Zach (00:00:01) - Here's what I am going to offer to you. Here is what I expect in return from you and have a conversation around the process. And then it's super clear that people can hold each other to it. And you're not confused if people are happy with your work or not. Like it makes it much, much more clear.

Ariana (00:00:20) - Welcome to Secret Ops, the podcast uncovering the world of operations, one episode at a time. I'm your host, Ariana Cofone, and today's guest is Zach Rattner, founder and CTO of the company Yembo, which is an AI enabled virtual property inspection technology company. We're talking about the future today, y'all, and how AI is able to help real life problems that humans are navigating. And in this case, how do you quote out a move whether you're moving offices or you're moving homes, how can you easily be able to understand what's in your room and how much that's going to cost you to move? So we dive into a lot today, and Zach is really great at connecting the dots between technology and human applications.

It's also been really interesting to understand his journey into growing as a business and all of those yummy lessons along the way. So I really learned a ton from Zach and I hope you do too. Let's jump in. Zach, thank you so much for coming on Secret Ops. I'm really excited to talk about your journey into your career because you are a very curious person, and it's led you down a lot of very interesting paths. So why don't you kick off with just telling us about your journey through your career and how you created Yembo?

Zach (00:01:48) - Sure, Ariana. First off, thanks for having me. So my name is Zach Rattner. I'm the co-founder and chief technology officer at Yembo. We're a computer vision company that sells AI tech to home services. It's an industry that traditionally has been under-technology-utilized. And I've been a software engineer my whole career. And I would say I get bored relatively easily. So I've had a lot of time to kind of dabble around and focus on different areas on the tech stack. So I kind of paid for college working as a web developer, then wanted to go super low level. So I found a job where I could write really low level C-code, working at a company called Qualcomm, where I was working on the code that goes on the chip in your phone that talks to the cell towers. So when you’re going down the highway at maybe 70, 80 miles an hour, you'll go out of range of one tower into range of the next one. And there was a team of about 25 or 30 people or so whose job was to make you not drop the call.

Ariana (00:02:51) - That is insane to me that like, there's a whole army of people that are helping for this very human problem.

Zach (00:03:03) - And I used to joke when I graduated school and entered the workforce, I was always really excited to learn how everything works. And now that I'm about 15 years into my career, I'm kind of shocked that anything works.

Zach (00:03:18) - Like how many details you have to get right, how many little things can go wrong. It's just kind of crazy for something so basic as how many bars of service do you have? Like legitimately 30 people. It's a super complicated.

Ariana (00:03:30) - Also, it makes me feel a bit of like a brat because I am such a jerk when I'm like, man, “I don't have like one extra bar, like what's going on?” Like there's so much going on behind the scenes and that like 10s, I might have one less bar, you know, I got to check myself a little bit, I'll put it that way.

Zach (00:03:46) - But we need that though, right? Because if we were complacent, there'd be no urgency, no incentives to drive the progress. So it works out well in the end, I think.

Ariana (00:03:54) - So you need those annoying people like me to kind of keep pushing forward.

Zach (00:03:58) - We call them passionate testers. But yeah, that's helpful.

Ariana (00:04:01) - Yes, I'm a passionate tester.

Ariana (00:04:03) - So you were at Qualcomm for how many years?

Zach (00:04:06) - Is there for about five. So I did the first three I was working on that team on the signal bars. Then an opportunity came up to go work on a much smaller team focused on newer emerging technology areas. So Qualcomm was dominant in telecom. It's kind of how they made their bread and butter. But also in the process of doing that, they got really good at mobile computing as well. So things like camera processing, graphics, they were one of the first or if not the first company to cross the one gigahertz boundary on a phone. There was a lot of really interesting, cool things going on, and there was a small team that got put together that was kind of focusing on emerging technology areas and I had an opportunity to join that team and spent about two years looking into computer vision AI technology specifically. A lot of the big applications at the time were more focused on things like self-driving cars and drones. And if you think about those use cases, they can't really be connected to the cloud. They have to be sitting on your device. Right? Like if a self-driving car needs to phone home to see if there's a pedestrian in the crosswalk and you're in a rural area with no cell connectivity, that's an issue. So there was this big push to like, look at on-device AI and kind of learn more about that space. And my wife was working at a moving company at the time, and this was the end of the genesis of what happened at Yembo. So in my day job, I'm going to these tech conferences. I'm coming home kind of all jazzed up and energized around people who are using AI for drug discovery and self-driving cars, and my wife is telling me she worked in the international department at a moving company. A lot of things like customs, logistics work. It's much more complicated than like a local move.

Ariana (00:05:49) - Yeah, that's not that's not anything I think I would want to do. That sounds like intense, intense headaches after headaches.

Zach (00:05:58) - I think just to give an example, a typical international move, like just say like New York to London, for example, it's not unusual for there to be 40 different companies involved in that entire lifecycle of that move, because you have customs agents, you have forwarders, you have the crew at the origin is usually not the same as the crew at the destination. There are specialty things that you need to do, like if you have a piano, you have to tie the hammer so they don't bounce around and break in transit. So there are companies that specialize in just getting pianos staged. So it's super complicated. And as an Ops professional, I'm sure you know, if any one detail goes wrong, the whole thing can be catastrophic. One of the big things with international moves is they're heavy. So they typically ship on container ships. And you get a date allocated, which kind of assumes if you work backwards from that date that everything is packed, it's loaded, it's ready to go. So if you accidentally send a 12 foot truck instead of a 16 foot truck, and you can't bring all the goods back to the warehouse, there are all these downstream implications. And then you, like, you miss the spot on the boat. You have to go find another spot. And depending on the country you're going through, there may not be one for a while.

Ariana (00:07:13) - It’s making me sweat even thinking about that.

Zach (00:07:16) - But like, the whole world kind of depends on it, right?

Ariana (00:07:18) - Are absolutely.

Zach (00:07:20) - A lot of companies do a lot of international moves. If you say it's too complicated and throw your hands up and give up like the world is a much worse off place. And that was really what the genesis for the idea was that there are all these problems that come up and it's not for lack of trying. I mean, there are the best in class companies in the world in this industry, get really good at it, but it's still very labor intensive. That person can still have a bad day and it's very specialized. So it's kind of hard to hire someone right out of school and have them know all the nuances. And that's where we saw an opportunity for computer vision, because we realized there's a real will to give accurate estimates as to what's there. There's a real problem if you don't have the estimates, be accurate and there's a real drive and motivation to do better. It'll directly impact both your top and bottom line if you're in the roofing industry. If you make this process better.

Ariana (00:08:17) - That was something that shocked me. So you've got this book that we'll talk more about, Grow It Fast, that the margins are super lean in that industry. So when you have somebody that's coming to quote out the move, it is really important that they're thinking about all of those different components that are going into quoting that person. Everything from…the thing that struck me, you said, you sort of have to look at an object and not only think about the object, but what box is going to be in how much room that box is going to take, what other packing materials. So there's all these mental calculations that ultimately to be able to quote out a move, you have to have an insane amount of experience to do that, like you have to…it kind of blew my mind. I'm like, how can you, even a human being, be able to do that? That's kind of what I was thinking in my head.

Zach (00:09:07) - Yeah, it's kind of crazy. And I think on top of that, there's not always one right answer. I mean, for something like, “hey, there's a sofa, how many cubic feet?” There's a scientific black and white answer. But if you look at all the books on the shelf behind me, how many boxes will that take? Well, the answer depends on how skilled you are as a packer. I mean, maybe books are easy because they're rectangular, but you go into the kitchen and there are cups and plates. Yeah, that's my least favorite room to pack as well. The kitchen is like a nightmare for me. I'm like, no, I can't deal with it.

Zach (00:09:34) - Yeah, it's that and garages are the most labor intensive. Oh my god. But yeah. But I think the idea being it's such a tough problem because you're not just looking at something and saying, what is it you're looking at? What is the labor that it would take and the materials that it would take.

Zach (00:09:51) - And that depends on assumptions around the skill and abilities of that person. We have some stats too that show…like if you are moving yourself, like if you're renting a truck and just doing it yourself, the number of boxes that you need is usually significantly more than if you're a professional mover. Because like, I would do it once and then not do it again for five years. Someone else who does it all day, every day. They'll get better at packing stuff super tight and things like that. So, like, the right answer for me is different than the right answer for you. And it just becomes super complicated, super fast.

Ariana (00:10:22) - So how did you begin to use AI to sort of solve that really tangly problem? Because technology also has evolved a lot in the last couple of years. So where did you start with this idea, and then how has that changed over the years as AI has evolved?

Zach (00:10:43) - Sure. So I think looking back, I think there's one thing that I believe we did right at Yembo. And if someone else is looking at bringing AI into our workflow that doesn't historically have it, I think there's a lesson learned and we talk about it in the book here. But I think the basic idea is we found an intellectually honest reason to have someone use the technology before the AI gets to be 100%. Because AI, it's like a label that people put on it. But at the end of the day, it's math and it's science and it's code. And it is all based is based on probability. So you and I would maybe look at this TV and say there's a TV. The algorithms don't work that way. They'll say I'm 92% sure it's a TV, or I'm 79% sure it's a TV. And the challenges that that brings up is you're never quite certain. So we need to it's your job when you're building the software around that technology to kind of hide that detail like people don't care about. Is this a 79% lamp? They just want to know, is it a lamp? So what we did was we found a workflow where the AI initially couldn't detect a whole lot of things. Also, the data sets that we had to train the eye were, were, were limited. You had to collect it before you could train it. So that means I need to get the data somehow. So I need some reason to have somebody go through the process before I can go and make the AI super awesome. And what we found was making this in-person estimating process where I ring your doorbell, walk around with a clipboard, write everything down, taking that and moving it to a remote based process where I can send you a link. You take 15-20 second videos of each room in your house. There was value in that alone. There's saving wear-and-tear in the car. They were saving drive time, fuel costs, hourly rates for estimating, the person doesn't have to stay home from work and I'm sure you've had like a four hour delivery window when you try to order something and they say stay home from work from 12 to 4. So there were reasons to kind of fix all of that. And what we noticed was that when we did that, people were willing to go through the text based process. We asked them feedback forms, and a good portion of people preferred it, not just were willing to, but actually preferred it to the alternatives. And the movers were able to look at it and give an accurate quote. So that means I had a reason that someone would want to go through this. And then we were looking at time as our key metric. So we want to save the movers time and let them go through and get the inventory list quicker. So that's how we prioritize. I think you really do need to prioritize, because it's relatively easy to get an AI algorithm that's like 75, 80% good, but to make it really like 99 plus is a long tail. So that's why we call it the self-driving car problem, where if you look at how long people have been working on self-driving cars and they're still not prevalent today, it's not for lack of budget. It's not for lack of trying. It's just really freaking hard. So when you look at the self-driving car problem, I think that industry is kind of struggling to find that intellectually honest value prop before you can really get there. It's self driving, but keep your hands on the wheel and still sit in the car and it's kind of unclear, like, “is this, is this really saving me a ton of time?” And I'm sure it'll get better. But like the vision that we're all promised of, like a car that looks like a living room and it's just a sofa, there's no steering wheel. It's far off because you have to be like, really, really good on the technology side before you get there. So that's where we broke down the problem and we said, “okay, here's the tech process. There's no AI. Then we bring in AI, and now you're 40 minute job goes down to 35 minutes and 34 and 33”. So we kind of had this conduit where the AI could improve and learn, and the technology made the product get incrementally better.

Zach (00:14:24) - But we didn't wait and say, don't touch anything to like and detect everything people would possibly own, because then I think we just would have run out of time, it would have taken years and we would have gotten the data. So that's why I feel like finding that underlying use case where the AI can get you like 5% of the way there, 10% of the way there, and you can incrementally improve. I feel like is kind of key just based on how the technology works.

Ariana (00:14:50) - Well, you know, going back to that self-driving car vision, I want to be in the living room of the car, you know, like I really want to be there. And so when we're not there, there's like an inherent disappointment that you feel that. So even though the technology, the work that's going on behind it is absolutely incredible, it’s sort of like “but it's not this vision and that we're kind of Jetson-promised that we want this future, right?” Whereas if you realistically say we're going to work on 5% of this, then 10%, then 15%, and taking the customers along that journey, that's pretty profound, because that helps to get people to realistically understand the application of AI within what they're doing. I find the same thing in operations that can be quite hard right now, is that a lot of use cases are writing content. You know, they're more about those sort of applications. So have a lot of operators that are like, you know, how can we really use AI to help operations? And that really comes down to like the tiny things that actually add up to a lot of time in your day and good operations saves time. But being able to quantify that time-saving is very hard. Yep. How did you go about doing that? Because that is a pain in the butt. I'll be honest. It's just that's the difficult part in trying to quantify the time savings of good processes, good technology. So how did you approach that?

Zach (00:16:24) - Sure. Yeah. You're right. It is tough. And I feel like every time we felt we nailed the metric, two weeks later there was a new way to measure. We actually didn't start it on time. We started on weight. We just figured, okay, the move needs to be accurate. So let's look at weight. But then what we found was in an earlier version of her AI, we didn't have a lot of data, so we would. It's this problem called overfitting where you glom onto something and you kind of hyperbolize it and generalize places that you shouldn't. So we accidentally learned that all white panel doors are refrigerators. And just because we didn't have enough data in there, but we had this one poor person who had like a one bedroom home, maybe it should have been 3 or £4000. It was pretty tiny in terms of typical move, but every door we thought was a refrigerator, and that made the Yembo estimated weight through the roof like equivalent to like a 7 or 8 bedroom mansion. But if you trace it back, there's like one fundamental problem that happened was this is a door, not a refrigerator. If you solve that, then something that looks like how this is a joke, you're like ten X off is actually fine. So we learned that not all errors are created equal. And if you're a mover going through and looking at the results, what really matters more is how quickly you can turn that around. So I think that part got a bit easier in terms of time savings. There is a baseline of how many surveys a day you could do before. And now we look at how many surveys a day you can do now. But I would say the data isn't the end all be all. It's a means to a perception issue where if the sales manager and the sales leaders feel like they are able to be more effective, then you have good adoption, you get good retention, things like that. So I would say that the time it's not like there's one black and white hard answer on it because, I mean, we had one move that took two hours to review because the person went out to lunch halfway through. Is that really that technology is fault? Like I would argue, no. But if you're able to demonstrate that you can service jobs you couldn't otherwise because I don't have to drive out there.

Zach (00:18:34) - So I may not be able to justify getting in the car driving 200 miles, but I can estimate you in Yembo. And if you're able to give a good experience back to the customer where it's not just, I don't know, I think it's like £3,000, but you have actual photos of what's there and the client who's doing it is able to do it quickly enough that they don't feel like it's bogging them down. And you can measure that by saying, okay, you could do three estimates a day before you can do ten now. So it must be faster then I think you kind of have it. So we basically didn't really address and solve the perfectly quantifying problem, but we got it good enough that we were able to understand the overall value prop. And then that I guess we could have gone further, but there wasn't really like a business justification in doing so.

Ariana (00:19:17) - You know, that is really it's so funny that you articulated that beautifully, because that's what I run into with teams where if you want to quantify time savings, then essentially your team has to time track, right? And then we have to time track before and after, and then you have to make sure that their time tracking is accurate. If you want that really granular data or you have to track sort of user behavior on their device, right, you'd have to be able to track those things in some capacity. But it comes that point where you're like, “is this worth the effort?” Right? Is it worth people tracking every single minute of their day, or us installing some sort of device to get transparency around that? I think that trade off is also an important part of that operational mindset. Like, can I justify the time or money spent on pursuing the perfect accuracy of this thing, or is getting 80% there enough for us to say like, this makes sense? And I think that the 80% actually is where you kind of need to say, we're good, we're in a good spot. But you articulated that super beautifully.

Zach (00:20:20) - Yeah, yeah. I feel like it's common all across technology businesses. There's this myth, too. When you're running software, there's a metric that we track. It's called your number of nines. And that is what percent of the time is your software up and running. So there's four nines means 99.99% of the time it works. Five nines is 99.999. But if you look at the expectations from the customer, thanks to things like Facebook and Gmail that basically never go down, if you ever have a momentary outage, people obviously get upset, right? Because like we've embedded ourselves in their workflow, they can't get their job done. For good reason. But if you look at the effort that it takes to go from 99% uptime to 99.9% to 99.999%, it's exponential. It's not it's not linear because you start looking at like, okay, you can have one minute a month to you can have like 50s a month, you can have 30s a month of downtime. And the things that you need to do, the redundancies that you need to build in the workflow and the processes. Because servers have this devilish tendency to only go down between like two and 4:00 in the morning, and they work fine when you're around.

Zach (00:21:33) - So that extra work that you need to put in, you need to make a business decision. It's actually not a technical decision about how available is this? It's a business decision. And it's going to come with dollars. Because if you need to have like five X redundancy on everything, in case any one piece breaks, it's going to cost you more. So I was kind of intrigued by that because it sounds on the surface like it's an engineering problem, like “it's your code. How often does it work?” But if you dig into the details a little bit, it's much more nuanced. It's really an ops issue.

Ariana (00:22:07) - Well, this is something I appreciated. We did a chat before the interview and you're very operationally focused. Like even though you have all these technical skills, there's something that's very operational about your brain where you sort of are super curious. You take these big issues, you learn these new skills, you break it down into pieces and something that I really echoed with, and I guess I would love to kind of go into the trifecta of people, process, technology just to get sort of your pro tips because you're coming from such a unique standpoint. So let's start with process. When it comes to process, what are some tips that you've learned along the way to really get the biggest bang for your buck when you're building your business or you're working on your technical stack, where would you put your effort when creating process?

Zach (00:22:58) - My views on this have evolved over time. As a young, curious hacker kind of engineer, I would say it's a waste of time. Just get stuff done. Then as I've advanced in my career, I've learned that not having process will impede your ability to get things done. And I like to think I've matured a little bit there. But I think one big example that we have at Yembo is we have three, kind of, central engineering hubs. We have one in the US, we have one in India, we have one in Ukraine. And if you look at a world map and where it's 9 to 5 in those time zones, there's very little overlap. And that was done on purpose so that we can make 24 hour progress, because there's this kind of legendary Silicon Valley vibe that like startups, just the engineers just like guzzle Mountain Dew and work constantly, which maybe works in short spurts. But I mean, if you want it to be more sustainable, it's much better to crack that code on how do you make 24 hour progress? But how do you also not burn anybody out? And that's where we kind of ended up. So I think in terms of process, we had a goal that we're going for. I think it's always helpful to define what the purpose and the outcome of coming up with this process is, and what we were able to do on the software development side is we split it and we realized that there are really three main workflows that don't really need to be happening synchronously. They don't have to be getting live on calls. There's like the initial design and architecture which we do in the US. Then there's a lot of implementation work around, like writing the code, testing it out, make sure…”does it work if the iPad's portrait and landscape and Chrome and Safari”, all those details?

Ariana (00:24:35) - Yes, yes.

Zach (00:24:36) - And then there's the testing, which happens in India. So if you look at the locations that we kind of chose to set those up in, you can follow the sun and go through the workflow. And then so if you're a US engineer, you scope everything out. You have your remote team, they build it, they hand it off to India, then they test it and you wake up in the morning, you get the report back and as a result you're able to…it's probably about 2 to 3 x ish numbers of like tasks that you can get done in a release because you're not paused when people go home for the day. But I feel like having that goal of like, we want to ship more things faster. We don't want to have a retention issue with everybody quitting because they work them to the bone. And we want to make it sustainable and scalable. So if I were to like ten x the number of engineers on each team, I want that process to still work. So we kind of like listed out…we call them the Bill of rights. Whenever you have two different teams with two different disciplines, like what are the sets of expectations? I think that was a key exercise that we went through because it made it okay to talk about problems, right? If we were like starting to do something and let's say I'm writing the code and you're testing it, if we don't have a clear bill of rights and something doesn't ship on time, and then like the manager is saying, hey, where is this, like you finger point? Well, the tester didn't do it quickly enough. Well, he gave me a buggy code, but when you have the Bill of rights, you say, okay, like we're all in this together. Our goal is to ship cool software and do it as fast as we can. But there are things that we need to do to get there. As a tester, here's what I expect from you. Like that you sanity checked it on your end, that you are clear on what it can and cannot do. It's clear what the purpose is. You're not just saying, hey, test some random code. You're like explaining what it is I'm supposed to do. And then in return, I would expect a clear ETA when you can get to it. Like, generally it'd be nice to get within one business day, but if you're too busy or whatever, you're out of the office, then, like, I just want to know what that expectation is so that I'm not in a position where I've written code and handed it off to someone else, and people ask me when's it going to come? And I can't answer.

Zach (00:26:49) - So we kind of like to take some time. It usually takes like 2 or 3 weeks to start something. Then you go back and forth and you like, iterate on it. But I feel like having that crisp bill of rights around, like, here's what I am going to offer to you. Here is what I expect in return from you and have a conversation around the process. We have an advisor who calls it like having an out-of-body experience where you're not just debugging one particular problem that came up, you're just looking more holistically at the workflow. And then it's like super clear that people can hold each other to it, and you're not confused if people are happy with your work or not. Like it makes it much, much more clear and it can also change. We used to have support tickets when customers filed tickets. Initially I had an SLA around that of you have 30s to respond in five minutes to resolve which is super tight. But it made sense when we had, I think two customers and all of our bugs were like really simple things and I was the only engineer working on it. So I was like, hey, I can do this. And then as more people grew, like I said, okay, that's kind of unreasonable. We probably shouldn't be shipping those kinds of defects to production anyway, where you can fix it that quickly. And then like, we went back to the Bill of rights and we retooled it. And like, you can evolve the expectation in the process as the company grows.

Ariana (00:28:16) - I keep thinking about the people component of what you're talking about, because to be able to mature the way of working that you're doing, especially as a global team, it takes getting honest feedback from your team and then really listening and saying, “okay, I hear you like this is unrealistic or we're lacking here”. How have encouraged that feedback loop with your team to be able to understand what their pain points are, and then bring that into the Bill of rights, or bring that into how you operate. Like, what is that feedback loop that you've set up with your team? Especially considering that I love working with the global team, there's nothing that I enjoy more than working with people all over the world. But you're also dealing with cultural ways, different cultural ways of navigating potential confrontation, honesty, things like that. So what tips have you gotten to kind of figure out how to get voices heard and to implement those things within the global context?

Zach (00:29:17) - Yeah, it's not come easy. And I think every company is a little bit different. So I can tell you what we've learned and maybe some percentage of it will be helpful for others. But I feel like the key at the root, it's a culture matter. It's not just like I can't put the perfect process on paper and say, please be honest and speak up if things aren't working well, and then instill a culture where there's fear and then people don't want to speak up. So I think they kind of go hand in hand and we're relatively open, like every Slack channel is open, unless there's a good reason for it to be closed and things like that. So we're relatively open with these things. And I think as the leader, the manager, you need to be willing to kind of go first and set that culture for your team. So we have this concept when the process is new or we just launched a product or we want to improve something and we call it the Gripe Dock. And I learned about this. I think we've put our own flair on it, but like the basics behind it, I actually learned in physics class in college. So in physics class they say if you're having a hard time solving a problem. Think about like a a block on a slope and you're trying to calculate how fast is that block moving by the time it gets to the bottom. It can be kind of hard to do all the trigonometry in your head. So they say, exaggerate it to the extreme and like, assume in your mind that it's not a 45 degree slope. Assume it's like an 89 degree slope. And then you can kind of check your assumptions to see that's almost a vertical drop. And by exaggerating and kind of blowing something out of proportion, it can help figure out where on that spectrum you want to land? So what the gripe doc is when you finish something, we make a Google doc called this product. This feature or whatever sucks because dot dot dot and we put bullet points in there. And what I do on my team is I will start those documents and I will list things that I personally contributed to, like at the end of any project. Right? Like you run out of time, you cut some corners like it's not like a knock on anybody's abilities to deliver, but like there are areas that are going to suck. If you had more time, you go back and do it. And what I'm doing is I'm making it okay to acknowledge that I'm going first and I'm like critiquing myself and putting myself out there because I don't think anybody else would want to be that first person. Like, I'm just going to pick on this other person over here.

Ariana (00:31:45) - Yeah, you'll be the guinea pig of it.

Zach (00:31:47) - And then you kind of like, let it snowball. And then you say, okay, what are we going to do about it? And then you kind of prioritize what to do next.

Zach (00:31:53) - And the first few times we did it, it was super awkward, like nobody wanted to say things. And then I found that going first bit is really key. But I think that's been kind of helpful because we'll and we'll gradually circulate them by putting it in a document. And it also doesn't have to be like one big meeting with it being global, where people are staying up at two in the morning and you can kind of just rotate around. And sometimes, I mean, the first time we did it, it's kind of awkward. Then we kind of got in our groove and we had like a ton of work to do, and then it kind of leveled off. So I think even if someone doesn't have like a million feedback points of things to complain about, it’s good to know that that process is there. But then it's not just like an open session where you complain, it ends with like, okay, it becomes a two column table and you say, what are we going to do next in the second column? And you fill all that in. So you're kind of setting a culture where it's okay to bring it up, but then we're going to collaborate and actually do something about it later and not just say, okay, that was fun. We all vented and back to having the same issues again. And I feel like starting with culture and then putting the process around, it kind of worked out.

Ariana (00:32:57) - Yeah, you're right, because I think what I've noticed in operations is that you need to give time to, to try something new, to see if it's working or if it's not working. And a lot of times in startup culture, if it doesn't work within a week or two weeks, then it's like, all right, throw it out. Right? Yeah. The key is to go through that awkward phase of not knowing the tool, not doing the process, or doing the thing to see if it's actually beneficial. And it sounds like you went through that too, where it's like, all right, people are kind of finding this whole thing a little awkward. This Gripe Dock may not be the thing. “Okay, I need to lead by example”, where you're sort of learning all of these sort of pieces to them. Be able to create that culture that you want to have. That tolerance, though, for awkwardness and uncomfortable like it's really important you have to be willing to be uncomfortable for a little while to really get the feedback, to understand if something is working. And I love the idea of a Gripe Dog, I'm totally going to bring that into things. In the past, I've done “celebrating failures”. So where you bring up something that you failed at and then something that you learn from it. And that was one of my favorite times when I was doing that with the team I was working with, because most of the time a failure is not if it's not a failure, right? It's just a lesson that you learned because something went awry. And then by sharing the failures, it just sort of takes the wind out of it. The shame, all the things that you kind of feel about failing. Right? Same with the Gripe Dock.

Zach (00:34:29) - Can I steal that on on our end?

Ariana (00:34:31) - Yeah, please. It's so fun. I think it's a good thing too, because I was such a perfectionist for so long, you know, when I was younger and I'm still a recovering perfectionist. But if you just celebrate the failures and you learn from them, actually, as a senior leader, it's really important to show that too. To say like, “hey, this is where I fell on my face. And I can kind of laugh at it now and learn from it.” And then, you know, other team members will start to mimic that. And that's how you really build culture, right? There's like a bit of vulnerability that has to happen for that culture to be made. That's hard to do, right? Being vulnerable to speak about things that you know, you maybe didn't do as well as you wanted to.

Ariana (00:35:14) - It's where the good stuff happens, though.

Zach (00:35:16) - Yeah. No, I think you're absolutely right, because I think that's where maybe there are other types of companies where this doesn't apply. But in a startup, everyone who works there is doing something that they've never done before. So when you're in that kind of environment and you're constantly learning, you're like a beginner at something perpetually because you'll figure it out, move on to the other thing. Now you're a beginner in the new thing, so would you expect someone who's like a kindergartner to perform at like a 12th grade level? Absolutely not. So I think we have this school mentality where you pick your area, you're going to study, get really good at it, and if you get a 4.0 and I get a 3.9, then you go higher on a ranking than me and failure is kind of stigmatized almost. And then you go into a startup where it's like, you don't need to be 100% expert at certain things to be effective at them. You just need to start and you need to try and you need to like, iterate on it. It's like you were saying before that 80% is usually good enough. There are lots of things that I'm not an expert at. I'm not particularly, I wouldn't even say good at, but at a startup, someone's gotta do it. And that willingness to go first is valuable. So I think you really do need to destigmatize failure, because otherwise you're going to put people in situations where they're doing things they've never done before, and they're expected to be like experts at it, which is just not realistic. Right?

Ariana (00:36:44) - Which is insane, actually. So there's a quote from your book that really struck me, and I want to read it because I think it's really important. And it reframed, I think, some of the feelings that I had about myself in operations, where I've heard a lot of operators sort of say, I feel like a fraud or like I feel like an imposter, because I sort of am supposed to know everything and I don't know everything, and it's impossible for me to know everything.

Ariana (00:37:11) - And in chapter two, Putting In The Work, you say, “sometimes our skills get the better of us. We gain mastery in an area, others respect our work. Then we start building expectations that all we need to do, all what needs to do. Hold on. Building expectations that all we do needs to be at a certain level of quality. The fear of returning to square one can keep us from trying new things. Fortunately, I don't mind returning to square one” and that for me, I read that I was like, man, that's so profound because the farther you get in your career, the more the fear can set in that I have to bring everything at a ten, right? Because I've been at ten for this long. But that's not going to help you evolve in where you're at in your life, right? It's impossible for you to always be a ten and everything, and that fear of having to remain there, I think keeps people paralyzed.

Ariana (00:38:08) - Where did that come from? Because I read that and I was like, oh my God, that is so excellent.

Zach (00:38:14) - I mean, I think I was just looking back at the situations that have worked out and the situations where I didn't. And I think the trade off that people don't realize they're making when they're in that situation, um, is that there's always opportunity cost, right? So if you're afraid to take a risk, it's not to say to be reckless, but like if you calculate it and say, okay, 80% is probably good enough, can I figure this out? You are saying that that path that you go down…you're just shutting the door on it, like there's 0% chance that that's going to work out. But if you say, you know what, I'm going to go back to square one. I'm going to be honest and say I'm not a particular expert in this area, then it could work out. And I think an example that I had in mind when I was writing was that our tech started working. Finally we had this trade show that we wanted to exhibit at. I'm an engineer by trading. I had never worked in sales, I had never exhibited at a booth. I wasn't media trained, but somebody has to go and explain this technology to the world. And the company has two people. So I bring my co-founder and we go, and we ended up actually winning an award for the best booth there. And it wasn't like we were amazing presenters, great orators, that we rehearsed the script or anything. We just were passionate about what we were doing. We had a kind of quirky, cool demo where we had a camera that was detecting people and we put it at the end of the lunch line. So when people are getting the buffet lunch, they'd like to get their entree, get their salad, get their fork and their knife, look up, see themselves on a TV with a box drawn around it. “Person: 98% sure” they’d come over and talk to us. And I still– don't think if you were to like, put me in a booth and compared my skills to somebody else, you would still give me a C-plus or a B. I'm not an expert in it, but being willing to put yourself in that situation, I was actually pretty close to just being like, you know what, I can't go, I don't want to do this. It's not my cup of tea. And the company probably would have died, right? Because we wouldn't have had a lot of customers coming in. We wouldn't have had, like, all the other things that I can see now in hindsight. So I feel like people don't always realize like,” that seems uncomfortable. I don't want to do it.” But what you're really saying is, “I'm so nervous to get over that hump that I don't even care what happens next, because I'm going to shut that door and it's never going to happen.”

Ariana (00:40:41) - Yeah. The fear is, I mean the skill that I struggle with, which I hear you, it was selling myself once I went on my own, was being able to sell what I do. Right? Because like, as an operator, I'm behind the scenes most of the time. I'm not pitching what I do. And I remember the first pitch that I really had. I mean, I shat the bed, it was absolutely horrible, you know, it's just like so awful. I was so nervous. I was sweating like I talked them out of working with me. It was just so bad. And I, I think I needed that. I needed to struggle through that because then it became so much easier. But that first one was just like, you know, I remember rehearsing in the morning as I'm getting ready, like things I want to say, and then I'm in the moment and I say all the wrong things, and I guess that taught me a big lesson, which is, “oh, okay, when you're starting something that's your own, you're going to be doing things that you aren't good at, like you're just straight up not good at.” But that doesn't mean that you can't not do them. That just means that you have to do them. Suck at it for a while until you get decent at them. And you can kind of pitch yourself or you can do the things right. And that that story that you had, I thought was so, so good because I think that that is a differentiator between people who are entrepreneurs or who wants to start their own thing, it’s just getting over that fear and doing the thing like it's so important, so paralyzing. But you just got to, like, get up there and you gotta fall down and get back up again. And the best thing is, I think that I found immediately after it completely bombed that pitch. I called my husband and we could just laugh about it. And that was a huge relief. Right? Like, you need to have that person or those people in your life that you can just be like, well, that really went to shit, you know? And that just sort of helps you get over and think about it and improve it. That's, that's, I guess a tip that I'm going to bring into this, which is you have to embrace those fears and then have that community that you can fall back on, laugh about it and learn from it.

Zach (00:42:49) - Yeah, I've had my fair share of similar ones. I think one of the first investor meetings we ever had, I got asked two questions that you never want to get asked in an investor meeting. So we go through the whole pitch, the slides. I thought I had some awesome slides, scrutinized the gradient on the back and the font size, and didn't rehearse talking about as much as I probably should have. So we get to the end and the partner says, so what's your value prop? So you should not get to the end of a pitch and not have that be clear. So that's like issue number one. And then I explained it. Got a complete blank look “okay”. It's also not the reaction you want to have once you wowed them with your amazing value prop. But I feel like one of the things that we did, we got some advice, which I think turned out to be right, is when you go in these situations, it's not just like a pull yourself up by your bootstraps to grit harder. Like you mentioned, it's good to have a support network. It's also good to realize that this is going to happen and plan accordingly. So if you have like one investor that you're like a firm or something, that you're like super key and you really want that one to work, maybe don't start there. Maybe find a friend who's not actually going to write a check and like, bounce ideas off of them and then go to somebody else that a founder who has raised before. And you can, like, do these practice sessions beforehand. And I feel like you can de-risk that, like anxiety around being good not good at something by making it okay to not do a great job the first time around. Like the first time I had to give a talk on stage, I turned on my phone, recorded a video of myself, and did it in a room. Then you go watch it and you're like, hey, I'm really twitchy. I say, I'm a lot, and you can go back and you can fix these things in an environment that's not super high stakes. So I think it's like the art of engineering the risk around things, and there's like an art to de-risking, and there's an art to like taking down the stakes, making things reversible if you can, making it not catastrophic if it fails. And I think entrepreneurs are usually heralded as he's like great risk takers. And you do take risks. So I see why they say that. But I feel like we're actually really good at making things less risky than they need to be. Right? Like, you can de-risk something. You can not make something a bet-the-farm kind of scenario, if it doesn't need to be. And you cannot do things that are super catastrophic if it fails. So I'm just seeing it come up a lot with the more experienced folks on our team versus the newer folks that I feel like the more experienced folks are really good at making things not so rickety and like one thing goes wrong and the whole thing goes to pot.

Ariana (00:45:31) - Totally. That was actually something I learned. So like I had a team that I was leading and I had more junior team members who were just new in their career and I think you're totally right where you want to learn in a very low-risk environment, so that when you're in a high-risk environment, you're ready to like, you know, do the thing. And so every week we would popcorn who led the Monday meeting. And the agenda was always the same. But you'd sort of put your own spin on it at the end. And everybody took a turn. The most seniors and the most junior members took a turn doing the agenda. And I think that was in retrospect, that was a really sweet time for me, because I got to see people really take up space who maybe hadn't in the environment because, you know, some people are going to be more outspoken in a team, some people are going to be more leadership focused. So they're going to take the torch more. And I think by creating that internal space within a team or a community where everybody can try at the things that they are good or bad at in a low stakes way, really helps you gain that confidence and helps you find your own voice, because how you would pitch to somebody versus how I pitch to somebody is so different, right? And if we mimic each other, that's not going to work. You know, that's if you try to do my thing, it's going to feel awkward. If I try to do your thing, it's going to feel weird. So you have to sort of find your own voice through just trying to find it. But in an environment where you are supported and where you can fail. And it's totally cool. I like that idea of taking risks, but figuring out how to mitigate those risks earlier on by hacking the system, either having those interviews, having those chats with people where the stakes are lower just to get that practice is key. I think the audience would be very mad at me if I didn't ask you for your technical piece of advice, considering that you've got such a breadth of knowledge and I want to spin it for non-technical people. So as someone who has gone to school for this, who has worked in an industry, who's been at the forefront of emerging technology for so many years, if we're talking to non-technical people and they're listening to you and they're like, man, I am so out of my depth and it's going faster and faster and faster, and I have no idea how to keep up.

Ariana (00:47:49) - How would you guide those non-technical people? Like where would you have them start in learning about technology today?

Zach (00:47:58) - Sure. So I think the number one thing that I've realized is that all technology problems are humanities problems, that technology doesn't just exist because it can, that there are reasons that it exists. And if you are non-technical, you have some area where you're an expert in and you have workflows that, you know, you have processes that you do. And don't discount those. I've seen a lot of folks discount them because it's not tech, but tech serves as a means to an end, right? Like we don't care about having phones. We care about communication with each other and these workflows and these processes. That institutional knowledge is super valuable. So that's thing number one is don't discount that body of knowledge. Then I think step number two is. Just be willing to experiment. Like if you listen to engineers talk to each other when something new is coming up, like some new software gets released, people want to try it out. They use like, almost childish terminology. “I want to play around with that or I want to take it out for a spin” like you would a bicycle or something. And that's like the mentality that you have when you're going into this is you're playing, you're just seeing where it goes. So I would say take some percentage of your time and dabble. Don't have a particular outcome in mind. Go play with ChatGPT, see what it can do well, see what it doesn't do well, because I feel like where real innovation happens is there's this technical capability and there's this real problem that people have. And when you find yourself at the intersection of that, that's where you can step on the gas. But if you're too far in the field of technology and you don't know the use cases, then you're not at that intersection. And similarly, if you are outside of the technology, then you won't. So you kind of want to go out of your way to put yourself there and I found some workflows that I've like, for example, incorporated ChatGPT in my day to day work. But it started on the weekends because I was just curious. I know this might be a dumb idea, but I downloaded my checking account details and I asked “what subscription should I cancel any other like cost savings they can do?” Like, maybe that was silly, but it's just like I was just playing. It was like, “hey, what if this happens? Hey, what if that happens?” Then you start learning, like asking it to write a blog post. You get a lot of like mundane run-on sentences that don't really mean anything. But asking it to analyze data it's actually really good at. Then you have that, like filed away in the back of your head. You're going back to work on Monday. Something comes up where you have to analyze a mundane amount of data. And like you, you have this skill that you got from playing, which is a bit counterintuitive for folks that are used to studying and reading textbooks and things like that.

Zach (00:50:45) - But I feel like having some time to play and then talking to other people around like, “what are you doing?” A lot of ideas are inspired by or bored from other industries. So being able to just bounce, like, “hey, what are you doing in this area”? And kind of cross-pollinating from industries that wouldn't historically talk to each other is kind of where the secret sauce lies from what I've seen.

Ariana (00:51:13) - Yeah I agree, I, I also really echo with that. For a lot of my career, I didn't really understand how all the pieces fit in together because of the different industries, different roles. I was like, where does all this fit together? Like don't get it. I don't get my own career. My husband, he said, “don't worry, it'll all come together. It's all working together.” You just don't know how it's going to fit together yet. And I do think that now, you know, operations is that thread for me where it's like that became the through-line, through everything I've done in my life.

Ariana (00:51:45) - And I think that that is actually quite powerful to have all these different experiences. You know, like I used to walk dogs, I was a server, I was a host, I was coat check, you know, like I used to just work all these random jobs in all my 20s and, you know, customer service and all of that, though, has given me such a wide breadth of perspective to be able to solve problems and to communicate with people, because I've been in a lot of those shoes to be able to understand it right. And there's something very powerful about that. But I would say it's easy to feel like, “what am I doing when you're in the middle of it? Like, what? Where am I going with this?” It was interesting. Like in reading the book, you know, there's so much more to your story that we could unpack here. Unfortunately, we don't have enough time. But what I loved about it was that you sort of just said yes to things and then figured it out. And I think that there's a lot of power to just saying yes and jumping in and trying it, if you even if you don't sort of understand the full context of how it's going to come together in your life, because it's going to influence you in a way that we might even not have context in, like today with the technology or the industries that we have. And there's something I don't know. I mean, I could really talk to you about, like the patents and the sort of physical products that you've developed and all these other things. But that's something with your story that I find really powerful and I think is a great thing that I'm going to take away from learning through your journey. Zach, the time has come to ask you some rapid fire questions to get to know you as a person a little bit more.

Zach (00:53:24) - I'm going to need to caffeinate myself a little bit before we get here.

Ariana (00:53:27) - Yeah, you got it. You got it. So just answer with the first thing that comes to the forefront of your brain.

Ariana (00:53:35) - And the first question is, what is your favorite part of the day?

Zach (00:53:40) - Definitely mornings you can plan out what you're going to do. It's usually quiet. I'm a relatively introverted person and I always wake up early, so when my day starts I feel like my battery is at 100% and exactly like a cell phone. I gradually decay throughout the day. That's 100% my energy level. So I'd say 15-20 minutes after waking up is perfect.

Ariana (00:54:05) - Beautiful. What book are you currently reading or what audiobook are you currently listening to?

Zach (00:54:12) - I'm actually going back to one that I read a while ago. So I've got two, one new one, one old one Billed by Tony Fidel. And he was the one of the lead engineers on the iPod at Apple. And then he went on to found Nest, the smart thermostat that got bought out by Google. And he has a lot of interesting lessons that he's learned. He calls the book like an advisor in a box, and it's really just like strange situations he's been in and how he's, like, innovated his way out of it over the decades. So that one is really, really fascinating. And then I'm going back and on audiobook and listening to Peter Thiel 0 to 1. It's kind of like a seminal startup book, but I feel like I read it when it first came out. I was much younger then, and I'm getting a lot more out of it this time around than I did the first time before.

Ariana (00:55:05) - Oh, I'm gonna check out both of those. My husband has been trying me to get to read 0 to 1 for a while now, so I will do it. I will do it now that I've got your sign of approval. What is the best purchase that you've made? Under $50.

Zach (00:55:20) - Under $50?

Ariana (00:55:23) - That is the, that's the tricky part.

Zach (00:55:25) - Can I show you? This is, I don't know.

Ariana (00:55:27) - Yeah.

Zach (00:55:28) - All right. So you see the safe here. Underneath here we have all these really awesome Yembo branded notebooks that we give away at trade shows. And they are…it’s a long thing that I don't really have time to get into right now. I ended up meeting a factory in China that does stationery products, and this is like their one bread and butter. So you want any other product? I don't think they can do it. But they gave an awesome deal. And these notebooks are $2 a pop. And when you go to trade shows and you give it out, people are like, “are you sure I can just have this? I haven't really done anything yet. Like, how much investor money did you raise?” And there's this perception that the thing is like a Moleskine and it's worth $30. But then there's the reality that it's like two, and that one is we got our money's worth out of it.

Ariana (00:56:19) - And there's something magical when someone hands you a notebook. I don't know what happens, but I feel like most people just sort of get really excited and don't know what that is.

Zach (00:56:26) - And it's great from a branding aspect. It's a great Trojan horse, because that's an excuse for your logo to sit on that person's desk until they get to page 200 in the back. So there's maybe an ulterior motive there, but it's one of the fastest moving. We've tried a bunch of different swag things at trade shows, and the notebooks always go quickest.

Ariana (00:56:44) - Yeah. Totally. What is your favorite quote?

Zach (00:56:49) - Favorite quote? There are a lot of good ones. I’ve got to pull up the …

Ariana (00:56:58) - You think through that mental library.

Ariana (00:56:59) - No rush.

Zach (00:56:59) - Richard Branson has one that's called. He says “Screw it. Just do it.” And I think if there's a spectrum of like conscientiousness and recklessness, he's definitely further down on the reckless side than I am. But I think that idea about like you, you won't know until you try is definitely true. So we have a picture of a like a gif of him saying that quote, and I send it to people at work. Way too often people are “like, well, I'm like, I think it's going to work, but I'm not 100% sure.”

Zach (00:57:32) - And then like that GIF shows up and then things just clicked.

Ariana (00:57:36) - That's perfect.

Ariana (00:57:38) - What is something that makes you little-kid-happy?

Zach (00:57:43) - Too many things. I think whenever a new tech gadget comes out, it's like, it's like a thing on YouTube now. And I'm not really the kind of person that would post these things on YouTube, but I really like packaging, which is a weird thing to admit. And like when something comes and you go through the unboxing experience and you think about like the onboarding flow around like, this this box came and you open it up and it's the manual on top, or is the manual underneath. That kind of speaks to the confidence that the product speaks for itself. Because if I make you read through a manual before you get there, then you're probably not. So I get weirdly excited, even over silly things like these are, I think, $20 AirPod knockoffs. But still, when I got it, I thought the the, the flow that you go through to get it…I was really weirdly excited about. But I have a I have a text thread with a couple other friends that are like-minded, and I don't bother my other friends that I know don't care about these things, but like, we'll take pictures and make fun of the kerning if it's off on the font, or we'll be like, “hey, check out this material that they use.” So it's weird, but I've learned to just own it.

Ariana (00:58:51) - I love it. Also, that's coming back to your book. That's the first thing we hopped on this call was like your book's journey through this was so gorgeous. So clearly that is all a part of your life now. And every component.

Zach (00:59:04) - Decades of opening boxes on things and taking notes.

Ariana (00:59:06) - Totally, totally. What is the most important lesson that you've learned so far in your life?

Zach (00:59:14) - I think understanding why. It's really easy to do something that's like, maybe something that's even never been done before. But I mean, there are markets that don't exist because they shouldn't exist. They don't really serve a purpose. But I think being able to connect why you're doing to what you're doing has sort of profound impacts that that didn't always realize at the time. I think a trap that I ran into earlier in my career, being an engineer is I always want to build something. And I think by learning why and say, “okay, I want to build something because that's like the one trick that I know I'm relatively good at it. It makes me feel safe.” You can kind of digest what is coming down to that. And then when you're talking with other people and someone else who maybe has a different background wants to do something else. Having conversations around their view on why, I feel like it's easy to talk about what. And “I've got this meeting I need to go to in ten minutes. I gotta drop it out.” Okay, “well, why is that there? Do you really need to be at that meeting? Like, okay, you're telling me you have too many meetings? How can we streamline it?” Like these kinds of we get caught up in the what? But I feel like the why is really where the value is at and where things are more important.

Zach (01:00:32) - So I think taking some time and energy to kind of dig and get to that is, is something that I wish someone told me like ten, 15 years ago.

Ariana (01:00:43) - And it's worth the effort to take that time to do it. Lastly, what do you want to be when you grow up?

Zach (01:00:50) - I want to still be curious. I think more or less don't want to change anything except for maybe the scale of it. I think if you look at when I first started my career, it's like, okay working on signal bars. You get good at that. Now I have multiple disciplines on the team here. We have to bridge the gap between AI and software and design. So I think when things go on, I don't know, maybe find a way to suck CO2 out of the atmosphere, some other like more audacious goal. But I think breaking big problems down into small ones, getting to meet cool people who know interesting things and doing things that haven't been done before never really gets old.

Zach (01:01:32) - So I want to…I want to be just as much of a beginner as I am today, ten, 20, 30 years down the road.

Ariana (01:01:38) - I love It. So people are listening to you and they're like, I want to listen to more of what Zach is doing or what he's up to. Where should they follow you? Where should they find you?

Zach (01:01:49) - I'm most active on LinkedIn, so if you look up Zach Rattner on LinkedIn, you can follow me there. If you want to learn more about the company, yembo.ai and see all the different things that we're doing there. And if you have any questions, probably like a DM on LinkedIn is probably the best way to get a hold of me.

Ariana (01:02:09) - Amazing. And check out the book Grow Up Fast. It's really excellent. The design is gorgeous and what I love about it most. Again, I'm still reading it is the approachability, being able to really understand your journey and all the things that we talked about today, like in your experience, was really refreshing. So I would highly, highly recommend it. Just want to thank you so much for your time and for your viewpoint. It's really expanded my brain a lot, so I just appreciate you taking the time to come on Secret Ops.

Zach (01:02:43) - Thank you Arianna, I had fun. Thanks for having me.

Ariana (01:02:46) - Thanks, listeners again. Thank you for always listening to Secret Ops. You know, it means the world. Please remember to follow us wherever you find your podcasts. We're also on YouTube now, so you can subscribe to us on YouTube. Or you can check us out at secret-ops.com.

Ariana (01:03:03) - We will see you next time.