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Shaherose: You to see the world in a certain way, and I want to look to the future now. So as someone who's been a product leader across that journey and someone who now is an expert in the mobility and transportation space, let's talk about that. What is the future that you now see, whether it be in the product space, mobility, transportation, that you are excited about?

Say a five year I'm not even talking out way, way out because I think things are changing so fast. What's the world look like to you from where you stand in five years and 10 years?

Shalin: Yeah, so we can break this down [00:27:00] into let's call it personal mobility. And then we can talk about the broader transportation logistics sort of industry personal mobility.

I think, as you can't. If you live in San Francisco, you can't throw a stone and not hit a Waymo that is driving itself autonomously. So if anyone finds themselves in San Francisco, Austin, Los Angeles please, you have to get into one. It changes your whole perception and understanding of what the future of personal mobility could look like.

And it is very exciting to see a technology that has been in the works for many years has gone through many cat lives of being like, Oh, I think we're there But now we're, it just dies and it's finally achieving some inflection point of scale. And that's that skill is real. And I worked in autonomous 8 years ago back 2016 at Uber ATG on the eve of the [00:28:00] 1st.

Pittsburgh ride sharing launch of a self driving cars for a couple of years during the crazy years. And, at that time it was a technical problem. It remained a, this is an unsolved technical challenge to have a car that could not just drive itself, but it actually can demonstrably prove.

The safety case way better than humans on the same roads that humans drive on. And Waymo has achieved in the last year, basically critical, demonstrable, measurable safety measures. So huge kudos to them. I think that's going to change the ride sharing industry. Certainly in a big way. And as, Elon Musk with Tesla is trying to take personally owned vehicles and turn that into kind of a a ride sharing model, which I think could be game changer for the overall auto industry.

Now, all that being said. If I had my crystal [00:29:00] ball on autonomous vehicles, we're not going to see at scale deployments in the next 2 to 3 years. That's going to fundamentally change the dynamics of the industry. These are still going to be limited to dense urban areas just to justify the economics of.

That model the cost of the sensor equipment, the operations and so on. It relies on density of demand for high value trips like airport trips and things like that. So that's why it's going to work in the San Francisco's Los Angeles, New York's though New York has a. Difficult, challenging regulatory environment but it's unclear if it's really going to make its way beyond into kind of the tier 2, tier 3 markets at a meaningful scale.

So it'll be interesting for us to watch that. The second area we, I touched on before was the overall transportation logistics industry. I'll [00:30:00] cover automotive because that's related. It'll be interesting to see if everyone else in the industry outside of the Waymos and Teslas, how they catch up effectively to this world of increasing levels of autonomy.

And it's clear that a lot of the traditional OEMs, they've been dying a slow death, and I had a chance to, work with some of them, during my time in Google Maps. And I think the world of how they make, products like they, they make incredible products like no other that achieve a certain level of quality.

They're also not software companies. They're not, able to bring a really engaging and immersive and, assistive, let's say navigation tech in the vehicles by themselves. And so we're going to see just this confusing constellation of partnerships and, joint ventures and mergers and, you bring your software and that's been happening [00:31:00] for years.

But I think the pace of that's only going to increase. And so I wouldn't be surprised to see consolidation in the auto space is just going to continue and continue the overall logistics industry, I think, is. Really interesting. Because it's a bit of a contrarian bet right now. For context, during my time in Google Maps, you mentioned starting a new line of business.

My ambiguous prompt when I joined Google Maps I was on the enterprise enterprise business that sells APIs and SDKs to third party developers. It was to create a new business line in logistics to figure out how Google Maps is going to crack those movement of things, not just people type use cases.

E commerce had been accelerating pandemic lit a fire under e commerce. Everyone was doing it. And so you had the whole ecosystem essentially get funded in a huge way. Because we all thought that the trends, the growth trends were going to continue many years in the [00:32:00] future. And of course, we realized.

After the pandemic sort of subsided that, oh, there's a huge exhale effect. There's a huge pullback. E commerce growth is not as high won't be as high as what we saw during the pandemic. And that was had a huge negative impact on the logistics industry. So over supply over glut of warehouses and whatnot, geopolitical tensions with, supply chains, in various parts of the world.

So generally, I would say people are not Poo pooing on logistics as an area, whereas just 34 years ago, you couldn't go wrong if you're building a tech forward logistics, company or startup. And I think that pendulum is now logistics generally is a, a cyclical business and industry. I think that pendulum is going to swing back because of what's happening in, AI.

And the fact that. AI is more than just a great consumer tool for answering questions. It actually is able to solve real [00:33:00] offline problems in logistics. Like, how do I know where a driver should go if there's, they're in an unfamiliar area? What kind of guidance, instructions can I give them if they don't know where the door is?

Turns out Google Maps sometimes and oftentimes doesn't know where the door is. But can you take imagery right of an area and then convert that into like really helpful guidance. There's the where do I put a warehouse, in a, in this area, if my demand is uncertain, or I want to be able to handle for.

Stable demand in these areas, but there's also geopolitical shocks or externalities that can happen. It turns out that making sense of a bunch of data and, helping inform iterative strategies. That's, LLMs and related tech is getting, much better at that kind of stuff.

Anyways, long story short, I think logistics is a very [00:34:00] interesting place, a contrarian sort of industry for for folks to look at. That's not, super sexy right now.

When the big bet doesn’t lead to the big payoff
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Shaherose: Yeah, I love that. Thank you. I'm curious about from your journey, were there any bets that you took in, the mobility, transportation space or bets you took as a product leader, building your teams that you were like, completely wrong about that we should know.

Shalin: Yeah. So you had mentioned I worked at skip and the big bet I would say generally for a lot of us as either investors or operators was micro mobility was. Going to be a it's going to change the world. Everyone's going to want to jump onto a scooter and then, right around and, do all the things to go grocery shopping, go see friends, go be a tourist, or even just as a commuter, like from the train station to your work.

And I think I got caught up in the hype, of. Micro mobility is super [00:35:00] cool and everyone's doing it. I got caught up in the the buzz around the form factor is becoming, more more interesting, safer, et cetera. And there's a coolness to working in that industry at the time.

And I ignored clear problem science. And in the basics, right? It was clear that, coming from a software world and going into an operator role where I was doing hardware and software, you can't just think about software returns. You have to think about, where are you buying your scooters from?

How safe are the batteries? How are you transporting those scooters over to the warehouses? How are they being maintained? Who's maintaining them? Where are you positioning? So all these things around fleet management that a traditional software person like me coming into that role wasn't even thinking about.

But I was applying just software frameworks to this, which is okay. A certain number of users, utilization rates of the marketplace, supply and [00:36:00] demand. Okay, let's go. Let's scale without really thinking through. unit economics that factored in hardware expense and fleet management and operational expense.

And so what ended up happening? I was, have a product for a skip and a lot of my focus was on the digital experience, the apps and some regulatory, compliance technologies. But I wasn't as focused on the hardware side and the bill of materials and the, cost of it and the hardware development cycles.

And we ended up just. Running out of money, we just didn't have a good enough product and good enough scale with good enough economics to really survive through what ended up becoming a difficult environment. And to our point earlier, a lot of the traction that most companies sell in that industry was not because of fundamental consumer economics behaviors, it was [00:37:00] because of venture dynamics.

It was also weaving in a lesson I talked about earlier around crossing the chasm. The mistake I made was to assume that early adopters of these new micro mobility vehicles was a leading indicator that everyone was gonna do it. And yeah, I was doing it, but maybe I was actually more of an early adopter for this thing and willing to take the risk of riding a scooter and getting hurt and without and riding in the same lanes as cars, but most people aren't willing to do that. It is just way too unsafe. And so I think when I put the blinders on to things that I just told you I would normally do, like that's what things Things bad things happened, but I learned a lot

Why AI is making it a confusing and exciting time for PMs
---

Shaherose: and we learned the most through these experiences.

I love the insight that, this wasn't just a software pure play and the chasm was really big. I think, honestly, I've never been. on any of those scooters for the exact reason about safety. I don't want to ride along. I've never biked in the [00:38:00] streets, it's just not my thing.

So I think there's so much wisdom in that journey. We actually, one of our early interviews was with Amit Kumar, who led a couple of the rounds. And, he was like, yep, I was all bought in. And we all got. We all got excited for sure as investors and as builders. Let's talk about AI.

You've, you've left Google recently and you've been building, you've gone back to coding and learning deep, going deep in to AI, building some, prototypes and products. And you've really got a sense of where things are going. You've mentioned AI a few times, and this is the meat of the convo is like.

I would love to hear based on the ecosystem that we're seeing today, right? We've got the foundational models, we've got the compute side, we've got these native AI apps. We've got new players that we didn't know were going to play in the space. And what do you think now, if we talk about, again, the future what are your hypotheses about where there are startup opportunities?

And you can speak from a founder perspective or an investor [00:39:00] perspective because I'd love to hear as someone who's, gotten their hands dirty. More recently,

Shalin: I will say preface everything I'm saying, but saying, I'm not an AI experts and I have not been working in the industry for years and years.

I do not have a PhD in AI. That said, like you said I have been spending a lot more time just immersing myself, not just in the news, but really actually as a practitioner. Building a rag app retrieval, augmented generation. So using kind of vector DBS and LLMs to provide a better search experience on your LinkedIn network.

I took an AI bootcamp that it was meant for software engineers, but as a PM, I thought, having the technical grounding and catching up frankly, and to. This confusing array of tools and knowing when to apply which tool to what type of task for what types of problems. I think for anyone in a product building role is a it's a confusing time to really make sense of it.

So all of that has [00:40:00] been super helpful. A couple of kind of thoughts. One is it is really difficult to keep up with the latest and greatest. And if I were in a full time job right now it'd be nearly impossible. I think it's more than a full time job to actually truly understand what the frontier is and where it's going.

And this is the challenge I have today, and I will say it's an unsolved problem. I still find myself every day waking up to the news being like, Oh, some new agent SDK got released by OpenAI just yesterday. I want to go try that. And it's changed the game in many ways, because I tried building an agent experience and there's no good frameworks for it.

And I think it's one lesson is a really important as I think about where I spend my time going forward, either myself or for a team to a lot time and capacity to just experimenting with the latest every day. [00:41:00] Because we don't know. And I don't know when some of those innovations or some of the things get released are actually truly game changer.

And obviously, seek deep seek was a good learning moment for everyone where we were assuming, yeah, you just have to, pay a lot of money for Nvidia chips and or, the standard frontier model companies. But turns out you can just take this model and throw it onto your own, servers do inference on it and boom, you can get up and running without having to pay money to anyone else.

And so I think that was game changer, but there's basically going to be every day a new game changer. And I think that brings me to the 2nd thing I'm thinking about right now, and you and I talked about this, I think, a few months ago, it is super confusing to know what truly defensible.

Moats look like in this world when the underlying platforms that all startups are now depending on basically are just getting disrupted every single day. Anthropics releasing something, [00:42:00] opening eyes, releasing something deep is releasing something is going to be some new lab out of China or India or somewhere else.

That's basically going to release something tomorrow. And you're as a start of building on top of those things. And I think what I've realized over the last few months of spending more time. I was coming at that with a lens of fear and being like, Oh, no this is why I don't think it makes sense to start a company.

It's just too hard. It's too much thrash. But the more I've looked at it, I actually think this creates. insane opportunity to go up the stack to the application layer to revisit assumptions that let's say companies with more traction who got that traction in a world that was pre LLM or on earlier versions of LLMs.

What’s wrong with search these days? Is search being rewritten - again?
---

Shalin: Actually, it can. It can. It's there. There's a crack, there and you can take advantage of that and achieve scale and traction when previously that wasn't [00:43:00] possible. An example of this is wherever you see a search bar anywhere, any app, any product across any industry. If you see a search bar, there's an opportunity to basically disrupt search.

And so we're seeing that with not just consumer search with open and, perplexity and so on really going after Google on web search. But we're also seeing that on enterprise search. Glean, of course, we all know how well Glean is done. It's that sleeper hit, over the last couple of years.

And now everyone's talking about it. But 1 can imagine wherever there's opportunity to bring better search that is, Search for X is a huge opportunity. Now, the second thing I think about is not just solving a search. I don't believe search itself is a product. Maybe if you achieve some level of horizontal scale to it or [00:44:00] breath, like again, Google and open AI and perplexity and so on, it can be, but I think the question is search to what end and.

How does one basically take, let's say, let's look at linked in and, recruiting. How does 1 go from I'm searching for someone to let me figure out who I know in common with them. Let me figure out then how do I make that introduction or how I get the intro to someone? Let me figure out how that person can apply and basically tie the still thread all the way to a successful, recruit.

There's many companies doing what I just described, by the way. So I'm not saying that's the investable opportunity, but taking that same pattern of going deep, on a specific workflow that may start with search and then solving a niche workflow problem for an industry, a user segment and so on and so forth in a way that before.

The economics of [00:45:00] doing that development and serving that audience were previously intractable because you'd have to hire a big team to do search and to do all those things. And now you don't, you get a ton of things for free. And I realize this. And as a quick story, I. I had this problem on LinkedIn where, you know, searching my own network was really challenging.

You have to do standard keyword searches and LinkedIn has been doing search for years and years. And now that I'm in exploration mode, I just wanted to reconnect with people who I trust or people who might be relevant to my interest. So saying recent startup founders boom.

While LinkedIn turns out. LinkedIn barfs on that query. But this is exactly what LLMs are incredible at. And so I, from not having a development environment set up, on my laptop to having a working prototype on my own network that answered those questions better than linkedin. com, I was able to do that within a week.

And for me, that also just. [00:46:00] Exploded my mind as someone I don't think of myself as an engineer. I do have a computer science background and did some, back in engineering 1st started many years ago. It was a holy shit, the game has changed. Cursor, amazing, obviously. If you're not using it, use it.

But every person who has an idea, We'll be able to quickly test it without needing to hire a team or to build a startup. And that was incredibly empowering. And so I'm super excited about a lot of the people that are building the tools to democratize, going from idea to product quickly,

Shaherose: I know it's super fun and exciting.

Scaling companies down to 1 pizza and 1 pizza only
---

Shaherose: And I'm curious again, given the life journey you've had, what do these companies look like? And I brought this up before, last year and I was like, I could see a new type of startup forming, a very lean one, one that tackles a niche space, niche customer need. And when you have a lean [00:47:00] operation, you obviously.

Yeah. Not obviously, but most likely you can become profitable pretty quickly because you're solving a really specific problem that needs to be solved Hopefully you've tackled you found one and are these what are these companies right? We've you know talked about it earlier of you know before we jumped on the recording that you know Some Sam Altman talks about the one, One person, billion dollar company, is that what you're seeing the path for yourself or other founders?

where did these companies grow? Because you've been inside, multiple venture backed startups that achieve scale, but they were, they were heavy, they were big teams. And as these teams get smaller, and the problems get smaller, what kind of company is this to you?

Shalin: Yeah, it's incredible to see, what a small team could do.

And I was talking to some of the folks at perplexity recently. And you know what, they're a 10 billion dollar company or 15 billion dollar company, but only 120 people, so we're not quite at the 1 person, 1 billion dollar [00:48:00] company yet. But, given where things are trending it's not inconceivable to think that could be possible.

And the big reason for that is. We're talking about software and development is just getting eaten up. It's getting eaten alive. I think it's Dario or Sam, Dario from Anthropic or Sam from OpenAI that's talked about. Look, by the end of this year, these AI software engineers, the AI coding assistants are going to be able to replace software engineers.

Now I will say today it's not there. Even as a PM, a technical PM I still have to check the the assistance work and read the code and make sure I understand what it's doing, especially for high high sensitivity like actions. It can hallucinate or not give me, the perfectly right answer.

So I don't trust it completely. Things are trending in a direction where, I might be able to trust it completely. So what that means is if you know exactly what you want or want to build, or I think it's called vibe coding. [00:49:00] Now you just have kind of a sense and you want to try it out.

It's amazing for that. It's not going to solve product market fit. And this is a really important distinction. I think coding assistants and everything, they're really good at doing things that people have done before, and so they can be verbose. They can do make things way more complicated than they need to be.

You still have to have the brains and the creativity to basically guide it and to say, this is what I want. This is what I imagine. And so product instinct has never been more important than at this moment. like knowing what you know to build and what makes for a good experience and simplifying and focusing these assistants that could go in a bunch of different directions if you wanted to do something it'll do it but it'll make it 10 times more complicated and do 10 times the functionality and what you get out of it is a frankenstein sort of [00:50:00] response or a tool or you can imagine like you can build an entire company in a bunch of systems like by just like snapping your fingers and every startup, a lot of startups are going to be building the next company builder template, like press the button and the whole company gets formed out of it.

But because of that, I got caught up in that wave of thinking, Oh gosh, like traditional, product development is dead. And even product management as a discipline as is dead, but I've actually turned the other way. And I realized that truly. Truly focusing and clarifying and simplifying the problem for, and whatnot is extremely important.

And that comes from, People that comes from humans at least for now, who knows what happens a year from now.

Shaherose: I know, right? Yeah, I think what I'm realizing is that kind of like what you said, like nothing can replace product market fit and you only get product market fit by really understanding the problem.

And actually having [00:51:00] a 10x better solution, you can, you only, that's like the genius work is like, what is the solution now you can tell cursor to make it and you've got it out in market more quickly than you would have. But if the input is wrong, the output is wrong and the sort of thinking like the brains, like you said, will become, has always been actually like, even when you input, the desire for a product roadmap to a human, it's the same thing.

If the input is wrong, the output is wrong. So I think like really acknowledging that it doesn't matter. That we can build it more quickly. And what matters is did we really hone in on value creation for the customer? Did we really solve their problem? 10 X better than, and are they willing to pay? Like that whole piece needs to be true So that's great. Like I, we're on the same page there. What I'm curious about is this idea of replacing software engineers. I've had this conversation with my husband. He's a software engineer and I'm like, what are you going to do? And he's I don't [00:52:00] believe. that we're going to be replaced because of what you just said, product minded thinkers, probably engineers that have more product minded thinking will be more valued.

But his thought and sat with me really well was, we live in a capitalist world. We'll just build more. Like we'll just keep building. Like we're just going to keep, we're just going to be moving faster. And so we're going to need software engineers to take on the new projects to define what we're going to build and how we're going to build it.

And to tell. The tool to make it. What's your take now that you've heard this? And maybe even comment on the product management piece a little bit more.

Shalin: Yeah, this is such a fun debate and question and I've honestly flip flopped a bunch. I look at what Dario says, in a AI is going to get better at most people at most tasks, basically, by 2026 to 2027.

Hey, world, wake up. You might be out of a job, and the labor market has to account for this. We're talking A year or two from now, like not five, 10 years from now. So that I think instills a lot [00:53:00] of fear and a lot of people, including myself around our job safe. And honestly, that was a fear that I had at Google that I am doing my job here, but gosh, where is this going?

And how do I need to account for that as a product leader and. Yeah, I agree with the idea that everyone's going to turn into that full stack product builder, if you don't have the skill set across technical design and product, go out and get it. Because in order to be a 10 X PM or engineer or designer you will probably have to leverage the tools to be first, to put it all together in a creative or unique way that solves a problem.

Like you said, and you can go a lot farther faster. By doing it yourself, then by waiting to find, maybe even co founders, [00:54:00] maybe teammates and so on. Like the tools advantage people who have that cross domain understanding. It disadvantages. It can help people who don't have let's say for me, I'm not a designer per se, but I've used lovable to mock up like web designs and convert that into an actual working web app.

But it still requires me to have a design instinct. So if you simply do not have a design instinct or an engineering instinct or a product instinct I think you're disadvantaged in, in this world where truly cross specialty people can actually move faster in, in building things.

Now this question of our jobs can be replaced, our software engine is going to replace and so on. I think I agree with your husband. I want to agree with your husband. Let's put it that way. I want to agree with Rocky. Think it's a yes. And. The average engineer that prides [00:55:00] themselves on really being a dot net specialist.

I've done dot net development for many years. I'm an expert at java or python, etcetera. That is not a differentiator. If that's what your resume says. Those jobs are very much at risk, but if you have some track record or desire to weave your engineering understanding to solve actual real world problems, and you've done that and you've gone through that journey, then I believe the tools will, lend themselves to that Jeevans paradox that you, I don't know how to pronounce it, but everyone's talking about Jeevans paradox where, the more easy, something becomes the greater the supply of a limited resource. It turns out that demand will follow and more things will happen.

I'm totally butchering the definition of that. But it's like what you said, where, because the tools have become easier to use, more stuff will happen, more startups will get formed, more things will get built, more [00:56:00] niche audiences are going to get served. And when that happens, there's greater overall economic value created in the ecosystem than what we have today, and greater consumer benefits and greater value to be captured.

So I think that's going to happen, but I think it's going to happen. Off of let's say the top 1 to 5 percent of people in engineering in design and in product management. And so coming back to myself as a PM leader, I've realized it is not good enough to become a good PM. Like I have to continue honing my craft to be a great product banker and to practice and to try and to keep iterating.

And there's a world where I've done product management for 15 plus years. And yes, I was ended up as a director at Google and one would say, Oh, you've made it. Now you can get any job you want and so on and so forth. And it turns [00:57:00] out when I started talking to some people, in the industry, they're like, Oh, we don't normally hire people from Google because you don't know how to get things done in the real world.

I was like, Oh shit, Google's become like Oracle and Microsoft. It actually has a negative stigma because at a certain point you get promoted enough. You actually are managing your communicating, you're dealing with stakeholders. You're doing all the things that a more nimble startup that's building off of like latest AI.

Doesn't even have to worry about because they're smaller teams to your point, right? They don't need to become a big bureaucratic company. And so I realized I was becoming a worse product leader every moment. I was spending at a big company. I was becoming a worst product person. And there's a parallel universe where.

If I didn't leave Google I don't know if I'd be relevant, in given the pace of how things are moving and how even myself, I need a pivot. [00:58:00] I think my job is not to manage teams. I was managing big PM teams, but I am perfectly fine now being an IC. anyways, I threw a lot at you, but it's not going to wipe out these jobs, but it's that the summary is. It's not going to be good enough to be good. You have to truly be great at your craft and then also have decent coverage and instinct across the other disciplines that make or seed can seed a great product.

Shaherose: For sure. I hear that. I hear that. We're all. required to upskill and go horizontal and become a super version of ourselves in this time.

Shalin’s AI angel investments
---

Shaherose: love this. Thank you. When you think about now. with your angel investor head on. What are the opportunities that you're excited about that you might have already made in the AI space that you can mention?

Or where are you looking to invest now, given everything that's going on?

Shalin: Oh, this is the trillion dollar [00:59:00] question. I love it. Hard hitting. So I will caveat saying, I don't know. That said I think a lot of what I'm doing is just learning. I take, investing right now is again, coming back to that framework of, yes, I want to see an ROI on my investment, but, it's about supporting people and teams and also learning and whatnot.

Right now, I'm shifting more towards smaller checks to learn to get my money. To get my hands in just to develop a perspective on how things are going to play out and it may mean that, I don't make a ton of money on any one deal, but at least it gives me some clarity around what is, what the heck is happening.

I'll give you an example. An ex Uber alum, this guy, Daniel Lehm is co founder of a company called a Gentrace and they are. providing more systematic evals for AI models that are being introduced by enterprises across their entire business. [01:00:00] Classic example is customer service chatbots, right?

Are now, the, their killer use case for Claude and open AI and so on and so forth. So the problem is any one of those. Stat bots, they're still, guardrails around it, but they're still stochastic and probabilistic and how they operate just the nature of, LLMs. Generally, you given a set of inputs, you may not get the exact same output every single time.

And this is a big challenge in the industry. And it turns out that in autonomous vehicles, we had this challenge 8 years ago. Basically, the autonomous vehicle is a black box. It's this ensemble of AI models that are chained together from perception to prediction to motion planning to vehicle controls.

And then many times per second, the vehicle is sensing it is predicting it is planning. It's taking action. And the problem with that is We didn't know what, [01:01:00] given a set of inputs, how the vehicle was going to behave in a deterministic way is very hard to understand that. And so we relied on evals and simulation and scenario testing and stages of testing, both on the developer workbench with a small set of test cases with our targeted set of test cases to a larger test, that runs on a CI, every night to Running on the track and then, out on the real world.

And so I've been thinking about that a lot recently, because it turns out autonomous vehicle development, how you do software development in that world is now going to be how every company is going to have to think about software development. You're going to have to think about it from a systems engineering perspective, you're going to have to acknowledge that the software is probabilistic.

It's not deterministic. And that is a huge assumption shift. That means that you're going to [01:02:00] have to get a lot better about testing and really documenting, given a set of inputs of what you expect as outputs, and then holding yourself accountable to that because you never know if you link to deep sink or you change it out with Claude, like very low barriers to entry and switching costs, to switching your underlying model. But it could really affect, your performance or how you expect your software to behave and really hard to understand ways. So anyways, coming back to it, a company like Gentrace is. I the key light bulb moment was saying, Oh shit, this company is doing something that we had in autonomous vehicles and we spent so much time doing.

And then it was another realization. Oh shit. Everything we did on autonomous vehicles, like. Everything. Let's just imagine a world where that is how software development works for now. Every company across every product they [01:03:00] build. What does that mean, in terms of the opportunities that are going to exist, the investable opportunities?

And I don't have the answer. I don't know and a lot of companies obviously are getting funded and infrastructure and testing and eval. So that space is starting to get crowded. I don't think anyone's really brought it all together in a great way, or maybe solved it for niche use cases, which is what we were talking about before.

You may not have to build a horizontal platform that serves everyone everywhere. But if you can really go deep on an audience. That is trying to bring, AI and LMS to a more conventional, software paradigm. There may be a vertical play there where you're not just solve that use case, but then you build the software development platform that.

Can enable those applications in those use cases to actually scale well for them without a lot of maintenance and engineering effort. So I know I went deep on a specific opportunity there, but [01:04:00] that's the type of thing that I'm looking at.

Shaherose: You really. Are making me think that we're challenging first principles, right?

Like how we're going to work going forward. Of course, we know AI is augmenting that, but the framework has changed. It sounds like how we approach software to your point in this AI world is, it's so interesting to hear that it was really like the way you did. Autonomous vehicles, right? The sensing, the determining, the predicting, and then the executing is, I love that.

Shalin: What a very cool insight to share. And what a time for you to be building. I'm super curious if you think about your time at Uber just going back again one more time, like an AI was where it is today. What would have changed? We probably wouldn't have hired as many people as we did. It's, I think about that actually because I'm also thinking about logistics and your question of, like how things if you're starting from scratch, [01:05:00] really, like, how would you do it differently?

It's a fun thought exercise. And I think there's the. conventional answer of saying yeah, we'd have fewer software engineers. You'd have more nimble teams like the canonical two pizza Amazon product teams, but maybe you can turn it into a one pizza team and build a really quickly and, go.

It supports it's engineering and development that keeps up with the pace of the business, which is super cool. Now. What's the non obvious thing? Here's a fun thought exercise. Could Uber have launched in a new city without ever having hired a single ops person on the ground in that city with AI?

And that's, I feel such an interesting provocation. Because what does that mean? To launch a new city? What do you have to do? You have to figure out a where's your supply coming from? [01:06:00] How are you going to basically hire drivers? And initially, the way Uber launched was it fixed supply. It would actually keep drivers pay them by the hour to just be online on the Uber platform.

And then over time, once density of demand came in, they could shift to more like dynamic sort of supply model and contractor based, a dispatch based model. Okay. How would you find drivers? And the old way of doing things, you'd actually run marketing campaigns, you'd post things on Craigslist, you'd, put flyers out, you'd literally talk to people who are working for cab companies and call them up and say, hey, come over to, I'm doing a recruiting event for Uber, we'll give you a, what if you can completely automate that with AI?

And actually do the marketing, do the outreach, do the interviews, do the onboarding, do the background checks and all the steps with AI and the SAS tools are now being built to enable you to do that. Or you could just get Claude to, to code it up, to do some of that yourself.

Where do I put, an operation center? How do I now [01:07:00] do demand incentives and demand generation and market and find, let's say university students and colleges who might be willing to like moat this in their things and this and that, how do I figure out the right people?

To reach out to in the first place who could be the data is now there. It's now starting to become accessible to an AI brain that could conceivably get you to launch a real tangible physical operations driven company in a place you've never operated before. And that I think is a pretty wild, pretty wild thought.

And that's coming back to logistics and, that whole industry. I think it, it changes an assumption that is a huge one.

Shaherose: Wow. What a future we are moving to. I, yeah, this, just this year is going to be really interesting. And I know the timeframe is short, but things are moving so fast.

Let's wrap on two [01:08:00] questions. Would love to know tangibly, what are some AI tools that are supercharging you either personally or professionally?

Shalin: Yeah. I have subscriptions to all of them. And then part of that is, because all of them have value. And then part of that is I want to just make sure I'm on the latest and greatest.

So I use the various tools for different purposes. Perplexity is great for, it's now become my new Google search replacement. So now default in my browser does perplexity searches. And that's great for just like up to date, information. Claude is great for software programming and coding.

Open AI is great for things that need more of a human element to it, or, natural language, type kind of conversational piece to it. Cursor as a product manager, software engineer, trying tinkering and five coding, perhaps cursor has been game changer. I know everyone says that.

So I'm not saying anything new here. But I do encourage if you know anyone who's listening hasn't used [01:09:00] cursor to do it. You may feel intimidated because it isn't IDE, there's probably a lot of UI paradigms for how Cursor, what it does well, that are interesting to learn from and applying it to other areas.

Loveable is something that I've used every now and then I'm looking for a really good tool that can convert a natural language prompt into a beautiful, contemporary, sleek mock or website design.

Honestly, no one does this super well yet. I'd cherish to hear Shaherose. If you have any, tips, no, I'm looking for

Shaherose: the same.

Shalin: Okay. Loveable got as close. to that for me. Frankly, and so what it is, you just type in a natural language prompt give me a design for a search tool that can, give you results and, provide profile data.

And it'll then spin up basically the code, it'll serve it, on a server, and then you can view it. And frankly, I don't care about actually deploying the [01:10:00] service, I just want to take that design. And then feed that over to cursor to be like, Hey, implement this. And so I've literally done this is a hack of taking the lovable output, brought it over to cursor, copy and paste the image and told cursor implement this.

And then it figures out in the code how to recreate that design it just saw and it's not half bad. But chain together a couple of those tools. So yeah, those are the few of the ones at least from a product standpoint. And then I'm just trying to build something that solves the problem for myself as well.

So hopefully this time in a few months, I can talk more about it and get everyone to use it.

Shaherose: Do you want to talk about it now?

Shalin: Let's just say. LinkedIn search doesn't work for a lot of people who want to stay better connected with people, and I am really passionate, especially in the AI world we're living [01:11:00] in.

That we're still able to foster authentic, meaningful helpful relationships with people, and the people they know, and that core power. Of your 1st degree network, I believe is an insanely untapped resource that with search better search and with the state of the tech can do a much better job at tapping into, but even more, it's not just about search. It's about getting things done. It's about, hey, I have a question. How do I'm in a really confusing time. Let's say in a product management role. How do I manage this work decision? Or how do I deal with a conflict? Or how do I think about a person I want to recruit? But I don't know exactly what the job description should look like yet.

And yeah, you can go to an LLM for stuff like that. But there's also just this wisdom That lives in your first degree network and in within your first degree [01:12:00] network people you really trust. It's crazy that you and I went years without talking, and I feel like I missed out on so much learning where I could be like, Charo's I'm actually considering an angel investment in this startup.

What do you think, but I just didn't think of you in that moment. And so I think there's an opportunity to bridge that, given my today context, who in my network can I can help me out and then get it done? And that makes your relationships better with people you care about. It uncovers relationships you had, but were latent, like the one we had that gets reinvigorated.

I think it'll just enable you to make better decisions, move faster be the best professional you can in this very confusing world. So that's what I want to go after without going into the details and I'm super passionate about that. I plan to start something in, in this space. if you're [01:13:00] interested, talk to me.

I

Shaherose: love this. I love this. This is a problem I've experienced my entire career, right? Even before I was investing, I was always helping founders and always trying to make the connections that would unlock a new customer, a new talent hire, a new investor. I was always running up against the garbage that is the search on LinkedIn.

And I had to create my own list of people with my own keywords to, to remember, to, that's why I remembered you when I reached out to you and the amount of time I spent like looking through lists that come from LinkedIn that lead to no value, my hair went gray in that journey. So thank you for building this.

I do agree in this Changing fast world authentic relationships that can generate value that wouldn't possibly be possible without the connection are really something people would value right in this world. And I'm excited to see where you go. [01:14:00] Come back and update us. We'd love to see you.

Let's wrap on. Where can people find you online?

Shalin: So I'm on LinkedIn for all the all the talk I did about how bad LinkedIn search is. You can find me on LinkedIn. That's probably the best way to get in touch. And I have an ex account that has been lying dormant. But now I probably have to reinvigorate if I get back into the startup game just to maybe not dude.

To jujitsu with other entrepreneurs and my email, Sean Montrey, S H A M E N T R I at gmail. com.

Shaherose: This was amazing, Shaleen. Thank you for spending time. I had a blast.

Shalin: Me too.