Zach welcome to the show hi Omar happy happy to be here thanks for having me I'm so glad we finally did this if if uh the listeners knew like how long it's taken us to get this thing scheduled and and kind of reschedule um it's quite an achievement so thank you for uh making the time today for sure if something's important it's worth doing yeah totally yeah do you have a favorite quote something that inspires or motivates you that you can share with us I do I am a big uh big fan of the band
radio head and and um they have a lot of good lines where if you digest what they're saying it's not always like immediately apparent but there's a line um on the album Kid a this one's optimistic this one went to Market and it talks about all the hosts of things in general that can go wrong but I feel like as a Founder being optimistic and still going to Market anyway is something that kind of gets me out of bed in the morning yeah love that so uh tell us about yembo what does the product do
who's it for and what's the main problem you're helping to solve sure Yambo is a computer vision company we're are about 70 folks across the world about half in the US half out and we provide computer vision services to moving companies and property insurance companies so in both of these markets if you want to get a quote for something it's traditionally very labor intensive someone has to schedule some time ring your doorbell walk around note down every item that's being moved or every item in the policy if you're getting insurance and what we provide is
a computer vision workflow where you can send your clients a link they can record Quick videos of each room in the house and then the AI identifies what's there pulls out key attributes for moving volume and weight are pretty key and then we provide that information back so you can have an accurate quote with the real photos of the items being serviced in there so our business model is to sell to the service provider so we sell to moving companies and sell to insurance companies but we provide the whole Suite of software where they use
it for their end users but the End customer gets it for free effectively because our our client is the company that's providing the service great and give us a sense of the size of the business where are you in terms of Revenue customers size of Team sure so we have customers in about 30 countries across the world um probably 70% of our businesses in North America but do have a sizable presence in Europe and Asia as well uh we have every day we're processing couple hundred hours of video those can be quick little 20 30
second uh recordings of each room all the way on up to longer calls for live video chats and um terms of Revenue we're in the high seven figures um and uh probably every day we see like on order of a couple thousand inspections being done across the whole product Suite cool um you mentioned you were a team of about I think 70 people uh what what's the general makeup of the team I mean with a AI startup do you do you kind of lean heavily towards people working on the technology or do you have a
big sales team or and how's kind of the general setup of the team yeah so we are we are yo. we are engineering company I'm an engineer by training my co-founder the CEO also as an engineer our team is about half Engineers um the other half we have operations customer success go to market folks we found that's really key because at least in the business World we're not selling something that's necessarily fun or a game like we want to provide a delightful user experience but being implementation experts is really key so that's why we have
a pretty big team that understands the client workflows and we sort of become like expert management Consultants almost that we're not just trying to sell software but we're explaining here's how you can take Cutting Edge 21st century technology and bring it back to these traditionally underserved by Tech communities and that's why we've ended up having kind about 50/50 engineering vers not just nature of the business that we're in cool and you know you guys were founded in uh 2016 and you were an AI company before everybody was trying to be an AI company right so
tell us about like where you came up with the idea for for this business sure so rewind the clock a bit it's May maybe 2015 or so and there is this academic Benchmark it's called imag net and if you're not familiar with it you can think of it like a thousand way multiple choice test so the imag net competition would have universities and corporate research Labs submit source code to compete in it and the way it works is you hold up a picture and you'd ask what is this of a human can do that relatively
easily but the challenge would be out of a thousand or so potential categories how do you make algorithm that can identify and what happened around that time was humans were no longer better than computers at identifying objects and images the best algorithms beat a college educated human and um what I saw happened then was seemed like the entire Silicon Valley Zeitgeist was pointing at self-driving cars and drones and these very competitive markets super ambitious problems to solve I mean even now as many years later still not solve self-driving cars still have edge cases failure scenarios
we still have steering wheels on our cars um and what I wanted to do was find an industry that was not going to see that advancement in technology coming and then just provide an amazing user experience so that people would be able to um to realize the benefits of the tech and my wife was working at a moving company um so that was kind of the the Genesis where I had the tech background she was working at a moving company she was working in logistics so if there was an issue and maybe a 12-ft truck
was sent when you should have sent a 16-ft truck it was her job to pick up the phone figure out where do you get the larger truck from and kind of manage all the downstream problems and the more we learned about the space the more I realized it's not for lack of trying it's just really difficult to provide an amazing experience because there's so many details you need to get right in a typical home when you're moving you may have 300 or so items and all of them can be a little bit different so how
do you plan for a move how do you make sure you have the right number of boxes on the truck seems like kind of simple but if you bring the wrong number you have to come back the next day or go and pick up some more when you're supposed to be on the job so it's just a very difficult problem to be able to solve and that's why it seemed like ripe for computer vision to come along and help okay great so you you you you've got the technology and you you're you're seeing it you
know applied in some of you know the kind of places you mentioned but you're seeing also these problems you know kind of more like day-to-day world with like moving companies and you're thinking why why do people have to go out why can't we use that same technology to solve this type of problem what did you do to go and validate the idea did you you know I mean you you you spoke to your wife and and that's kind of you know one Insider that you're getting some some information from did you start to you know
try and do the whole kind of thing like line up interviews and go and talk to people running moving companies that's exactly what we did I think one of the cool parts of the moving industry is it is super fragmented I think there's 7,000 or so licensed movers in the US all the way like large companies all the way down to like two guys in a pickup truck and what we did was we first to validate you can tell I'm an engineer we wanted to see how big of a problem is this really so I
went to the Better Business Bureau and they have rankings of complaints that have been filed by industry and we just pulled the data down turns out movers get complained about more than lawyers more than diet supplements and more than Airlines so we figured okay there's there's something here going on um and then we wanted to zoom in and see what exactly is it about moving companies that people complain about and we looked at Yelp reviews Google reviews BBB complaints and um did some rudimentary data analysis on the keywords that were being used and what we
found was people generally complain if you break their things if you quote incorrectly or if you don't show up on time so we're a software company we we can't necessarily help with the showing up on time part because that's a physical physical thing but the prices being incorrect was something that we learned was really really an issue so then from that we're able to go call multiple moving companies and again cool part about it being a fragmented space is I can get hung up on a bunch and that's okay because there's so many fish in
the sea so we did some cold calling I randomly showed up to a couple that didn't go over too well you usually just get escorted out of the building but in the beginning days you got to do things that don't scale so so how did you how did you kind of you know you we were chatting and you were saying look I'm I'm an introvert I'm an engineer how how hard was it to just walk into these places or start cold calling and you know once you get those first few rejections did it kind of
make it harder or or did did that just you know kind of smooth the the the kind of the wheels for you and and you know kind of just get you into um get get you into the flow of of doing this I'm just trying to understand like what was going through your head or how easy or hard it was to to go and just uh talk to these people yeah it gets easier I would say it never got easy I remember the feeling in the pit of my stomach when you park the car you're
in the office and even if they agreed to meet with you and uh open my phone for the 18th time looking for an excuse to not have to do it so there's a certain amount of um convincing myself that I had to do to it's more of like a mindset change where this is an impediment to progress if I want to see if this thing is going to work and I don't want to just have like a fantasy in my head of one day running a company I'm going to have to get over this and
yeah you have some embarrassing situations that come up but um I think if something's really important you can convince yourself that it's worth going through the pain to get through it and I think the like on a lot of things in business and in life I mean you practice a bit you get better and maybe you fudge one or two but we would also um work that into the system so if you have a really important client and you really uh want to do a pilot with them or you really value their feedback put them
fourth or fifth on the list so you can get some reps through the system um all learning is good learning so just you can kind of be prioritizing along those things so I would say it wasn't it wasn't necessarily easy I still don't think I'm the best person in the world at doing it but the goal is to be good enough to get to the next level not perfect yeah yeah it's good attitude okay so when you weren't being escorted out of the building and you managed to get these people's time whether it was on
the phone or in person what was the reaction when you tell them that we we're going to build this a solution to do these you know virtual home surveys like like were they excited about the idea it was a very polarizing suggestion there was about half of the folks that we would talk to would say if you can do this you would completely revolutionize the industry this is incredible like can I buy it now sign me up and then we didn't have it working yet so we we made a wait list for those folks the
other half though were skeptical and they would just say yeah yeah right if this could have been done it would have been done by now and that's where as an engineer and as a Founder you usually want to have some secret that you know that most of the market doesn't know but you got to remember that image net thing had happened so I knew computers are better than people at identifying objects and images but that's a big radical like fundamental sea change so it made sense that people didn't quite understand yet so for those folks
we didn't say no forever um we just didn't continue following up with them they maybe aren't an early adopter um kept it in the CRM and put a note on it and if you're specific about the objections and if they mention hey this is never going to work you can follow back up a year later when you have it working and say hey would you like to try it out here's a link free of charge we'll U happy to walk you through a demo but um yeah it was very very polarizing people would immediately fall
into one of those two categories how long did it take to get to a point where you felt confident enough that there was an opportunity here there was a startup potential um and and that you know you guys were going to invest more time in in building this product yeah it took about maybe two three months to convince myself that if the tech existed that there would be a business there we were also for the conversations that went well we were experimenting with different business models so we even negotiated pricing and did these non-binding letters
of intent I mean they're not really that um they don't carry any legal weight but they would help us articulate if such a thing were to exist is $100 an estimate too much is $10 so we we got it to the point where we had a a list of clients that had basically agreed to pay a reasonable rate per survey and do it assuming you're able to do XYZ ABC so that took a couple months the next question that came after that though is is it possible to do what we're signing up to do and
what these people are expecting and that that part took a couple years to get really really resolved one question about the letter of intent how did you frame that with these these customers like how did you get them to sign something so we did it as a weit list we realized we're not going to have infinite capacity I mean Gmail took what 10 years to get out of beta so we figured hey when this thing does exist I'm not just going to open the floodgates to everybody I'd like to take one client on then three
more then five more so we pitched it as expressing interest in reserving a slot in there so there was no cash no upfront ask immediately but it was if you're interested and you'd like to be on this list would you be open to like monthly check-in calls and here's what the pricing would be but again you don't have to pay anything till it actually exists and what we found then is you get the right kind of customer when you do that you get someone who sees the potential of the technology who wants to be first
to Market and everyone else you'll need to build out more features add more bells and whistles down the road but you want your early adopters to be Unapologetic supporters of what you're doing and that process kind of helped filter those things out if they started nitpicking about slas and uptime and can you translate into this language they're all reasonable concerns but just not for customer number one so we would note the concern park it and then go look for somebody else and and did you actually get them to sign a piece of paper or E
signature or something yeah we actually did Adobe fill in sign again it was uh it was one page and it said I think it was something to the effect of like if yumo had an AI powered virtual inspection solution that could identify objects from a customer's video then we would be interested in paying 10 20 00 whatever dollars per survey for it it was like very very short and brief but I think the point was to be able to articulate the value enough and then also you're not really negotiating um so you can be a
little bit more abstract with it so we'd say would you pay $1,000 a survey they'd say never you kind of like learn how they're thinking about it the expected Roi that they want to get out of it and that really helped when we're building the product to understand what is Meaningful what moves the needle for my customer because we don't want to just extract a bunch of cash from our clients we want to help them go grow win more business and then participate in some of that upside yeah I think that was a really smart
thing you guys did There's when you when you do these types of interviews and people say that sounds great it's tempting just to stop there and say they love it and when we come back with the product they're going to pay but I think to get to that last Mile and actually have them sign something even though you say you know not legally binding or anything there's a there's another level of commitment or or a data point that you're getting that they that they're interested enough to be able to you know willing to do that
right um so I think that was really smart the other thing you said was it took a couple of years or a few years for actually for us to actually build the product that you know we wanted to was was that was there something in between like did you did you come back with a first version or an MVP with these guys how long was it between the time that these customers or potential customers were signing these Lois to the point where you came back and put something in front of them that they could start
trying sure yeah it was about a year or so from Loi signed to here's a login uh probably about two or three years to the point where it was enough to be a viable business and this I think was really key and for any listeners who are thinking about applying AI or machine learning to your end to end products I think this was a really key finding was if you expect the AI to be perfect there will always be scenarios that doesn't quite work in AI is fundamentally probability based even a human right if I
if I ask you like hey read the text on the spine what book is this people aren't going to be perfect at reading it so if you make your use case so high stakes that it needs to be perfect you're going to have implementation issues so what we did was we we understood the customers problem really well they spend a lot of time burning fuel sitting in traffic wearing te in the vehicle it's not a particularly awesome customer experience to have a handwritten list of items and then sometimes the prices change you don't quite no
why so we had an intellectually honest value proposition which was still intact if the AI wasn't perfect so what I mean when I say that is typical home may have two 300 different items if our AI could only detect five or 10 we were still saving time and we were giving pictures of the actual items that were there in the in the move so the Mover may have to go through and do some review and spend some time it's not completely automatic but they are providing better documentation they're increasing their win rate they can go
into geographies they don't physically uh have boots on the ground in and there were enough reasons that someone would want to do that that it was okay that the AI wasn't perfect and that gave us a reason to exist another day and then over time we were able to say hey this um product that we put together the AI can detect 10 items then 50 then 60 then and we kind of gradually worked our way up but we were really careful not to set the wrong expectation that it was going to be a completely driverless
self-driving car no steering wheel and you can just go anywhere in the world by the click of a button on day one because that would have set us up for failure how did you guys um fund the business for the first few years we did an early seed round um with some Angel Investors and kind of bootstrap that way AI is really expensive just the compute is is a lot but we tried to not get too hung up on raising gobs of cash and doing a bunch of crazy things so we did make sure that
um like the first uh dollar we took in was actually revenue and then from there the uh the investment was always to accelerate and to develop the product further and to to make the AI better and I think that was really key where we never really got too detached from reality that we wanted to make sure that the product that we're offering is valuable to our customers so that um we see it as like an accelerator but you have to already be on the right track and heading in the right direction but we didn't want
to just like take Venture dollars and then go figure out what to do next because that's a that's a very inefficient way to operate yeah yeah okay so you go back to those customers about a year later give them a login and then what happened what was you you you you'd been talking to them about this vision of how Ai and this product could make their lives better and you know some felt it was revolutionized the industry what was the reality of that first version of the product it was it was bumpy it was rough
so I think our AI could detect maybe 10 or so items really well um we had no full-time product designers no one with psych background so the user interface was it looked like it was built by a backend engineer me um so we had uh we had some churn problems we had bad expectations where people were expecting it to see behind closed doors work in the dark just stuff that is like literally never going to happen um but like the promise was there and the right group of customers got value so some people came and
then left but other people came and then expanded and what we found was certain clients were able to expand the geographies they operated in it's traditionally very expensive to open a new satellite office as a mover you have to rent a new Warehouse trucks crew all these kinds of things but with Yambo you can buy Google AdWords in a new geography and quote the jobs and then not really actually drive out there unless you win it so what we saw is people were able to uh decrease the cost of expanding their business people will be
able to service leads after hours if someone's working 9 to5 they may not be home to walk around and answer the door but you could text them a link they could do it of their own convenience so what we found was the initial archetype of a customer that did well in the early days had one of those initial pain points and then as the technology got better as we added on more features we were able to broaden the applicability but what we found was that we needed that initial group where they felt some kind of
paino that our product at that point in time could serve we don't like selling technology that's going to be valuable based on future performance it's like if you sign in and you get a login you should be able to do something today that's valuable and uh wasn't the easiest but we were able to find that group of people then expand from there yeah I I think that it's not just finding people with the pain but like you guys were doing it's also about finding those early adopters people who are who are more motivated or or
just kind of more inclined to use this type of technology or to try things versus the people who have the pain but the minute you know they type in their password wrong and can't log in it's like they're game over right they're not interested anymore that's not your first ideal cust store initially anyway yeah and I think and when if you don't if you legitimately don't have capacity to serve everyone then you can ask qualifying questions and we've had a couple clients that were asking to be in the earlier cohort cuz who who it's just
human nature right who would volunteer to be second right everyone wants to be first but there were some folks who just mentioned hey I don't think you're going to get what you want or what you're expecting to get if you go live with us on this day I think you should go into the next group and um sometimes people bristle but at the end of the day you got to you got to do what makes sense and I just didn't want people to sign up with expectations that I know I couldn't live up to because
then you're going to get a cancellation notice the next month when the renewal comes up right so you said it was bumpy initially obviously over time the the AI got better the product got better that story about your customer's wife that we talked about when when did that happen just tell us a story I'm I'm trying to figure out like was that very early on or sure yeah that this was early on so the the Yambo product REM moving someone scans a quick 20 second video the AI summarizes it into some images and then shows
what's there so if you want to scan this room you'd see TV printer book carts needed to pack it and this particular room that we scanned was pretty busy there's a lot going on maybe 80 or so items but the uh mover who was testing it out his wife was standing in the room and she was kind of stretching like this a bit and um our AI accidentally tagged her as a surfboard surfboard which is not a kind of problem that a human would ever make but if you're Ai and you're just seeing lines and
shapes and colors that person bent like this you can kind of you can kind of see why um but um those are the kinds of problems that uh that I think a lot of AI companies face where from a technical standpoint it's not really like a different kind of failure than calling a sofa a love seat but from a sociology standpoint it's dramatically different and um those are the kinds of things that we we had to go back and um actually became a barrier to adoption is the AI would detect like 80 things correct and
everyone wants to talk about the one or two mistakes it would make also we found laundry baskets and bedrooms were often being called barbecue grills because usually barbecue grills are covered you just see fabric over some Contours um but like you and I as humans no you don't really keep a barbecue grill like in a heap on your bed in your bedroom so we had to build out in the early days um our AI team called it ugly hacks I called it our Common Sense engine and we'd say things like if you see um refriger
ators in the bathroom they're probably white panel doors just call it a door don't call it a refrigerator and we had all these like ugly hacks just to make the AI not make stupid mistakes because those are the kinds of perceptions like you're not you're not associating your brand with trust if um if you make like glaringly obvious mistakes so it was kind of like he brought it up in just it was funny took him maybe like two years to stop bringing it up as a joke um but it did actually make us re-evaluate how
we were being perceived and the the product did change as a result of that okay obvious so obviously you're you're improving the AI technology and you've got these wonderful hacks in place to you know help you make it through to you know the next level you know next kind of wave of improvements that you're you're going to roll out what did you do to manage expectations with customers when they're excited about the technology and you said you know it was pretty accurate but they were picking up on the one two three things that it didn't
recognize or do a great job with so how did you manage that situation with with customers it was not a one anddone thing it's what you do every day so in our sales decks we made sure that we pitched it as something that saves time but does not eliminate a human we um put in a lot of energy and effort like I don't feel great waking up in the morning building Terminator technology so we made a point to say hey these are commission-based salespeople you can close more jobs focus on growing your business and being
intellectually honest about this actually if people say that's not going to happen then like ask them why figure out why and then come up with proof points and show that it's able to to improve the top and the bottom line so I mean people do always bring up individual mistakes here and there but I think it's it's machine learning it's probability based people understand that but by having that core value prop around okay maybe we did call a sofa a left seat or a wife a a kayak or a surfboard or something but you got
a quote out and the person came to your website at 7M when no one was in the office would you have preferred that they just shopped around somewhere else and you would have lost the business so we kind of like made sure that people were understanding it the right way but then also every time they were right we'd make sure that we'd catalog it we know we had Telemetry so if the AI was getting corrected even if you never said anything we would still know because like any AI product you always want to be iterating
and always want to be improving want to talk a little bit about sales getting to that first million in AR you know both both you and your co-founders Sid are Engineers um and many Founders in that situation would uh would try to get a sales person or or some kind of you know growth Market or whatever on board as quickly as possible so they didn't have to talk to customers or try to sell anything you were pretty deliberate and you you you decided that you were going to do the selling even though you had no
experience why why did you do that and and kind of what was the experience for you sure I think it made sense for the time and place we're at today we have sales folks they're better than I am at it and uh I don't necessarily miss those days however in the early days when you're selling nent technology the market doesn't quite understand it yet you don't even quite 100% know is it going to be perfect is it going to work is it is it going to be viable or not I didn't want to have another
layer in between on hearing that feedback and getting those objections and I think it goes back to those early days when I was telling you when we were looking at the Better Business reviews we were talking to prospects is I got told directly this is important to me I wouldn't pay for that and we decided until we got to a million in ARR I didn't want to be trying to Outsource it because I don't know what works or not if I bring someone on and they can't close any deals and they come back and say
the product doesn't work I didn't have enough history with it to really understand what's right what's wrong so I don't think I was the best salesperson I would pretty much cave when any objections came up and maybe despite ourselves the product was good enough we were able to get to that Milestone but when you're still setting it up you want that direct feedback line and if I build something that I think is going to be amazing and it's not I don't want it to take two weeks to filter back to me I want to just
be told directly from the customer um what's working and what's not so I think in that kind of environment it was pretty clear when it was time to hand it off I mean a million is kind of like an arbitrary number but what we were um what we saw was the process was starting to become repeatable it was we started to look at things like cycle time how long does it take to close a deal what are the common questions that come up what are common payment or pricing objections all these kinds of things I
wasn't really learning anything new by doing it anymore so that was a good sign that it was probably time to grow up let somebody else take that over over and then hand it off how are you generating leads how are you finding these customers so the moving Market is very networked so we found trade shows worked really well for us if I have an office in San Francisco you have an office in New York we're not really competitors like if someone's moving across country I may hire I may have my crew go pack up the
home on the origin and then your crew goes on the destination so what we found was going to these trade shows where all these folks are at and then referrals around you have a happy customer you're able to improve their top and bottom lines finding out who do they tend to work with and kind of working that angle has worked out pretty well for us but I think it just comes down to finding who's hungry for the value you're providing and how do you bring it to them and what we found for us is movers
are all over the world but when you have a conference everyone's in one room so that worked out great for us yeah and it turns out that events and trade shows have turned out to be a great great growth channel for your business is something you still do today I I think that I'd love for you to explain like how you were setting things up in a booth and and helping people experience you know Yambo rather than just telling them about it but I think it's also funny because you know in your book which we'll
we'll talk about in in a in a couple of minutes the first thing you talk about is like you know having a booth at an event and it was like 900 100 bucks and it's like do we really want to spend $900 on a booth right and that's the reality for many early stage startups right it's that's a lot of money um but it you know it it turned out to be a a good bet and uh you know a great way to meet customers and and generate sales uh but yeah just tell us about
like you know what was that Booth experience like what were you exactly what were you doing sure so year one you're absolutely right sponsorship was $900 I'm an engineer I did the math I said I can sit at the bar and buy $9 beers for 100 prospects and it'll be the same as getting this booth we didn't have the product yet so we did that second year the product was a bit more mature the venue actually changed the rules and said you can't just freeload in the bar area unless you have a pass so we
did get the booth there and what we were finding is people were generally interested but skeptical because a lot of these folks have been doing surveys inside people's homes for 20 30 40 years so to come along and say oh I have ai that does it people would kind of roll their eyes and say yeah right so our booth was very simple um again I never designed a booth before probably wouldn't pay me to decorate a room or anything but we had that idea in mind around people are going to be interested but skeptical so
what we did is we flew out to the event was in Florida so I'm in San Diego fly across the country took an Uber XL the big like uh minivan comes picks you up went to TJ Maxx and just bought some furniture we got a sofa chair a love seed a or a little nightstand a lamp and the booth was just putting the furniture there and when we told people what we were doing they would say oh really and I just hand them a phone I'd say yeah point it point it at the furniture and
you'll see the results right away and they'd go and they' do that and then like their faces it was cool it was like you're a magician almost like their faces would light up and then they'd start um objecting well of course you you picked that furniture so I I brought the receipt and I said no look this was purchased like 45 minutes ago when I was putting this demo together back in my office I had no clue what I was going to find I just wanted to see what would fit in the Uber and what
we found is that like being able to do it live and be real shows that it's you're a credible person and that you're not pitching vaporware and um that that kind of experience um we've had a couple trade shows like that in the early days where uh there was one time we even paid for it we're in the black before we even went back home because we closed enough deal just from from that like on the spot convincing but I just think it's being intellectually honest being able to be willing to do it live and
it comes back to our engineering routes around we're a technical company and we stand behind what we do and is it the best way to get sleep the night before absolutely not but it makes for a really convincing demo just to to do it real and do it live yeah that's great show me don't tell me right that's exactly what you were doing love that okay uh we should uh we should wrap up uh let's get into the lightning round I've got seven quick fire questions for you uh so whenever you're ready okay uh what's
one of the best pieces pieces of business advice you've received just get started you don't really know what you're going to get told until you actually do it so don't don't convince yourself in your head just get started what book would you recommend to our audience and why I think 0o to one by Peter teal is a good fundamental Exposition on startups and how to how to change an industry and disrupt the world I think any any founder should read it if they haven't already great and then we also got to mention your book you
you wrote the book called grow up fast lessons from an AI startup I got got one right here awesome so people can we we'll we'll talk about where people get that in a second but uh how did you find the time to write a book a lot of little a lot of little things I um I was disciplined I didn't binge I was disciplined I booked 90 minutes each morning before the workday so around 6:00 to 7:30 in the morning and I did three days a week cuz I figured five was too ambitious and it
took about a year um but what I was Finding was there was just so much happening in the AI space I felt like I had things to share I was repeating myself a lot to like new managers who were hiring things along those lines so I wanted to take the time to package it up and and share it with a wider audience yeah love it what's one attribute or characteristic in your mind of a successful founder I would say resilience is key is that anyone can conquer the world on a good day but to be
told no to have a setback and to be able to brush your ego aside and figure out what you're going to do about it I think that's what separates true Founders from people who are just interested in startups what's your favorite personal productivity tool or habit this is going to sound really low Tech but my to-do list is I email myself and I use inbox zero I've tried every other tool on the planet but it's just so hard to beat and I'm in my inbox all day anyway yeah what's a new or crazy business idea
you'd love to pursue if you had the time I think there's a lot of um non Tech areas where AI can be impactful I would love to open an art gallery powered by AI or of these industries where they traditionally haven't been served but you can take a new and interesting angle on it again I think I got time to write a book I don't think I have time to do that today but maybe 10 years from now we'll see what's an interesting little fun fact about you that most people don't know I spent 5
years living in Vermont and I grew up with two llamas and um I it's one of those things you got a show don't tell so I had to go back to my parents house last Thanksgiving and scann some photos because nobody believed me so I had to be able to have photos I could send that one that's funny uh and finally what's one of your most important passions outside of your work I've got a family got three kids all under the age of six so um don't have a ton of time left over after hanging
out with them but um love the outdoors was just um out in a cabin in the woods with them last week um and uh I just think spending time with uh with family hanging out doing probably boring things that you wouldn't want to talk about on a podcast but um meaningful and fulfilling things with uh with close friends and family I got to say say you you you you always struck me as a very chilled guy for somebody working on a startup and having three kids under six that's a lot of stress there it's it's
a learn learned skill yeah I think me freshman year in college was super not chill and you just kind of learned that you learn to trust your problem solving skills as you get older is that it's not like I've seen it all before but I know how to handle it if something comes up yeah okay great so Zach thank you so much for joining me um and also it's your birthday today so happy birthday I appreciate you making the time today if people want to learn more about Yambo they can go to yo. a that's
ye mb. a uh if people want to check out your book they can go to growup fast book.com or find it on Amazon we'll include links in the show notes and uh if folks want to get in touch with you what's the best way for them to do that probably the easiest is find me on LinkedIn Zack Ratner or you can type in Yambo it's not hard to find me but I'm on there almost as much as I'm in my inbox so feel free to send me a note sounds good thanks man I appreciate you
making that time uh great conversation congratulations on uh everything you guys have accomplished so far and uh I wish you and the team the the best of success thank you so much Omar happy to be here cheers
