Dr. Jeremy Weisz: 16:13
It is interesting. So like a restaurant, they can kind of look and actually will help their business maybe staff up.
Sanish Mondkar: 16:20
Exactly. So if I ask you a simple question, let’s say you were running a restaurant and I tell you, hey, you know, I’m going to tell you exactly how many people are going to come in into your restaurant next week. And I’m going to also furthermore tell you exactly what they’re going to order. And now you would be like, wow, with that information, I can create a very efficient labor Labour plan, right? I know how many, how many cooks, how many, how much waiting staff, how many, you know, people at the host positions and how many openers and closers and at what time and how when they should be coming in and when they should be leaving and things like that
So predictive capabilities of AI is a game changer for these businesses, because now you can predict exactly how many, what your demand for labor is going to be. And once you set the foundation, I need so many people now you feel very good as a business about saying, okay, I know how much I’m going to spend now. It’s a matter of allocating the shifts to people. Let my employees pick the ones that match their preferences. So now it’s a win win for both, right?
That’s an example of it’s you have to look at it from both sides. Ultimately our customers are running a business and labor tends to be very high on their PNL because these are labor intensive businesses. So they’re, you know, getting them to be less cost conscious is not possible. We just have to help them be more efficient. And in return, they would basically extend that to also employees and giving employee choices and things like that. And it creates a really good both culture and operations into these businesses.
Dr. Jeremy Weisz: 18:03
Sanish, what data do you need to compute that with your AI? Because I imagine, are you integrating with their payment processor or something like that? You are.
Sanish Mondkar: 18:12
Yeah. So we get so when you think about so it depends on the industry and depends on the business. So for example in quick serve restaurants a lot of it is kind of items and and and and guests or customers. So if you get their historical data from their point of sale for example, now we can basically we automatically generate these AI models that learn from this historical data set and predict the future for the next, you know, several weeks, because that’s generally the scheduling window. And furthermore, over the years, we have become very sophisticated and accurate in that regard.
Now we can also, you know, discern the impact of weather on the business, the local events, school calendars, other other factors that influence the traffic into a quick serve restaurant. For example, one of our customers, you know, they were struggling with properly allocating labor, you know, to the point of demand. And we applied demand forecasting and they and, you know, the impact of something like rain or weather is different in different locations in, in some of their locations, they had a much larger sort of seating area and when it’s, it’s and there were a lot of foot traffic outside when it’s raining, people would actually step in the restaurant and buy more things in a different location. They had less of that and people were just, you know, just continue driving and not stop because the weather was, so it really depends.
Dr. Jeremy Weisz: 19:57
I could see Cinemark, we talked before we hit record. Cinemark would be one of those. If it’s raining outside I’m going to go to a movie. Yeah. How does Cinemark use you?
Sanish Mondkar: 20:06
I mean, same. All of the above. Demand forecasting is so foundational for accurate and efficient workforce management in Legion scheme of things that almost all of our customers choose us because that’s one of the value points that they see, of course. And all the employee, you know, goodness and employee engagement and stuff like that. But it starts with an efficient foundation of forecast. Once you forecast as accurately as possible, now comes the next layer of the cake, which is okay. Now let’s figure out how much labor you need to meet that demand that you forecasted.
That’s another AI powered optimization process where you say, okay, here is the right amount of labor, not too much, not too little, where you can optimize employee skills to getting those things done. Then comes the third layer of the cake, which is let’s generate a schedule. The schedule actually then specifies who goes where, when, at what time in that process. That’s also AI powered. In that process, we take into account a very broad spectrum of attributes like employees where where do employees want to work?
When do employees want to work, their skills, their productivity, their positions, all of that stuff? Excuse me. So you can see how this builds out to be something that is super effective for business and the labor cost, but also gives a lot of value to employees in terms of how, when, where they want to work and really elevates their experience.
Dr. Jeremy Weisz: 21:35
I want to talk about Philz Coffee because you have an interesting start to this journey. Can you talk about the influence of Philz Coffee?
Sanish Mondkar: 21:44
Absolutely. I think it was, you know, for all entrepreneurs, I say choose your first customers wisely because they are going to be and don’t and don’t. And when I say wisely, what I mean is don’t go with the easiest customer. Really think about which is the customer who’s actually going to stretch you the most in the right way. That is consistent with your vision for the company, right?
And one of the first conversations I had with Jacob, who was a Founder of Philz Coffee, was I remember it very, very clearly, like it was yesterday. I kind of gave him a pitch. I didn’t have anything at that point. No product, no team.
Dr. Jeremy Weisz: 22:26
What was your pitch?
Sanish Mondkar: 22:27
Yeah, just walking around drinking coffee at Philz Coffee. Right. And I met him and I said, hey, look, I want to build. I want to rebuild scheduling and workforce management in a way that employees feel like is the best schedule they have received.
Okay. And as if they’re working for the best manager they’ve ever worked for, who’s creating a personalized study for every single one. And while we are also making sure there’s automation in how that schedule gets generated and what’s in that schedule. So it was a very sort of broad picture at that time, but it had the right elements in it that employees would, would, would really kind of benefit from this. And, and I remember Jacob said, okay, you know, he thought about it for like a couple of minutes.
And over the years I realized that what Jacob style of, you know, there’s a lot of intuition. Right. That he kind of puts to good use and he said if you build it, we will use it. Okay. Which I thought was like I was like super happy. I’m like, wow, this is wow, that sounds easy.
Dr. Jeremy Weisz: 23:39
But then you said if you built a rocket ship, I’d go on it, but you still got to build a rocket ship.
Sanish Mondkar: 23:45
Exactly. He said, but he has two conditions for me. One is he wanted me to build it in his headquarters, like so. Basically come to the office and work. Right? Which I thought was actually fantastic. Maybe he didn’t mean it. Maybe there was a hurdle in his mind. But for me it was like, wow, this is great because I’m also looking for office space.
Dr. Jeremy Weisz: 24:07
You’re giving me an office? I’m there. Yeah.
Sanish Mondkar: 24:10
And he said, and you’ll have to train yourself as a barista and do the job and that was you know, I didn’t honestly I didn’t I was like initially I was like, how hard can it be? Right? Well, it was super hard. It was very, very hard. It was five days of very intensive training and, and I don’t think I ever became a good barista.
Honestly, I wouldn’t drink my own Philz Coffee, so. But it was. It gave me real appreciation. And Jacob was absolutely right. It was a real appreciation for, hey, if you’re going to solve a frontline worker experience problems, you better step into their shoes and develop the empathy and and make it real.
And I think those types of experiences really set the foundation. And then as we started building the platform, Philz gave me seven locations to work with to pilot my capabilities and the AI powered scheduling and things like that. And I would go to all six of the seven locations every week. One of them was in SoCal. So we would go like once a month.
I would spend a lot of time with managers and watching them build schedules and the amount of hours and pain. Most managers really care for their employees and they want to make sure the schedule is right. But it just was so hard. So it was really good to go through that. Several months of working very closely with one customer, we said no to others at that point because we really wanted to focus and the team was very small, but that was the foundation and I don’t think we have really, you know, looked away from those core values that we learned during that time.
Dr. Jeremy Weisz: 26:00
How long did it take from start to creating the product and actually charging for it?
Sanish Mondkar: 26:08
Yeah, we created a product in about six months. But I would say it wasn’t great. The first version of it we were and and I and the way I know it wasn’t great was because I would go and meet every manager and watch them use the product and sometimes they would be polite about things. Oh no. I’m like, no, no, no.
If you don’t like it, just like, you know, you don’t have to hold back. And so we iterated on that. For another, I would say 3 to 4 months. So by the time we launched nationwide with Philz, we were, I think I want to say in month ten or month 12, something like that about roughly speaking, a year. Yeah.
Dr. Jeremy Weisz: 26:49
And then at this point you’re focused on Philz and not any other. At what point do you decide, okay, we’re going to go out and you’re perfecting the product with Philz obviously launching it. What point do you decide okay, we’re going to go out and do some business development and get more clients?
Sanish Mondkar: 27:06
After we launched nationwide with Philz. And I know that’s not always the conventional way of doing it or the right advice even, but this is a complex product to build. And we thought we were fortunate to find and partner with someone like Philz where we saw eye to eye with the ultimate vision, and we felt like we had to see this through before we basically distract and refocus ourselves.
Dr. Jeremy Weisz: 27:35
Yeah. How do you decide on pricing?
Sanish Mondkar: 27:40
There is some precedence that was set on pricing before with workforce management. So we sort of adapted to that. And over a period of time it was a lot of experiments, customers giving us feedback. Very large customers would want sort of volume discounts and so on and so forth, which makes sense. Now we are going through at this point in the life of the company, we are going to interesting pricing experiments with outcome based pricing with AI and, and, you know, seat based pricing, which is more traditional SaaS.
Dr. Jeremy Weisz: 28:12
That’s traditional like seat based if someone has X number of people on it.
Sanish Mondkar: 28:17
Exactly, exactly. So that’s what the industry is used to. So we want to kind of definitely start there. Right. But as we evolve and as we become more and more outcome focused, I think the industry would is definitely developing an appetite for outcome based pricing, which personally we welcome because we think that’s ultimately how all software should be judged early on.
Dr. Jeremy Weisz: 28:42
Do you decide, okay, I’m going to fund this thing or am I going to raise money? Or do you just charge someone like Philz ahead of time and give him a great discount for funding this thing?
Sanish Mondkar: 28:56
We ultimately I mean, initially I was looking to fund at least to a point of time, and I started funding it. But very soon I realized that, you know, there were firstly, there were some amazing investors who I met who were providing a lot of value, like folks like, you know, Maynard at WIN Labs and Ross Fubini at XYZ. They were, you know, I would say 99% of the conversation with those folks when it wasn’t about investment or money, it was about just advice and strategy and product ideas, and those types of things. I was getting so much value out of those conversations that when it came to, hey, do you want to invest in the business? It just was such a natural question and an answer that we didn’t like.
There wasn’t like a pitch deck and I’m pitching and showing business plans and stuff like that. And I hope like especially early stage entrepreneurs, they all get to experience something like that because that was I thought it was very impactful. And it almost like didn’t feel like an investor entrepreneur relationship, but like they were more like partners. Right? So and I got a lot of value.
And Ross is still on Legion’s board after all these years and, and, you know, kicking ass with his own XYZ Ventures and stuff like that. So. But that’s so, so long story short and ended up doing seed round. And then series A and series A was with Norwest Ventures and and from that point onwards, it definitely the focus was on starting to scale the company.
Dr. Jeremy Weisz: 30:43
What did the team evolution look like? I mean initially it’s just you and then, who do you hire early on?
Sanish Mondkar: 30:52
Still me. No, I’m just kidding.
Dr. Jeremy Weisz: 30:53
Yeah, right. I know you’re a computer science genius, but not that big of a genius, right?
Sanish Mondkar: 30:58
This is all the team. Actually. One of the things that was. I don’t want to say it’s unique to Legion, but somewhat not. It’s a little bit uncommon is I was I was a solo founder, but that enabled me to hire some incredible people.
And really basically from my standpoint, all the early employees were like founders and I treated them. And especially you can see Gopal there he was the first hire. I worked with Gopal in my prior life. Incredible technologist. Employee number one, for all practical purposes, co-founder of Legion. So that just allows, you know, having that situation allows me to think about, you know, there wasn’t this magical line between founders and then everybody else. It’s like, hey, everybody else working in the company, especially at an early stage, you are all going to shape the company in a way that’s no less than a founder. And from my standpoint, hiring the caliber of people that also would be no different than the only reason why they were not founded because of timing. That’s not their fault.
That’s just where, the point where we met each other. So I’ve always kept this perspective that founders are not special people or anything of that sort. They’re, you know, your goal is to always or said differently, your goal as a CEO is to always hire founders and people who can basically take the company forward, have the ownership mindset and really make an impact.
Dr. Jeremy Weisz: 32:50
Sanish, one of the three things you mentioned which is the trifecta, right. Why are people leaving or staying is, you mentioned the, you know, the instant pay, right? At what point do you integrate that feature and how does that work?
Sanish Mondkar: 33:06
We integrated that about two years ago. And so that was fairly recently. Yeah. Fairly recently because getting workforce management right, both from an employer and employee standpoint was goal number one. And that that definitely takes. I mean, that was a substantial surface area to cover.
Instant pay is something we added recently, and it’s been amazing from a user adoption standpoint, from a value end user employee value. It really completes the thesis in many ways. Of course, there’s a lot more we can do, but the foundation of employee value for frontline workers, as I said, you know, schedule empowerment, modern experience and on demand pay. Those three things are now in the app. And we just see extremely positive results from the employees with this.
Dr. Jeremy Weisz: 34:08
How does it work? I mean, is it, do they just, yeah. Do they just?
Sanish Mondkar: 34:12
Yeah, their shift is over, assuming they’ve signed up for instant pay which they can do with from the
Legion, excuse me, mobile app. After the shift is over they can go to the app and they can draw a portion of their pay. Some portion is still left for the pay day for taxes and garnishments and things like that.
But they can draw a good portion of that. And there’s a small fee for same day and it’s free for the next day. So depending on how urgent it is, our cost structure is different for that. So there is a free option if employees want if they can wait until next morning. And we see employees use it all the time and employees use it for for all kinds of things.
Emergency situation, not an emergency situation. Our longer term thesis on that is I think pay ultimately is going to be especially for shift work is going to be shift based and not payroll cycle based. So we are basically, you know, shifting our employee experience in that direction.
Dr. Jeremy Weisz: 35:21
Yeah, it’s an interesting feature. Did that come from just talking closely with employers or more employees?
Sanish Mondkar: 35:30
Employees, employees in when I remember so 3 or 4 years ago in our employee surveys, which we do broadly, not just Legion customers like you’ll find that on our website. It’s State of the Hourly Workforce. We publish this research report every year. And. I want to say about four years ago, this one of the questions we ask is besides pay, what are the reasons that would make you choose a job or leave a job?
Yeah, that’s exactly right. That’s the report. And I encourage everybody to download it. It’s got a lot of great information in there. So about four years ago this instant pay showed up as a little blip on that.
And every year we’ve watched it grow significantly. Now it’s like 40 something percentage of the reason why frontline worker would make a leave or go decision. Right. That is massive. And when you combine that with skill and empowerment and other things or the trifecta as I called it, that’s over 90% of the reason why an employee would stay, stay or leave.
So these are things you can actually incorporate as a business. You can incorporate these things into your kind of your, you know, employee employee technology suite and really see great value.
Dr. Jeremy Weisz: 36:56
We talked about AI of course, and AI is built into you know, there’s a whole Legion AI page, of course, but talk about the impact of AI in brick and mortar specifically. Right. Because they’re not sitting in a desk like you and I, you know, always at the computer. How does it impact them?
Sanish Mondkar: 37:14
Yeah. So it’s a great question. And we spend a lot of time thinking about that because that is our world of customers and that’s our market. And that’s also, by the way, happens to the majority of the employees out there in the world. It’s over 2 billion, you know, deskless workers.
There are multiple areas of applicability for a brick and mortar business of AI. And I think my advice and recommendation to operators in brick and mortar businesses don’t be on the sidelines. Don’t think this is for technology industries or knowledge work and things like that. You can benefit a lot from AI in the following manner. One of the things we talked about was the predictive capabilities, right.
So just predicting demand for labor, predicting when your customers are going to come in, predicting who is going to buy what. All these things are possible to do today with AI with a very high degree of accuracy. And that just establishes the right plan that you can build for your labor, for your customers, for all that stuff. So that’s number one.
Number two is when you think about optimizations of schedules and making sure each employee is personalized. That’s a lot of permutations and combinations, right? If you got a roster of 30 people in your store, which is a very small store, in the scheme of things, you could have over 250,000 permutations of how you can create a schedule, right? Especially if you want to cater to your employees preferences. So you can easily do that and fully automate that with AI.
But now with generative AI, there is a whole new possibility that did not exist before. Keep in mind all these are deskless workers. In other words, they’re not sitting in front of a computer, as you said, and looking at software programs. And guess what? They don’t want to. That’s not their job.
So how do you engage with this deskless workforce and enable them to do complex things in software without being in front of that software all day long. That’s the world of generative AI, and LLMs have really opened up very high caliber, high quality and effective agentic framework for conversational interfaces for doing all these things. For example, a manager on the go can receive a nudge from an agent saying, hey, Joe is going to be late for the afternoon shift. Do you want me to reassign the shift to somebody else? Yes. Go. Yes. Reassign it to somebody else. Should I pick somebody or do you have somebody in mind? Just go pick somebody.
Like that type of stuff without going back to the desk, without going to a device, without going to a phone and doing all these things, but just being so conversational, but yet being completely in control of the operations on the floor. Those types of possibilities did not exist before this effective generative AI and LLM capabilities that we are seeing now. So that really rounds up the AI potential in workforce management beyond predictive capabilities, beyond optimization capabilities to now these capabilities that really can assist every single worker and persona, whether it’s a manager or district manager, an employee, a cashier in new ways that they’re not that did not exist before.
Dr. Jeremy Weisz: 40:43
I’m curious, the buyer behavior. Yeah. Because you have some big customers on here. Do they typically go, Sanish, yeah, we’re going to try this at one location, then we’ll do two, then we’ll launch across. Like how do they normally say they want to integrate Legion?
Sanish Mondkar: 40:59
It’s a great question because that is the biggest hurdle. Honestly it’s adoption and change management ultimately. A majority of the operators in labor intensive industries are not known for being on the cutting edge of technology.
Dr. Jeremy Weisz: 41:18
They’re like, let’s change everything. Give us more work. Right.
Sanish Mondkar: 41:22
That’s exactly how they don’t think. Right. So it’s our job then we I mean, what does that mean? It means it’s our job as technologies to make sure what we are building has that adoption in mind. I’ll give you a great example.
When we first started creating automated scheduling, the first incarnation of that was click a button. Here’s the schedule. And managers would be like, I don’t think this is the right schedule. I don’t like this. I don’t like that. This is not how I would do it. I don’t think Joe should be working at 9 p.m.. Why not Jane? And then we realized, well, well. And we had an answer. We were like, explain. Like, well, no, but this is what data shows. This is what the input is, what the AI.
But the real problem was automation lacked explainability. We needed the managers to understand the why and explain it. And explainability and transparency builds trust. So we started evolving our application UI design to constantly talk about. If you want to know why the demand forecast is higher at 2:00 pm, you can click here. If you want to know why this person got assigned this shift here, you can click here. If you want to know why 394 hours of labor were allocated for Tuesday, and not 395. Yes, you can slice this in this way.
So over a period of time, like and this is part of the burden and the opportunity for all AI builders right now, it’s at least in the phase of adoption that we are in right now. Maybe this would be different three, five years from now where it’s just well understood. AI is always producing the right results. But for now, two things are important. One is explainability and also to get the input back from the managers. So if managers say, yeah, I understand this, but I still don’t agree, I’m going to go ahead and make a change to the schedule. Then we gotta learn from that because there is something that is being instructed back to the AI engine.
So this cooperation between the human and the AI, in context of a workflow and the explainability of why certain decisions are being made, goes a long way in driving adoption. And we’ve seen this through a massive amount of volumes of data that we’ve got, and now we just have a point of view of what drives user adoption.
Then there’s also a different problem what drives a company adoption. And that is basically, you know, to exactly what you said. Most of our customers want to start with a smaller set of locations. They want to refine that, try it out, and then they scale up from there.
Dr. Jeremy Weisz: 43:56
Sanish, whenever I’ve gone against Waze in my directions, I’m like, oh, that’s not a good way. It was a mistake, actually. I should have just listened to Waze. But people have certain tendencies and things they like. And, you know, I think sometimes Waze is incorporating more things than I know. So I’ve learned to mostly listen to Waze, so maybe you know. Same thing with your software. Like, okay, I don’t know, maybe I would do it this differently, but it’s spitting this out for probably 17 different reasons that maybe I’m not seeing.
Sanish Mondkar: 44:27
Indeed. Exactly.
Dr. Jeremy Weisz: 44:30
You know, so what was a proud moment? You know, Philz was obviously a proud moment from a customer perspective. What was the next major milestone of a customer that like, oh yeah, they gave us a chance?
Sanish Mondkar: 44:43
Yeah, I would say in the early days, Dollar General was one of our first largest enterprise customers out there. They are I mean, they are one of the largest employers in the country. They’re well over 180,000 employees, I think well over 18,000 locations at this point. So to take on a customer like Dollar General and they operate like they are nationwide, truly nationwide, they are in small cities.
Dr. Jeremy Weisz: 45:11
I mean, every small town I’m in, there’s like a Dollar General.
Sanish Mondkar: 45:14
Exactly. And to take a customer like Dollar General and have, you know, at that scale, size.
Dr. Jeremy Weisz: 45:24
Who makes a decision at that type of company, who’s deciding? Let’s take a look at this. Like what type of position?
Sanish Mondkar: 45:31
Yeah. There’s generally a combination of people. Right. There’s oftentimes maybe one sponsor generally that maybe in retail store is head of retail ops or with, you know, in collaboration and partnerships with the CIO or because it’s such a big technology transformation tool. Leave aside the business process transformation.
And oftentimes and more recently, we see the chief people officer or CHRO being big part of Legion decision because it has such a positive impact on the employees. So that’s sort of the three most, you know, engaged C-level personas. But within those three I think operations generally takes the lead. Okay.
Dr. Jeremy Weisz: 46:22
How do you get a conversation with Dollar General?
Sanish Mondkar: 46:25
So most customers buy this software, this category of software through very thoughtful RFPs. It’s not ad hoc. It’s not you know, they would have sometimes you know ten chapter with.
Dr. Jeremy Weisz: 46:43
They said we’re in the market to switch. They’re in the market.
Sanish Mondkar: 46:46
Exactly. Yeah. There is an impetus to switch that generally comes from within, because they may be running on older technology or inflexible software or no automation and things like that. At least larger businesses buy that way. Now, there are sometimes smaller businesses or midsize businesses who would be opportunistic and pilot something and then make a decision to replace.
But it’s generally a thoughtful RFP and RFP process for larger businesses can go on for months. And they evaluate every single thing like software, your credentials, reference ability, you know, enterprise readiness, all security certifications, all those things. And that just goes to say how much this platform matters to the customers.
Dr. Jeremy Weisz: 47:37
Yeah. No, it’s interesting to see the journey here. You still must have customers that come to you because they hear about it through another brand, I imagine.
Sanish Mondkar: 47:47
All the time, yeah, all the time. I mean, one of the most surprising things for us was customers hear through other customers, and then we dig in and then we realize there’s employees who have gone from this to that, and they have said.
Dr. Jeremy Weisz: 48:02
Oh, that makes sense.
Sanish Mondkar: 48:03
Upwards. And that’s just so great to see.
Dr. Jeremy Weisz: 48:06
So like, I want instant pay. And like, you don’t have it here.
Sanish Mondkar: 48:08
Exactly like I used to work in this company. And they would let me on my schedule and pay me instantly after the shift. And this your place doesn’t do that. Like, why don’t you talk to the Legion people like that?
Dr. Jeremy Weisz: 48:21
There’s a certain cool virality to your software, right? Because if you have 180,000 employees in like you said, there’s going to be turnover, they’re going to go to different companies. That’s like the best type of virality. Then you have, who knows, like 18,000 people a year going to a different company. And you know, send them t-shirts.
Sanish Mondkar: 48:41
It’s the silver lining of turnover.
Dr. Jeremy Weisz: 48:42
Yeah. I mean not that you want turnover, but whether there’s not or there is, I guess either way you win in a sense. You know, we just have a little bit of time left. Sanish, first of all thank you. I’ve one last question.
I want to encourage people to check out Legion.co, as you saw. You know they have some great resources. Obviously you know the State of the Hourly Workforce report, you can check it out and other things on their resources page. You know, my last question is just some of your favorite resources. It could be books, podcasts. It could be business or health. I know you, I’ve heard you talk about health and longevity and David Sinclair stuff, so I’d love to hear some of your books, podcasts that I should check out and other people.
Sanish Mondkar: 49:32
Yeah. Well good question. I’m still into mostly those topics. I mean, there’s AI is drinking from the firehose right now because it’s evolving so quickly and it’s exciting, but it’s also sometimes overwhelming to stay on top of. And you feel like you don’t read for five days and you’re already like falling behind.
So that is always hard to keep up. But there are, you know, podcasts like Dwarkesh and others who are, who are just absolutely amazing in the knowledge that you gain. Health is longevity and, you know, topics like that. For me, it’s more of casual reading now because I’ve kind of gained, I would say, sufficient knowledge at least to kind of take care of myself. And now it’s more about, you know, just being disciplined and trying to, you know, put that in practice, which is where sort of the problem statement has shifted. But it’s always fun to read about those things.
Dr. Jeremy Weisz: 50:36
And are there any like, thought leaders on the health front that you like? I know you’ve, I’ve heard you mentioned David Sinclair.
Sanish Mondkar: 50:41
I think David Sinclair is still like the top to me. But there are others. Yeah. I can’t think of some names off the top of my head, but some.
Dr. Jeremy Weisz: 50:53
Of the recent books I’ve listened to is Dr. Mark Hyman had a book that just came out. Dr. Peter Attia also had a book on health and longevity as well.
Sanish Mondkar: 51:03
I was gonna mention Peter Attia because he is fantastic. His advice is so practical and doesn’t require you to go and buy a thousand supplements, which is good. You know, it’s just, hey, stay healthy, stay happy, have good friends, you know, like that, that type of stuff which is awesome. Yeah.
Dr. Jeremy Weisz: 51:25
Anybody on the business book or leadership?
Sanish Mondkar: 51:29
For me, I’m at the phase right now where I learn, I attempt to learn, would be a better way to phrase it a lot from our customers’ businesses. I make it a point. It’s and it’s also fun. And I encourage that to all entrepreneurs. Can you and you know, sometimes you may have like thousands of customers and it’s fine, but you can still pick the the of a set of customers. But are you able to understand their businesses and break it down like an analyst would, or like a, you know, like a, like a board member would.
And that oftentimes gives a lot of insights to opportunities for your business. But even if it doesn’t, it’s just a great skill to develop, to be able to look at a business, look at a 10-K, talk to some business leaders, understand the priorities, map the two and and really have a have a good point of view on what’s going on in that business and where they’re going.
Dr. Jeremy Weisz: 52:33
Totally. Sanish, I want to be the first one to thank you. Everyone, check out Legion.Co to learn more and we’ll see everyone next time. Thanks so much.
Sanish Mondkar: 52:41
Thanks for having me. It was fun.
