Alain Denzler: The Evolution of AI - A Journey Towards Human Interaction

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My name is Matt and I will be talking with Alain Denzler about human centric AI in sales and cultural considerations.

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Alain, I'm really happy to have you here today. How are you doing?

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Pleasure to be here, Matt. Really? Yeah. Good, thanks. How are you?

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Thank you, thank you. Fine.

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Busy with the podcast, as you probably know that I already mentioned, but with any further ado,

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I would love to start just to go straight away to the question, but before that you work for

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the salesforce, you worked for a really successful pitcher, really successful startup in Switzerland,

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and now you're building your own stuff.

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I promised yesterday, my colleague from Google that I will not mention AI too many times in

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the podcast because this is popular topic.

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But I think we couldn't get without it because you are building a startup around the AI.

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So maybe you could tell a few words about the company itself.

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Yeah. So get it AI, it has it in the name, right?

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It is unavoidable even if you just pronounce the name itself.

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No, we're building something that's going to change a lot of the ways that people interact with brands online.

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We've kind of grown up knowing this kind of online sales space as e commerce or like buying

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stuff was just always something you do alone.

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It was convenient 24/7 but it was more a search first experience.

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You mentioned Google before, they dominated that space there, and the websites of brands were

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mostly copying that and somehow all about getting you onto the site.

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They paid a lot of money for it, and then you're just left alone and you search and that's something

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that at get it AI, we're trying to change because it's not an optimal thing to do.

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And Picasso once said, like, I do not seek, I find now we'd like to go more to the find.

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So instead of googling it, you want to just get it.

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So that's what we help.

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We put digital humans onto those online spaces where brands want to sell things.

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And then all of a sudden you can kind of like miniaturize your brand ambassador, have all the

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knowledge that your best salesperson would have, and then have that represented 24/7 on all

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the channels that the brand services, right?

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So anywhere where the customer chooses to engage, that's where they will have that superhuman

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sales agent present to sell to them.

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And it works pretty well.

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So you showed me the demo.

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I have seen some demos, demos in the past from other I showed for one company and it looked

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really creepy in your case.

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It was like pretty realistic, I would say.

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So it's already nice I asked for beta. Right?

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Yeah. So it's still beta, but we are not doing the avatars ourselves.

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We work with partners there.

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And I think the point is that you want it to have to be indistinguishable from humans.

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There's this expression of uncanny Valley, I know if you've probably heard of that, and that

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just describes this creepiness you say you refer to, and if it's close, but just not close enough,

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sometimes it's better to stay away further. Right.

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So they make it less human so that it doesn't have this creepiness effect.

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But I think with the recent advancements in Gen AI, you've also seen the Omni, the OpenAI GPT

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four omni presentation where they were already hinting towards her with Scarlett, the sardines.

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You wasn't too happy about that one, right?

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Even though I think I read about it and it was quite legit. They paid actors.

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It was all other actors.

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So there's actually somebody losing out now on that one because.

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Yeah, that's quite easy to prove.

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They, they flew them all in.

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There's receipts, there's contracts and stuff.

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So this lady that has this, the sky voice, I'm quite certain it's legit.

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And, yeah, it's, it's, I mean, I would say 99% certain.

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You know, they made a public statement online and, and they have evidence.

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And this is something you, accounting wise, you can prove to. Here's a contract.

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This is the lady, she just wants to stay anonymous because otherwise, you know, you don't want

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to get, you just want to get the money if you can. Right?

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So she could, and that was a great opportunity for her. But, yeah, her.

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But it was obviously too close to Scarlett Johansson's voice. So that's the debate.

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I think that's going to happen now is how close in terms of likeness can you get with the big

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stars having a legitimate kind of like a voice double?

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Dad, she has a, she has the right to sell her voice and her likeness, and she wants to kind

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of make profit out of that, and then the big stars can block it.

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So that's kind of like a debate.

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Then, you know, I get the point of the stars and all the thing that happened last year also

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in Hollywood where they were like striking and AI and all that, and now this is the effect of it, right?

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And people coming in and saying, hey, we have likenesses.

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And then it just happens to be quite similar to your voice.

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So what are you going to do now?

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So I'm curious to see how that would be laid out by the legislative armored or I guess the courts. Right. Interesting topic to follow.

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Yeah, I fully agree. I was listening to all in podcasts on a why here?

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And they were discussing the scarlet jokes on thing.

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But definitely I think this will disrupt the market. It's the same.

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I don't know if you've heard of artists like Sting or like the police.

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They are selling the whole catalog or Bob Dylan of their music. Right.

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So for the realities that, I don't know, universal, somebody will get in the future when they

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are already not with us. Right.

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So I think it will definitely disrupt the market of the actors because they're super expensive, right?

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Yeah, yeah. But I mean, the point why I mentioned it is that the presentation showed really

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nicely how you can overcome that uncanny Valley. And they're not coming.

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They're calling it real time, it's close to real time with the voices.

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And then you can have this natural dialogue with all of a sudden this digital voice that is AI.

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And that's something that overcomes the uncanny valley.

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And that's where we position ourselves.

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We've not taken the stance of trying to go abstract and not making it like a human.

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We want to make it human because of that connection.

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And then once that connection is there, you can do way more things that before were just fantasy still.

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Yeah, cool stuff. So when I saw your website and you showed me the demo, I was already thinking

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how SaaS companies could do sales with that, like enterprise sales, because this is really expensive,

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you have all those pitch decks, you have a huge sales team, and with that you can automate the

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process, which is like you can cut the cost so much and have a repeatable, scalable quality of that.

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Yeah, 100%. So we're not starting directly in the software space, although it is directly adjacent

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to it and we're in commerce first.

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But I think what you mentioned is intuitively correct.

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We don't want to go replace humans.

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That's not the idea just now.

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Maybe at some point that will be on the cards. I hope not.

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I also like doing sales, but the current focuses on markets that are or in spaces that do not have a human incumbent.

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So imagine the commerce, but also software within software, not the enterprise sales teams,

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but the product led growth.

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Those guys don't have any money to spend on people that are actually present and having calls

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and booking demos and all that.

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They might have a very light touch approach, but even then it's still cost those we want to help out.

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So there we see potential and then you can scale it up.

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You can also look at channel sales and other things where there's a lot of these long tail,

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underserved market segments that then all of a sudden become serviceable with a digital human. And that's the thing.

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There's a lot of discussion around AI and replacing humans and losing workers and stuff.

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This is one of those areas where we don't have to do that because as a customer now, there's

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a lot of them that are getting left out.

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I was in pharma already there before and then at pitcher as well.

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You have to be very strict in terms of how you target and whom you target.

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We did lots of exercises around the world with local market teams with lots of data.

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You get in and stuff, and then you just go after basically 80% of your revenue, which typically

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in a retail setup comes from 20% of number of customers.

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And so you've got a long tail of 80% that gets nothing.

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No service whatsoever, no love.

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And so those are the ones that now all of a sudden can also get a face of the brand and interact

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with a digital human and have that service level experience that you would expect from major brands.

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You know, that's, yeah, it's astonishing sometimes how, how little love those brands give for

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the b two b space, that long tail. Here's our website.

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It happens to be a shitty website.

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We don't really care that much.

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Just go help yourself and off to the races they are.

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And your team, like you are fully remote.

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I would say your team is super distributed even across the US because you have a lot of guys

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in us, you have the co founders in us.

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And I'm wondering, because I even noticed that you have one ex googler from, I think it was Silicon Valley. Right?

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So how do you recruit those kind of, like, how do you recruit those guys?

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Like, at such an early level, especially, like, you know, it's really hard to build some kind

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of brand and at such an early stage recruit the people from like in the big corps, really famous

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corpse, like Google, for instance.

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So yeah, one of the co founders is like Xfang.

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So he was working, he was actually in the digital assistant space, since the digital assistant space exists.

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So it started in the founding team of the Google Assistant, moved on then afterwards to meta

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and worked on the whole kind of meta.

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Was it metaverse or something?

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Or the Oculus team there, and then now is at Samsung.

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So also in the Bixie team there doing digital assistants.

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And so that was somebody that we won over as a co founder and I, that of course then one leads to the other.

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Once that person is in and believes in a vision and mission, there's lots of people also from

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FAANG that want to join a startup that has such a strong disruptive power.

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That's all I can say.

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I mean, that everything else is really, it's the team, it's the dynamics behind that and then

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it kind of starts rolling.

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One more mentioned, the remote first setup really helps because a lot of the Silicon Valley

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companies have gone back to making people or forcing people at least into a hybrid setup or

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that be in the office two, three days a week at least.

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And so if you're the one that offers remote and 100% remote, you can all of a sudden get people

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that have actually installed themselves in other locations because they thought, and you know,

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the same guys that are forcing them back to hybrid actually told them during COVID hey, we're

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going to be remote first permanently, right?

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So yeah, if you adjust your setup of your family or your living situation or whatever, and then

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all of a sudden that changes again, then that's good for us.

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That plus the overall kind of like cutting the people last year, that was also beneficial for us.

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That's a really cool advantage, I must say.

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It was funny for me when I saw Zoom bringing the people back to the office, like, come on guys, you were telling me.

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Yeah, look at their share price.

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I think not all decisions they make are beneficial for investors, let's say.

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And I'm just wondering because you work on Peter, you worked in Salesforce and I think that

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the previous company was the Mercury.

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So like a lot of experiences and I think building the startup is kind of easier when you collect

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the experiences, especially with enterprises.

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So you have a good training, you have a good fundamental.

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So if you could mention about something, was it like helpful?

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Do you have some lessons learned that you think, like why?

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And now you think like this thing, this new venture will be successful because of the a, b and

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c, like lessons learned that I had?

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Most definitely, yes. I think the way of working that we learned at pitcher is something that's

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really good in this remote setup picture was already remote first before COVID hit.

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That was just how this is DNA of the company. Everything went through slack.

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That was our digital hq and then we had our project management tools and then some meetups and stuff and hangouts.

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That was something, that's something we can easily transfer over into the get it culture as

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well and which people appreciate very much.

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And that's something we've had a lot of people come in also volunteering, just working for free

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like internships or just people that were bored from their day job and they just helped out

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in the time and the spare time that they had very cool to see and they would come into our meetings

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and typically it's quite structured and how the things go about and they compare to other things

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they've seen and they're quite astonished how that can go about.

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So that I would say, yes, there's definitely transferability that we can bring into the team.

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Are there some lessons learned from the organization?

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Of course, you don't have to mention any that you say like, I would do it differently when I started my company.

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I don't want to do it this way.

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This is my lessons learned out of the, out of my previous experiences.

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So I think what we've seen is that what works best is that you don't prescribe too much of the how.

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Like I think a vision is good and where you want to get to.

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And if you have experienced people afterwards, they will figure out how.

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And that's something we've learned to a lot before.

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I think what we maybe, maybe I'll make a short pause in that thought and just make one excursion

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to the fact that at picture we were very much driven with what customers want and I call it customer capture.

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Even so, we went after the biggest of the big, like the top s and p.

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They're just used to working with agency like SaaS companies where whatever they say, like my wishes is their demand. No, I'm sorry. Sorry.

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My wish is your comment. Exactly. That's the right one.

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So that's in that setup, it's typically quite unhealthy and it does not allow you the same type

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of freedom that the teams also then get to do what they think is best.

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And that's what we're deliberately doing different now.

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And the instructions are clear that the target of the company is not to get the whales, but

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rather to get the more nimble players out there, like between 5 million and less than S and

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P 500, but probably not listed in the stock market yet.

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Some private company led by founders or something like that. That's what we're after.

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They're more agile and fast and sales cycles are shorter and all that that allows us then, and

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that's why I just made that excursion.

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Now back to the initial thought.

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That's what allows us to give that freedom of the how because we say this is the vision and

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then you guys figure it out and then we can still push back if it doesn't fulfill what we think

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it needs to be fulfilling.

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But I think that makes a lot of difference.

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And then you can have, I like that Spotify model.

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I know if it's coming into the ages now, that's something we weren't able to implement before, although we wanted to.

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And that's something that we're very much kind of like after now it's like just giving that

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freedom to the teams, having those squads of specialists that are doing stuff, having fun and figuring it out.

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That's what we've always seen also in the previous company, the best engineers and the best

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people overall, you get if you have interesting problems to solve and don't dictate too much

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how they have to solve it.

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And that's how you keep them at pace, so to say. Right.

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And you started the company during the recession phase. Right.

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So the big techs are laying off people, the money are really expensive.

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Like we came from hyper demand for tech into like almost like no demand, like the VC's are not putting the money.

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So it must be, must be difficult.

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But I don't know, do you see the influence of those events on the things that we are doing?

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Because you are in AI, so maybe this is the thing completely different.

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Yeah, we're definitely feeling that and that's also one of the main roles that I do.

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I'm at get it AI as founder.

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I'm also doing a lot of that investment thing.

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That's what I'm trying to push forward.

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So I do get that, that feeling.

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It helps to be AI.

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I think you get funds that otherwise others would not get at this moment.

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But I think for sure we did feel the interest rate hikes we are getting.

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The info that the funds that used to be like 300, 400 million in size are now more like 30, 50 million in size.

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And they have still the same amount of startups knocking at the door or more.

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Because Genai, there's a lot of people that want to do something there and so they have more

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people coming in and less funds to distribute.

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So it's harder, yeah, that we do feel, but we've been able to secure some angels and some big

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names in Silicon Valley as well in terms of venture capital.

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So I think that's something that at the end, if you show that the team can deliver, that you

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can build traction, then my job as getting those investments in should also be easier.

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But generally I would say there's still money that wants to fund good teams and good ideas,

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but it probably has to have a bit more traction to it than it used to have.

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So what are your goals?

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Let's say in the next twelve months do you go to have paying customers or maybe active users on ebeta?

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What is your roadmap and Uber goals?

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So we would like to launch the beta program next month. So that's quite close.

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The team has been working hard to get that to fruition and with that also we should be generating revenues already.

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That should help also get in the funding side. Makes my job easier.

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And then basically once you have revenue you've proven product market Fitzhen and from there

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you can start growing the customer base.

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So we've been also getting a lot of traction from brands incoming and asking if we can.

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There's word of mouth already people are spreading the word.

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So we can start choosing also whom to work with and to make sure that we're really focusing

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on that ideal customer profile and not having that customer capture that discussion with Pepsi.

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And yeah, it went exactly in that direction where they were kind of expecting us to put in lots

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and lots and lots of work before they even select anything to do with us.

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And that was like we basically told them that's not what we're interested in and they seem.

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So that was the smartest thing a startup told us in the whole year so far.

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Because typically startups are very eager to get them as a brand and then they go all, they

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spend 100k only on just lawyers and legal reviews and all that stuff.

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So it's quite a huge big pre investment to get them going.

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And then you're basically a slave, right? Yeah.

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So that's the Uber goals will be generate like get the platform launched, generate revenue and then grow simple, right? It's not that big.

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And the KPI's are also quite simple since the setup is like being a giant sales rep, like being

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the sales rep version of her.

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That's kind of how you can imagine it.

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And so sales reps are incentivized on generating sales and our whole team then knows if they

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have any spare minute and they should invest it into optimizing the way that we sell.

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Nice, I think makes a lot of sense.

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And the games of angel investing, they change a lot.

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So what I noticed now on LinkedIn, because I invested in some companies and if I'm getting the

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pitch, one of the first sentences is like the amount of monthly recurring revenue, right?

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So I haven't seen this before and I'm lit tech maybe like 13 or 14 years.

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So it makes a lot of sense right now and during the tough times.

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But regarding the you already gave really good tip regarding the clients right to not to attract

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the companies like Pepsi at the very beginning because it's really costly.

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You are still small, you probably don't have the lawyers to, and you probably don't have the

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time to close the deal in one and a half year or something like this. Right?

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But maybe could you mention some pain points or challenges, especially for the startups in AI

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world that you have that you see maybe something that not many people are talking about from the outside?

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Do you see some challenges, especially in this space?

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I think what's interesting, how it evolves is the pace. The pace is extraordinary.

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And I think the thing that people don't realize, a lot of the apps that we're building or being

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built last year were basically what people call wrappers.

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They just kind of have this LLM and then there's a little wrapper around it, then it looks cool.

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You know, those get replaced very quickly and don't have any moat.

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And maybe the moat thing is that the discussion in itself, I'm not a big fan of discussing modes

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for pre seed companies, but what I do think is that when you look at what used to be sort of

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when you look at that pace, you have to make sure that you don't become irrelevant with the

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next update of the models that are coming out.

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And they will inevitably come out and they come out at a certain pace.

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And it's interesting to see if that'll kind of establish itself.

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Like with iOS ten, 1112, every year one new one.

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I think it might come into that kind of pace, but let's see.

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But the point is that with that pace,

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how we try to do it is that we try to focus on things that used to be impossible without AI,

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and now they've just become like very difficult.

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So things that were hard are now easy.

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Those you probably shouldn't do.

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That's just something that'll be done by some other bigger platform, horizontal player or so.

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But if you like, within our space now focus on a niche and then have that very difficult problem

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that used to be impossible, then we believe that you can have quite a good existence and you

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don't have to be afraid of the next model coming out.

24:09 - 24:15
And I also, what I think is quite wise, I heard that from Sam Altman actually, is he thinks

24:15 - 24:21
the most investable companies are those that ask him eagerly when they are finally releasing

24:21 - 24:26
the next update of their model and not the ones that are clinging to their chairs before the

24:27 - 24:30
announcement comes out, because they're in that impact zone of the big ones.

24:30 - 24:32
We try to also stay clear of that.

24:34 - 24:43
I'm wondering regarding your soap, because you are one of the, one of the three, your three

24:43 - 24:45
co founders, four co founders, right?

24:45 - 24:50
So everybody brings something to the equation to make it successful.

24:50 - 24:55
And I'm wondering, what are your superpowers? Right? What do you think?

24:55 - 24:58
Like why this company will be successful?

24:58 - 25:03
Because of your skills, like what you have learned in the past, maybe? Yeah.

25:03 - 25:08
Well, maybe too modest to answer that one.

25:08 - 25:14
With the superpowers, I bring in vision, I bring in the human touch.

25:14 - 25:20
I like making people also feel comfortable when they're coming to the company

25:23 - 25:28
and like I said before, giving them enough space to be their best.

25:29 - 25:36
I've always thought that it's ideal if you can bring in people that are smarter than you because

25:37 - 25:41
you're as good as your team is, and if your team is better than you are, then you are also automatically,

25:41 - 25:43
in average, quite a lot better.

25:43 - 25:46
So I always try to follow that principle and it's not let me down.

25:46 - 25:52
It makes the work environment a lot more appealing for all the people involved and it makes

25:52 - 25:53
it easier to reach your targets.

25:53 - 25:59
I mean, I think the whole thing with the people being the most important resource, it holds true.

25:59 - 26:05
You just have to really make it like something you live and not just something you put on a slide. It's all about that.

26:05 - 26:10
And if you get those people, the right ones in, then they can do magic. And that's pretty cool.

26:10 - 26:15
So I like to be that person that enables and then lets the others do the thing so I don't have

26:15 - 26:17
to hand hold all the time.

26:18 - 26:20
We've got a really good product team together.

26:20 - 26:23
We've got the experts in the growth area there.

26:24 - 26:32
So I'm more on the fundraising side, trying to, trying to get the people, like you said before, it's a challenge, right?

26:32 - 26:37
But they are just kind of being able to, you know, have that vision, have the selling skills

26:37 - 26:41
as well to convince people to buy into your vision.

26:41 - 26:43
That's what I think I do. Quite okay.

26:45 - 26:50
And I was looking for lessons learned that we could share with the audience.

26:50 - 26:58
Like the people who are listening to the podcast always like to have the lessons learned that are not so obvious.

26:59 - 27:05
And like in your case, I really like, recently asked this question, what was the hardest thing

27:05 - 27:07
in your career and what you have learned from that?

27:08 - 27:13
So I think one hard one was the actual sales job out in the field.

27:13 - 27:18
Like going from door to door every day for one and a half years, going visiting doctors.

27:18 - 27:19
First of all, it was like doctors.

27:19 - 27:22
And I was just an MBA graduate or business admin.

27:22 - 27:27
Like, I did business and I graduated, and I went into a sales job selling medicines to doctors,

27:27 - 27:30
and I was like, how am I going to do that? That was really hard.

27:30 - 27:36
And it just, you know, took some time then to realize that they're also just humans.

27:36 - 27:43
And they might have been able to, like, learn the encyclopedia by heart when they graduated.

27:43 - 27:47
But then in their everyday life, they're very much kind of, like, doing, you know, one patient

27:47 - 27:52
after the other, and they're happy to have some academic sales guy in between.

27:52 - 27:54
That kind of brightens their day.

27:54 - 27:59
And they don't know within that whole spectrum of medicine, everything there is to know.

27:59 - 28:04
And within my areas of, like, you know, I was doing diabetes, endosteprosis, and asthma and

28:04 - 28:06
stuff, I knew quite a lot.

28:06 - 28:08
I knew a lot about the area.

28:08 - 28:13
I knew a lot about what other doctors think as well and how this is being done in practice.

28:13 - 28:18
And I could share that across, and it was really hard, but you kind of grow into that.

28:18 - 28:20
I'm not sure if it's the hardest thing I've ever done.

28:20 - 28:24
I think the other challenge I had was then within picture.

28:25 - 28:32
We had a hard time while we were building a really good team, we were building a cool platform,

28:32 - 28:38
but we were then kind of, like, redoing one really core part of it, which was harder to scale.

28:39 - 28:43
And I had just brought in some folks in India.

28:43 - 28:48
We had some very specific engineering talent we needed.

28:48 - 28:53
And it just happened to be that those people were all in Ahmedabad in India, because that was

28:53 - 29:00
like, the headquarter, engineering headquarter of one of those companies that had that kind of a knowledge.

29:00 - 29:09
And so we had a team there, and I had before worked mainly with european, polish, a lot of polish engineers.

29:09 - 29:17
Very reliable, very, very kind of, you know, logical and planning and, like, you know, communicating

29:17 - 29:21
also clearly of what expectations you can have and where they're uncertain.

29:21 - 29:27
And then when they commit, they deliver, or if they don't, then, like, that's something they know. Typically they delivered.

29:27 - 29:32
I've never had a point where I had team members that just didn't deliver, even though they had promised something.

29:32 - 29:38
And then with indian culture, that was really hard for me because, like I said, I'm typically a trusting person.

29:38 - 29:43
I hire people that I think have the right merits and then let them do the thing and trust.

29:44 - 29:47
And there I was, let down in the trust because it was a cultural thing.

29:47 - 29:48
I didn't know about that.

29:49 - 29:55
The cultural thing was that they would always just confirm whatever I'm asking from them and

29:55 - 30:01
try to look good in terms of the times, the dates that they set. So it's nothing.

30:01 - 30:04
It wasn't this logical, rational approach.

30:04 - 30:10
It was more about this, like, making your boss happy thing, and I fell for it, and I trusted

30:11 - 30:12
that it's going to work, and then it didn't.

30:12 - 30:14
And then I said, okay, by when?

30:14 - 30:16
And again, that didn't work.

30:16 - 30:21
And so we went into a bit of a tailspin there with some of those core elements which we had hired.

30:21 - 30:26
And to rehire someone, you can fire them, of course, which we then occasionally did.

30:27 - 30:32
You could rehire, and that just takes a lot of time, and in certain project scenarios, you don't have that time.

30:32 - 30:35
So we were a bit stranded there, and that was hard.

30:36 - 30:42
And that was the first major setback that I had in a project in my whole career.

30:42 - 30:48
And so we really had to take a step back and just also manage expectations with a customer and

30:48 - 30:54
then go back to the drawing board and kind of redesign that part, which was just kind of conceptually

30:54 - 30:59
done wrong from the start there, which the team was owning, but then kind of, like, over promising

30:59 - 31:01
on and not raising the flag.

31:01 - 31:06
I think it's always important, and that's the culture I want to live, is like, it's totally

31:06 - 31:07
okay not to be able to do something.

31:07 - 31:11
It's okay to do mistakes, but it's very important to kind of, like, raise the hand early.

31:12 - 31:17
Like, if I say, hey, here's a task to do, I expect people to be like, hey, I can't do this,

31:17 - 31:19
or, how should I do this?

31:19 - 31:21
I don't have the competency now.

31:21 - 31:22
If you want me to do this, it'll take very long.

31:22 - 31:28
Or you get somebody else to do which has the competency or so, but just not saying anything,

31:28 - 31:32
silently accepting it, and just being like, oh, shit, I'm going to have to learn this all on the job.

31:32 - 31:38
It'll take me forever, or I'll have to work all the weekends or so that's on you.

31:38 - 31:43
That's the part where I expect them to speak up and be like, nope, maybe not the best.

31:43 - 31:44
Or then just make me aware.

31:44 - 31:48
And you can still take the decision then and be like, yeah, okay, you can still.

31:48 - 31:52
I'll have that as a learning assignment, and I'll just factor that in.

31:52 - 31:58
It'll be less reliable code, it'll be less reliable timing and stuff, but it's cool.

31:58 - 32:02
Other times, you can also take the decision being like, no, okay, in that case, thanks for letting me know.

32:02 - 32:03
Let's do it with somebody else.

32:03 - 32:05
There's nothing lost in that part.

32:05 - 32:10
So, yeah, that was, I think, some of the, some of the learning I took out of that was this.

32:10 - 32:16
There's the strong cultural element to it, which it's not something you can read about.

32:16 - 32:21
It's something you have to experience, I guess, but having the awareness of it probably helps.

32:21 - 32:30
So we've taken those learnings, and with the new company, we're not going as broad geographically,

32:30 - 32:37
because I think it's good to have certain centers where you have, even if it's remote, like you do engineering gathering.

32:37 - 32:42
There was an engineering gathering in Bucharest, and this seems much easier to have people then come together.

32:42 - 32:47
And even if you remote first, you should also have these touch points every.

32:47 - 32:51
I don't know how often, it depends how often you can vary, but every quarter or so, every half

32:51 - 32:57
a year, you should see each other just to have that human touch as well and the connection that you get from that.

32:57 - 33:08
So that the learning one is, let's say, the cultural learnings, the number two is then having

33:08 - 33:15
certain hotspots where you focus on maybe where you also know the culture enough to not tap

33:15 - 33:20
into too many traps or have too many learnings, because one of the most valuable things we have is time.

33:20 - 33:27
So if you're losing that time and resources, both of it, then it's a learning block where you

33:27 - 33:34
might overcompensate the cost advantages of going, let's say, to India or to, to Philippines or something like that.

33:35 - 33:40
And then, yeah, from an engineering perspective, not going too broad. Also in time zones.

33:40 - 33:48
And with us and Europe, we got two major time zones, I mean, continents, of course, with multiple time zones.

33:48 - 33:55
And once you go broader, once you also have Asia involved, then it starts being the follow the sun principle.

33:56 - 33:59
There's always going to be darkness somewhere, and somebody's going to have to put in really

33:59 - 34:03
long hours at strange times, and that just gets more complicated.

34:03 - 34:10
So if you want close collaboration, the world is kind of flat, but still has some edges. Right?

34:11 - 34:13
So there's limitations to it. Yeah.

34:13 - 34:21
So, and the last question, last but not least, I always like to ask about the books, resources,

34:22 - 34:29
Maybe conferences, podcasts, something that has been really influential and beneficial for you as a leader.

34:29 - 34:35
So you say, like, you had this aha moment after, you know, Learning from the Source of Knowledge.

34:39 - 34:48
Yeah, there's a few. I really have quite a diverse set of podcasts that I just listen to, and there is.

34:50 - 34:52
One of them is Lex Friedman.

34:52 - 34:56
I really like the way that he goes into depth with those thought leaders.

34:58 - 35:03
I don't do that every week, but I do listen to quite a few of his interviews that are like 2

35:03 - 35:06
hours long, and they just capture my attention.

35:06 - 35:15
And it's once when I was still, what was I in my twenties when the Steve Jobs biography came out?

35:15 - 35:19
That's one of those audiobooks I was listening to because of that same reason.

35:19 - 35:22
It's kind of like going into the heads of those people.

35:22 - 35:24
They're all people, they're all humans, right?

35:24 - 35:27
So they all kind of have their way of doing things.

35:27 - 35:31
And if you want to learn a little bit of how it's. How it.

35:31 - 35:35
How they think about the world and think about problems and how they go about solving those

35:35 - 35:37
problems, I find very fascinating.

35:37 - 35:45
And so, like, one of the ones I can remember quite strongly just now was the one he had with Mark Anderson.

35:47 - 35:54
And that really kind of like shone a big spotlight onto this whole phase of introducing the

35:54 - 35:58
Internet to the world, because Anderson was getting famous with, I think it was Netscape or

35:58 - 36:05
so, right, or the browser, just the general, like the browser being the door to the world, which

36:05 - 36:06
we are very used to now.

36:07 - 36:08
That kind of came from him.

36:08 - 36:15
And that way of thinking is just fascinating because we are at this kind of a place right now.

36:15 - 36:25
And I love the way that he framed also the fact that when the Internet, what was it again, when the Internet came up?

36:25 - 36:33
I'm sorry, when tv came up or film cinematography, the first thing was when they had that is

36:33 - 36:38
they took the previous medium as the input or the content of the new medium.

36:39 - 36:45
So they were actually making a video of a play, right.

36:46 - 36:51
It's funny now if you think about it, because now like Hollywood is just, there's no play, it's all in real world.

36:51 - 36:54
And like, you know, now it's even computers and stuff.

36:54 - 37:01
But if you extrapolate that to the next level, which is going to be agentic Internet, right?

37:01 - 37:04
There's going to be agents that are doing most of the talking right now, I think 80% of the

37:04 - 37:06
Internet traffic is this video.

37:06 - 37:10
In the future, 80% of the traffic will just be agent to agent communication.

37:12 - 37:17
But in the beginning, when you have these LLMs and the agents and all that, the content that

37:17 - 37:19
they will have is the Internet still.

37:19 - 37:27
So they're feeding off the Internet until then that it will be then the actual, let's call the

37:27 - 37:31
AI native content, which replaces what we used to have with Internet.

37:31 - 37:33
And that's also how we think at get it.

37:33 - 37:42
AI is that this whole search first web that we know about, and I'm not talking about social

37:42 - 37:44
because social is a very different dynamic.

37:44 - 37:46
It's not search first, it's basically feeds.

37:46 - 37:51
I'm going to just exclude that part, but the part where we're actually going into the browser

37:51 - 37:55
and searching stuff and looking through websites and all that, that's going to be replaced.

37:55 - 38:00
That's something that we're going to, our kids can be like, whoa, dad, did you actually spend so much time searching? How is that?

38:00 - 38:02
Like, what did you do the whole day?

38:02 - 38:07
Like, you know, well, just tell somebody what you want and they'll present you with the results. Like this. Fine.

38:07 - 38:09
Not seek that I mentioned in the beginning.

38:09 - 38:14
That's kind of what I see coming and that's what I very clearly saw mapped out there.

38:14 - 38:20
We don't want to be surge first, we want to be agent first in terms of also the experience that you get.

38:20 - 38:21
And that'll be very different.

38:21 - 38:25
You know, the same way we're talking here together is different than if you write together.

38:25 - 38:27
It'll be like that, that kind of a contrast.

38:28 - 38:31
So that's, that's one that, and you know, I listen to the economist every week.

38:32 - 38:33
That's been something I've been following.

38:33 - 38:36
I'm curious to see, by the way, how that's going to pan out now.

38:36 - 38:40
Because one of the reasons I was listening to the Economist every week is because it was actors

38:40 - 38:42
that are reading that out aloud.

38:42 - 38:49
And now if I have a chat GPT result, I can just read aloud and it's sounds like an actor.

38:49 - 38:55
So if this technology now gets applied to other sources, I can, again there in my listening

38:55 - 38:58
rituals, expand my sources and that'll be interesting.

38:58 - 39:02
I'd like to have some sort of an app that gives me a feed or a summary of different things together

39:03 - 39:08
that just gets read to me that I can listen to when I'm doing some exercise or I'm cleaning

39:08 - 39:10
the house or cooking or something like that.

39:11 - 39:13
So that's the other big source.

39:13 - 39:19
And then there's some cool books for product managers and product leaders, I think it's called inspired.

39:19 - 39:24
I always forget the authors, but that was a good one where I took from that, where you're saying

39:24 - 39:29
that as a startup, you just have to make sure that back to my funding role, you have to make

39:29 - 39:33
sure that you don't run out of money before you've proven product market fit.

39:34 - 39:35
That was a good one.

39:35 - 39:40
Basically in the beginning, a lot of the VC's and everybody's like, yeah, so does it work?

39:40 - 39:44
You're like, yeah, obviously I'm asking for money here because we don't have those numbers yet

39:44 - 39:50
and hence the valuation is lower and everything but yeah, you're racing towards proving product market fit.

39:50 - 39:53
Once you have that, I think the world will be a bit different, even though I think it'll all

39:53 - 39:55
adjust to whichever realm you're in.

39:56 - 39:58
It'll just be different challenges you're facing. Right.

39:58 - 40:04
But right now that's like my holy grail is to have that product market team, product market

40:04 - 40:10
fit proven by the team and then I have an easier job than bringing in the money that they need to grow further.

40:12 - 40:14
Awesome. Thank you for that, Alan.

40:15 - 40:22
I really, what sticks in my mind is the thing that you mentioned about the revolution, the point number two. Right. So you are changing.

40:22 - 40:26
Let's say we have the Internet and then we have the AI.

40:26 - 40:30
So you don't have to type, you have to like, you just get the answer that you want.

40:30 - 40:33
So it reminds me the story of Sony.

40:33 - 40:40
So like when the Sony released the tapes and you can listen music on the tapes. Right Lunda. Walkman. Right.

40:40 - 40:45
And they have already like a second team working in a different room on the thing that will,

40:45 - 40:48
that will be the next big thing after the Walkman.

40:48 - 40:50
So like they released the discman.

40:50 - 40:56
So I think in your case what you are doing, you are building like the discman after the Walkman.

40:56 - 41:02
If I, if I think about the Internet or mp3. Or mp3, right.

41:02 - 41:05
This is a better, better comparison.

41:05 - 41:07
As long as we're not doing the.

41:07 - 41:11
Probably many people don't remember the minidisc anymore. Remember that one?

41:11 - 41:12
Yeah, yeah, yeah.

41:12 - 41:16
As long as we're not the ones that are creating the minidisc which had like just a one year

41:16 - 41:19
stint and then they were like completely erased. That's fine.

41:19 - 41:20
You know, I think that's.

41:21 - 41:27
So I wish you to be successful and create the next MP3 3.0 or something like that.

41:28 - 41:34
No, I think that's one of those like moments in our generation.

41:34 - 41:39
And that's something like everybody says, like, yeah, yeah, the people from bitcoin, like the

41:39 - 41:41
cryptocurrency guys said the same and all.

41:41 - 41:45
But I think this one you really feel in this society right now, it's going to be bigger than

41:45 - 41:48
other big and big things that came along.

41:48 - 41:52
For me, this is a once in a generational shift that we're experiencing.

41:52 - 41:54
The last time we saw something similar was with the Internet.

41:55 - 41:59
And now this will be such a dramatic way because we have so much touch points with the digital

41:59 - 42:07
world now that this whole way of, it's the first time in human history where technology is adopting

42:07 - 42:09
to us and not vice versa.

42:09 - 42:11
That's if you, if you take that to mind, once.

42:11 - 42:13
That's the whole game changer so far.

42:13 - 42:15
It was always like, hey, here's a new app.

42:16 - 42:19
Learn it, you know, and now it's just like, well, hey, here's my assistant.

42:20 - 42:24
You tell me, like, how I'm going to get this thing done that I want to get done, and that's

42:24 - 42:26
just, that's just fundamentally different.

42:26 - 42:32
So this, I'm really excited about the next decade or so and to see how our whole everyday life

42:32 - 42:36
will just, it'll change so dramatically that our kids, like I said, our kids will not know this

42:36 - 42:38
world that we are in right now. The same way.

42:38 - 42:42
It's weird for them to imagine that we were growing up without computers in the beginning.

42:44 - 42:46
What a boring life, right?

42:49 - 42:53
Awesome. Thank you for a great talk, Alan. I wish you success.

42:53 - 42:55
Yeah, likewise, Matt. Thanks so much.

42:56 - 43:01
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