Inside Gong: How teams work with design partners, their pod structure, autonomy, trust, and more | Eilon Reshef (co-founder and CPO)

21:44But it's your responsibility. So we're not going to quote unquote punish you. If you decided that, you know, you kind of took it an opinion from a customer and went ahead and did it. It's your responsibility to decide, you know, do I know enough? Do I need more input? How up do I go? So it's, let's requires them to think, you know, how confident am I in my decisions? So is the way is the culture basically you give them feedback and advice and the teams can operate the way they want. They can build the features. They think they're important work with design partners that they think are important.

22:18Yes. And of course, you know, you are expected to solicit feedback, right? So if you're going to build your own thing for six months and it's going to be, we're going to have, we're going to review it along the way, of course. But we expect you to initiate a review. You have like a, we have about a weekly session. We can bring up your reviews. But it's not as forcing you to do it. You have to bring it. You have to solicit it. And you have to sort of drive a process. This episode is brought to you by Vanta. When it comes to ensuring your company has top -notch security practices, things get complicated fast.

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23:31Is there an example of a product or a really important feature that came out of this way of working where a team just like, I, you don't think it's a good idea. I'm just going to do it anyway. I don't think it goes up to, to a whole product. It's, it's kind of very hard to, because you got to have resources to build a whole product. But I do think there are substantial features that, that came out of it, even sort of the kind of the AI fine tuning example I gave you before, is like something came up in a hackathon and people were like, let's start to build it, let's incubate it, and then they come move forward.

24:01Of course, we have to give them resources at some stage, but it wasn't like a top -down let's do this. It was more like, hey, we're trying it out. Hey, we need a couple more resources. We're trying more and in some stage, we realize it's super important. And then we kind of, quote unquote, funded it completely. So when people listen to this, some product leaders might be thinking, oh, I want to work this way. I want to give my teams more freedom or trust. What do you, what needs to be true in your org for this to work well versus it become chaos? Firstly, use a leader and need to sign up to like, sort of let go a little bit, not control everything.

24:35We link to sort of make some more mistakes than maybe you'd make otherwise. So that's the one thing. I think the harder thing is sort of, at least for me, is you also have to sort of get your peers on the same boat, right? Because the head of sales is going to ask you, hey, what's happening? How do I know what's happening? If you don't have a control over every feature and the CFO is going to ask you, hey, what's the, I don't know what if they are or are of this or how do you justify those type of decisions? So there has to be some fundamental trust within you know, you're in your team, you're in your colleagues to, to at least experiment that way.

25:14And of course, if you do an ongoing basis, you lose some visibility. And I think that's maybe one thing you got to acknowledge, right? Because if you give people more control by definition, you're going to have less visibility what you're doing. So give a little bit of visibility, hopefully get the benefit of higher velocity and higher what more are low or, you know, engagement from people. And that should result in better products as well. I love that. That's a really good example. With the sales example, which is great. Do you encourage the sales folks to talk directly to the pod to ask about these sorts of things?

25:47Or do you discourage that sort of communication? Yeah, I think sales from my perspective are part of the virtual pod, right? So the court pod is, as I mentioned, a product engineering, but part of the virtual pod is there's product marketing, customer success sales. In all fairness, you know, sales people are usually busy doing their work versus actually sitting with us and helping us kind of, is this going to sell? Did you hear it from customers? The type of questions that product managers usually do want to get. But if they're happy to spend time, they would be very evil. Coming back to the design partner way of working, does it feel crazy for companies not to operate this way to not work this closely with design partners on new products and features they're building?

26:31I wouldn't go back, right? So I think it's just like, even like, I hate terms such as risk. That's a very like, I don't know, like up a big use term, but just a risk of building something you're not going to know if it's going to get used. And I was asked by a sort of a very senior product manager of a very successful big SaaS company. It's like, why do you even do this? I'm like, what do you mean? We launch products and then we see if people like them. I don't think that's a great idea because in that company, successful, bigger than God, but at the same time, I just think it's leaving too much in the hands of, I would even call it luck, right?

27:06Because how do you know? Yeah, like I was thinking, it just feels like a cheat code and just feels like something a lot of companies can learn from how you all operate there. Something that has come up a bunch, so far in our conversation is your focus on speed and optimizing for velocity. Something that I've heard about you is that you're really big on just making really quick decisions, even like one way door decisions that are really big. Your philosophy is just make it quickly before you have all the information necessarily. Talk about that approach. That's maybe a little for a person I think, but I would encourage people to look up in Google, there's maybe I do a spoiler for it.

27:43Isaac Asimovie, the science fiction writer, I think beginning of last century, and he has this like a short story that the machine that won the war, so you can look it up. It's a fun story, pretty short, but it's basically the computer, the big computer at the time supposedly won the war, but the only reason won the war is because they wanted people to trust this superhuman machine, but what they realized the machine was just giving crap, just like our anemonesination. So the head, the person, president, whatever it is, basically ended up saying, I end up tossing a coin, but people wanted really believe that this is a smart machine thing that's going to help us win the war.

28:19So it's kind of obviously a funny story, but I think there is truth to it. It's many, many decisions when it's not a close call. It's like, should go, should go open an office in China right now. Well, probably not. There's so many reasons why not. We don't really be baited, but should we develop feature A and feature B and you look at them, they're kind of the same, I don't know, call it same value or same cost or whatever. However, whatever kind of mental framework you have for deciding, you end up being like 51, 48, 49. No decisions going to be like super wrong. So yes, you can try to bring in more data and you can try to sort of like bring more people, but like both decisions are okay.

28:57So just go ahead with one. Hopefully it's not like a huge, a huge mistake. I'll tell you I had this discussion with my co -founder, I meet with the CEO. And a few years ago, we're considering buying a company. And you know, it's like pretty strategic decisions, right? And we're like, I know there's pros and cons. We're like on the fence there. And we end up not buying the company. We kind of look up gone and we haven't bought like big companies. And I asked him maybe it was a couple of months ago. It's like, what if we had bought that company? Do you think we would have been in a radically different position?

29:30He was like, no. So it's like, I mean, it could have been better, it could have been worse, but it would not have made a huge difference. And the reason is it was a 51 -49 decision. It wasn't a 70 -30 decision. So it's hard for humans to make decision. You probably know, there's experiments that show it's almost like running or jogging or doing something that is a physical requires your physical capacity to make decisions. So just make it, I know it's hard that you want to postpone it, but just do it. It's such a freeing way of thinking about it. It's interesting because there's been recent conversations on this podcast where Spotify has this kind of value.

30:06They call Talkest Cheap. And it's meant to be a virtue. Talkest Cheap, so let's just talk a lot before we make a decision. But it's specific to Spotify because there's like a lot of regulatory challenges. And if they make it a big decision, it's a long term. It's like they put a lot of effort into it. So it's interesting, there's such different ways of operating. There's like, let's just talk for months and make a decision versus we're just going to make it and it'll be fine. Yeah, of course, like big, big one door. Yeah, I mean, this is of course, you're going to spend more time on, but people tend to overthink I think decisions.

30:42I also found out personally, the quality of my decisions, if you sort of wake me up in the middle of the night and ask me, what do you think about X? And I'm going to be like, I have no idea. I'm slipping. And then you're like, you know, you've got to force me into decision. I'm going to make a decision. Now you're going to give me two weeks to ponder over it. I don't think the quality of the decision is going to be much, much higher, which is maybe person, could be personal. But that's at least what I found out over my too many years of existence. So I think something that's probably necessary for that to work out well is having a deep experience in that space.

31:14Like you've been at this for a long time. So I imagine your instinct often is trained based on your past experience of the market and customers. You feel like that's a necessary component of trusting your gut and instinct on these sorts of decisions. Yeah, of course. You got it. Some stage note you're doing. Yeah. If I were now to make a decision around, I don't know, entering a different space, there's no way I would be like, yeah, let's flip the coin like the Asimov story and go for it. I take it, I go to a conference, learn it, whatever the thing is, and then make it a decision. But most of the decisions all of it make on a day -to -day basis is now our domain of expertise versus like totally new statistics.

31:46Awesome. Okay. Let's talk about AI for a bit. You guys were very early on AI. You were working on, basically, AI was like your product was built on machine learning back then, what it was called. Before it was cool and everyone probably thought it was like a waste of time and like, no, it's never going to work. Now everyone's building AI, building AI into their product. Would have you learned about working with AI over the years that you think people maybe are not yet aware of or that will likely cause them pain that you can help solve and avoid for them. Yeah. Funny. When we launched GONE, we didn't use the term AI because people thought it was bad thing.

32:23It makes wrong decisions or they just thought it was an action item at Acroony. When we found it going, I was in sabbatical and actually went to this deep learning course because I was bored in on fairness. After that course, I ended up buying a video stock, which I wish I had kept up until now. But I did send an email saying, hey, this is the next thing. So we understood it's the next thing. Of course, we didn't know it's going to be an LM and GPT and other acronyms that evolved over the years. And probably in now that we're talking about the end of 2020, four -ish, I think people should not go from one extreme, which is, hey, we need a bunch of data scientists for every small project, which was the case five years ago or three years ago, to an other extreme, which is, hey, LM is going to solve everything because LM has done so with you.

33:14We use LM's over the place. Most companies have developed AI kind of stuff for use LM's. It's a great thing. But at the same time, don't assume it does everything. You're seeing some need some of the core competencies of AI. So you do want to have expertise, people who actually know what they're doing and help guide us PMs around, is this something that can be built or no? Because if you're going to spend many, many hours on asking an LM to do, I don't know what, like in a case of gone, for example, tell me what the good sales cycle look like. It looks like LM's don't do that. It's just like maybe something else does, but we have a team prediction model.

33:55LM's cannot predict these because it's like very, very specialised. So I think you need to still have expertise. You still want to have some measurements. So yes, version one, you can just go to an LM and say create something, I don't know, whatever. But if you don't have measurements, like in the old machine learning, whatever metrics you use, you're not going to advance. You're going to have V1 and they're going to have V2 and there's no way to know if you've made a progress. So we kind of pay a lot of attention to, we have people who are going to specialise, you know, how you measure this LM system, which is kind of the one, using chess as well.

34:28And we do have experts who kind of help us make the right decisions. You can make a very, very good progress without these. But I think there's a glass ceiling if you don't like figure out how to kind of create a more operational rigor on this whole AI thing. So what I'm hearing is don't assume you can just outsource all your AI magic model building to the foundational model companies. You need to have your own AI expertise and how expertise. Yeah, or even if you end up outsourcing the core work, at least you have to have the expertise to understand what is doable, what is not doable, what's the right way to approach it, what's the input you give to the LLM, how is this going to be good quality or bad quality?

35:08There's even like, if you just take the product management aspect, if the LLM gives you something that is 90 % accurate, or I don't know, people are going to think it's good. The products are a little different than if it's 50 % good. So just the way you even think about it, the way I think Figma calls their AI feature like first draft, which is a term I like, because they kind of realise it's not best, it's not great, but it's a good first draft. So if you know what it is, it's easier not just to name, but how to conceptualise how to build a workflow around it, and what to train users to assume for it.

35:42And I think there's an expertise there that comes on top of an LLM, even if you just use LLM, so you can't afford or you don't want to go deeper. For folks that want to do this at their company, what are the functions that you have that help you do this? Slash skills of people you hired that you think are far important. So I think you still have to have this kind of quote unquote that data scientist role and data scientists could be in the company, it could be advisors as well, right? It's not everything has to be a full time in the company, and the role of a data scientist is help this help guide the company, right?

36:22Deal prediction model, is this an LLM thing? Do you need to build a model? If you need input, do you need how long it's going to take? Also, in our world, at least data scientists are the people who know how to measure these things. Is this model better? Is this model better? Is this problem better? Is this problem not better? And the judge then a little bit judgment, right? So when Gaul creates an account grief, at the data scientist is not going to know if that brief or this brief is the right one, but they can kind of guide us through what's the right tool set you need to sort of put it in front of customers and how do you measure this and what not?

36:53And then I think in the end of the day, you also need like this myth, you know, kind of now it's becoming a common, you know, the sort of the prompt engineer, the person who's actually working with the NLM and guiding them, that that is like a it's a bit of a technical skill, but you got to have it in it and it doesn't have to be a full -time person, but needs to be there needs to be that expertise of somebody who's actually optimizing things. Many, many customers tell us that you know, going to AI as well, it's more accurate than others. Yes, there is some combination of models we build from scratch fine tuned because we have AI expertise, but some of it is also how we kind of the prompt we give to the NLM is how much rigor we put into optimizing them and kind of finding the edge cases and and ranking them and improving them over time.

37:34If you want to get really good AI, you have to invest in it as well. As you're talking, I'm thinking about how the your pod model matches really well with this world of things moving so quickly, AI changing constantly, just giving teams autonomy feels like a huge advantage in this world where things are just changing weekly. Yeah, so we have a couple of maybe you know, it's three different pods, we have like an embedded AI specialist team, either as as specialist or a team or I don't know, a couple of people and then they kind of can iterate very, very quickly on using NLM's or using non -nLM's, you know, SLM's people now say a small language model, but whatever the thing is, they can iterate very, very quickly.

38:15Awesome. Okay, a couple more things I want to touch on. One is the spiral model. So you mentioned that you just went to learn deep learning on your own. You like went off to the side, I'm going to understand this new thing that everyone's talking about deep learning and you got really smart and machine learning basically really quickly and you have this thing you call the spiral model or the spiral method for how to learn something complex quickly. You wrote a medium post about this or block posts. What is the spiral method? How does it work? How do people learn things really quickly? But it really complicated.

38:47Yeah, I think it's even beyond just the speed, but also like how do you even know that you learn that you actually learned it? So it's kind of there is a mathematical kind of, or not physical concept called annealing, which is how certain kind of material kind of becomes the way it is and it's sort of the temperature goes slightly down, visually becoming crystal or what not. There is an element to this, I think in learning as well, which is you want to know what deep learning is, that you know nothing, you go find the person next to you and you're like, what is deep learning? They tell you something.

39:18Of course, you don't know anything because you just heard from one person and then I questioned, that's like, who else should I be speaking with? They give you three other names. I think in tech, we all tend to be to have like this very, very kind of cool ecosystem of people who are willing to help as long as you don't ask too much of them. So they speak with three other people and then they give you like other names and you sort of go around. And ideally at some stage you feel like, you know, first person you have no idea what they're talking about, you probably didn't even understand what they're saying.

39:44The fifth person you might understand 50 % or 50 % is like new. At some stage you're going to feel like, well, new stuff is 10 % or 5 % or 0%. I call it a spider, because it's going to go in circles around the target and eventually you feel like, well, I'm hearing the same thing again and again and you're like, well, if I heard it from three people, I didn't learn anything new. I'm sort of at the bull's eye. Of course, at the level I am. So I'm never going to be like a deep learning specialist in the same way that, you know, through data scientists are. But as a product manager, I know it probably as well as I can, given that, you know, everybody I spoke with at the time was not giving anything new at the level of the diet desire to this side.

40:22I love that. Is there anything you've been setting recently that you've either used this method for something else you're excited about learning that's new or on the cutting edge? Usually I kind of do this for, for kind of use cases within, within our customer base. For example, if I wanted to sort of, if you wanted to go after a certain persona or a certain use case for the product. So we had this notion of can we do a better job for a specific persona within sales, people who are account managers. So I would use a similar method. I talked to one account manager, I took to an analyst or whatever the thing is.

40:58And eventually when you start hearing the same thing, it's like, what do they care about? It's different than it sets salespeople like selling new business or different that contact center sellers. When you start hearing the same thing, you're like, okay, I kind of got to where I need to be. Now I can make decisions. I can always do another spiral and get one level deeper, which is, I don't know, to some user research go all in. But at least at the sort of the conversation level, I've got that where I need to be. I love how simple this is is you just start talking. Just find somebody to talk to you ask about this.

41:29No pressure. And then just, okay, who else did I talk to you? Just keep having conversations, spiraling deeper and deeper into knowledge and wisdom. Okay, one day I wanted to touch on, which is always stuck with me about your approach initially, when you were starting GONG, is your how you found your initial ICP, who to go after. And it's it's really funny how narrow you got when you all decided here's who we're focusing on for our first dozen customers. So I have the list here. So when you decided here's who we're targeting, here's the list of constraints. We're going to target people selling their product in the US in English over video conference using WebEx, which is the big one at the time.

42:13Selling software that is worth $1 ,000 to $100 ,000. And there was only 5 ,000 companies in this bucket. Can you just talk about why you found it was so important to get so narrow and just the power of getting really narrow, which is very counterintuitive to a lot of people where they're like, oh, we're just going to be for everyone's huge market. I think it's sort of the traditional I call it the bowling alley or whatever you want to kind of form a mechanism. Yeah, the crossing the chasm kind of methodology, which you want to start narrow, you want to create this kind of small point where people talk about each other and you can kind of light the fire in there.

42:54In my previous company, I by the way, I edit it, crossing the chasm and I told myself, nah, I can do way better than that. So we had one customer in, I think it was L 'Oreal or one of the cosmetics companies in American Express in Cisco, like different industries and there was no way we could scale it because everybody had their own lingo, the way they thought about the technology and whatnot. So by having a smaller set of kind of customers or I see kind of definition of customers, you can develop like much more focused and it's easier to light the fire because people move, right? At some stage, I think it was you're one into the business.

43:29We heard from a company that they interviewed a salesperson and the salesperson asked, are you using GONG? They said we are thinking about using GONG but we're not. Like, well, I'm only going to work for companies that use GONG and that's this sort of the power of a small pond with like companies that are like each other because you get this viral effect that is not commonly B2B but it's as close as you can because of those conversations. That other customer became a GONG customer literally because they interviewed a person who told them he's not going to come unless they bought GONG. You can do this if you have a wide market where people don't even talk to each other and there is an assumption that you're not like varying yourself at this market.

44:05I love because today, like I said at the very top of this conversation, you're just so ubiquitous. Like, everybody seems to be using GONG and I love that you started with something with those like seven, I don't know, different constraints to narrow down who you are going after and it's such a good example of the power of starting very focused and then expanding from that, which is what you've done. Okay, last question before we get to our very exciting lightning round. We have a segment on spot gas called Fail Corner where so many of these podcast conversations, everyone's always sharing all the successes, everything's always going great.

44:38Nothing ever goes wrong. In reality, things often go wrong. Can you share a story from your career or just the journey of GONG when things didn't go well, when there was maybe a failure and if you learned something from that time, what you learned? Yeah, I always kind of joke that in my previous company, we've done so many mistakes that if life limited you to a certain number of mistakes, I wouldn't have any left thing. I still do mistakes, but just so many. So every one of them probably done twice or and then it's like, oh, it's some stage is like, you know, third time's a charm. So the one I just gave you is like probably the worst is crossing the cas and you start a company, you have this like technology.

45:19I was thinking, let's go horizontal and that technology was whatever web integration something. Eventually ended up being an e -commerce content syndication or content management SaaS software, which is the right way to go because you want to specialize in a certain market, but initially just going all in was like just ridiculously not smart. And the other thing we did together was like that was the previous company started year 2000. So there was like the bubble, one of those very, very nice bubbles. So like, you know what, we actually got three customers admittedly in totally three different segments.

45:53Now let's go and scale. Now we only we get like we need like one salesperson, one is E and C kind of do what's now called product market fit. I don't know the term even existed there. And we're like, nah, you know what, investors told us he got higher more people. So we hired another 20 salespeople, all of them failing miserably because we didn't have a true product market fit, but even what's worse, we didn't have true focused ICP with like a very, very pitiful and a broad market fit. So if you sort of hear me talk about sort of how we started going, I mean, kind of there's the CEO and he kind of drove it out of that business strategy, but sort of me being sort of a cop out of there and definitely bringing the same.

46:30I'm not going to make that mistake again. I might do new and fun ones, but not that same mistake again. Awesome. Thank you for sharing that. With that, we reached our very exciting round. Are you ready? Sure. Let's do it. First question, what are two or three books that you find yourself recommending most to other people? There is a set of books. I think one that is sort of the starter one is I think it's called right now the ideal executive. People don't really know itself and manage the book out around a team and whatnot. I think the original version is funnily enough. I think it was called mismanagement, but nobody want a Bible called mismanagement.

47:09Much rather by a book that's called ideal executive because you of course are not mismanaging. You're the ideal executive altogether. So you're just reinforcing yourself. The joke society is basically kind of gives you the, it's trying to sort of define people by four characteristics. I think misnamed, but like are you an administrator? Can you like, are you, he calls it a producer, basically get the job done, integrated, which kind of brings people together. And the fourth one, it's basically kind of changed an agent, you know, kind of do a lot of mess and change stuff. Usually entrepreneurs can include that part of course.

47:46And basically his claim is like nobody does the whole for. He can maybe you're good at one, maybe okay at the other. And personally, I'm horrible in administration. So I obviously acknowledged that and I tried to sort of compliment myself. But so I think there's two things in it. Firstly, just those, I thought there was like the four good ways of looking at people as a manager as a leader of course. That's one. But I think even if you disagree with those four, just rekindle just like understanding that you want to look at the people in the organization yourself included. And it's sort of prism of, you know, key characteristics, and you can select a different framework helps you a lot with creating high velocity discussions with others.

48:27Because I can talk with somebody say, Hey, you're a P. So like, well, I'm not the PM and I, whatever the thing is. And that makes a discussion that is like much, much faster and more comprehensive as than just like trying to explain this from scratch. Like, Hey, you tend to do this and you might want to do this and you might want to strengthen that. So I'd recommend starting from this. But there's probably other methodologies you can pick and maybe kind of some of the listeners here have already had one. But that's one I like because kind of found it useful. And that's it's called the ideal executive.

48:59I think some pretty sure. Great. Any other books before we move on? That one's going to probably be very important. I like crucial conversation. That's going to mean the beating path. It's like how to conduct conversations with people in your organization. I think it's never bad to sort of read and immerse yourself into how to speak properly with other people. We have an episode coming up where we're going to share scripts and phrases to use to have better hard conversations. Yeah, it's good. Yeah, I'm excited for that. Slash scared. Okay, next question. Do you have a recent movie or TV show you really enjoyed?

49:35I didn't have TV like brought this TV for many, many years. So nowadays there's Netflix so you can find stuff. But in my case, in sort of a TV and movie tend to be pretty esoteric for an orange. So I've recently watched this British TV series called Slow Horses with Gary Aldmann. And it's a really kind of fun, you know, sort of funny spy thing, which I fall I'm using an intelligence at the same time. So some kind of comedies tend to be pretty kind of lowest common denominator. That one seems still fun and witty at the same time. So that's my latest that I kind of really kind of enjoyed watching even the third season.

50:14I love Slow Horses. It's like, I don't think it's that obscure. I think it's like one of the ones Apple promotes often. I will say the last season was not not my favorite, but the other two are. Yeah, I hundredth center green, which I said, even the third season was okay, but the first two are really, really good. Yeah, it's super fun. It's a force. It's like me like three tries to actually get into the show initially, because people kept telling me it's so good. And I started watching and it's just like, who's this old messed up guy just complaining endlessly, but you got to keep watching. Okay.

50:43Do you have a favorite product you recently discovered that you really like? I see him. You have a silverware caddy in your dishwasher, right? Oh, yeah, it's a poet like Forks and Ives. Yeah. The category. So that's my favorite product as a flageley. And I'll tell you why. It's a funny story. I lost mine. You can ask yourself, how can you, you know, freaking lose the like one of those baskets? And it was in the in the dishwasher, of course. And for some reason, I couldn't find it. That's like you have to be really kind of out of you might not find. Anyway, so I go to some Amazon or eBay or wherever I just buy a new one.

51:18And then of course, a day later, I find it's like a fence somewhere within the dishwasher. Now I have two. So this is my latest invention. If you have two of those baskets, you could put one of them in the sink and you can just like continuously load your cutlery or silverware while the thing is working or you haven't vacated it. So it kind of changed how we organize our kitchen with something that probably cost 10 bucks. No product managers ever thought about offering two of those with your dishwasher. I don't even try to upset anything of any of that. And I told you with some people, I actually ended up buying a second one and it was successful, which is the most ridiculous thing.

51:53It's like you spend 10, 15 bucks get something organized in a completely obscure and unintentional way. I'll give you an even crazier idea that a previous guest suggests Rory Sutherland has this pitch that you should have two dishwashers. Everyone should have two dishwashers because one could is your clean and one is dirty. And you just take your plates and things out of the clean one, use it and put it straight into the dirty dishwasher. And why are we just putting things away constantly just like go from one to the other one to the other? So there you go. Similar idea. Similar idea. I'm actually a thin box, though, a little bit maybe cheaper.

52:31Exactly. How is this an design for two dishwashers? Okay. Two more questions. Do you have a favorite life motto that you often come back to find useful and worker in life? Why did I use this going to sound funny, but it's actually really, and I use it and actually believe in it. It's not sure if you know for philosophers like Razer's like all comes Razer, which is basically. There's other Razers. Yeah, there's so many Razers and there's one that I think came in in some Murphy book or what not. And it's called Handelman's Razer. You can look it up Wikipedia or wherever. And it basically says it goes like never attribute to Melis.

53:08That which is adequately explained by stupidity. So it obviously sounds funny and it's trying to be funny. But it's so helpful because so often do we attribute like people's behavior, you know, thinking a company, a customer, I don't know if personal life sometimes to Melis like, oh, this person's not returning my calls because X or this person hasn't given me feedback or has given me feedback because of X. And it's sort of like we all, I think there's the saying like always assume well or with intent or whatever. And this is sort of the more funny way to sort of say that. Yes, the person is, and against stupidities, only a funny way to do it, maybe in a appropriate, but it's basically yes, they just didn't know, they didn't care, they didn't think about it, they weren't trained, whatever the thing is.

53:52And if you take this model new day to day life, at least I find that it's it's so true and so often true. That is, you know, funny but inspiring. I really love that quote. I think of it often when somebody's doing something that it's annoying me. Final question, you mentioned that you are from Israel, you live in Israel, you mentioned delicious food, hummus is one example, is there another Israeli food that you think people are sleeping on that you think you push to try when they have a chance? Israeli food has become a little bit, you know, kind of gotten a little bit to be in fashion lately.

54:25So people coming from the US to visit in the office are like, oh, Israeli food is so good. And I'm like, what do you mean it's the same food we've had for like 20 or 30 years? I think the taste changed because you kind of eat more healthy and less oily these days. Most of these Israeli food is sort of Arabic in nature or Turkey. So there's great falafel, great hummus, pita bread, Turkish delights of sorts. So a lot of those. And some very, very obscure and if you come to Israel and show Iran, some very less known food that only kind of special guests get to taste. What's that? What's one here?

54:59Okay, and say it here. You're not allowed to know. There is there's a thing called Sabih for example, nobody knows of it. It's people claim it came from the people who came from Iraq, but my wife's father came from Iraq. He's like, we've never seen this before. It's sort of pita bread filled with hummus and eggplant and eggs. Now maybe something else I have no idea. The heenie maybe I don't know. It tastes good, but it's such a weird combination and it's become a little bit of a thing. Nobody knows what the origin is. I think it's some, somebody made a mistake and gave it a name and now it's like ubiquitous.

55:31Hmm, but you are making me hungry. Elon, this was amazing. Two final questions. Where can folks find you if they want to reach out and learn more? Maybe ask some follow -up questions. And how can listeners be useful to you? I'm really available. LinkedIn is probably the best way. I tend to kind of read my inbox and LinkedIn and respond when I can. And then useful to me. I mean, if you want to come work for Kong, check out our careers page, of course. The product team is mostly based until I've even doubled in Iron -N. So maybe a little bit removed from most people, but there's sometimes folks in the US and sometimes non -products.

56:06Of course, Roj, we're hiring quite a few people these days. So we'd love to at least give us a chance. Awesome. Elon, thank you so much for being here. Thanks for inviting me. Bye everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or a leaving review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny'spodcast .com. See you in the next episode.