← Marketing Trends
Marketing Trends
He Built FaceTune's AI… Here's What He Says Marketers Get Wrong
00:46:39
The marketing teams winning with AI today are not the ones chasing every new model release. They are the ones who found the boring, repetitive tasks their teams hate and automated those first.
Loading summary
Transcript79 lines
- [00:00]
A
I'm hiring, I'm a CMO or I'm a marketing team and I see this new title of AI marketer. People just adding AI in front of their titles. What are your thoughts on this?
- [00:10]
B
I think it's LinkedIn fluff, to be honest. The title implies expertise instead of literacy. It's oh, I have this AI expert, so I don't have to know AI. I'm going to go to this AI expert and this AI expert will solve all my problem. Everyone in the company should know to a certain level how to use AI tools. Sometimes people go and they open an LLM or a video model and they try to use it and they don't get results out of the box and then they say, AI doesn't work for me, it doesn't solve my problems. You have to know how to use the tools, which tools to use, and how to use the correct workflows and not just the tools that are hot right now or popular right now.
- [00:59]
A
Hey everyone, I'm Stephanie Postols, host of Marketing Trends and today's guest is Nir Pashtir, the co founder and CMO at Lighttrix and one of the rare marketers who didn't just adopt AI, he built the tools behind it. Nir has spent more than a decade at the intersection of AI creativity and marketing, solving the real creative bottlenecks that developers and marketers deal with every single day. Today we're going to be talking about what AI actually means for marketing workflows, how to build AI intuition, and why the future of video is generation, not production. Nir, welcome to Marketing Trends.
- [01:33]
B
Thank you. Thanks for having me.
- [01:35]
A
Super eager to have you on the show because so many people on the show have talked about the creative process and video and I feel like you're the person who can answer all the questions I've had over the last many years. So you'll be on the hot seat for a while here. All right, so to jump right in, I want to start with this is a theme I've sometimes heard on the show. Marketers will say, you know, AI has not improved our creative output yet. When, when you hear this, what are the blind spots that these folks are missing?
- [02:08]
B
I think it makes sense and it also makes sense when you see, when you look on the output of companies and even of countries, the GDP didn't jump. When AI is out for two or three years now, it keep improving in the same pace. So it means that we didn't change things dramatically. And then we need to understand why some companies say, hey, Things completely changed, and for some companies it didn't. So I think there's a way that companies need to learn and people need to learn how to use AI properly. Sometimes people go and they open an LLM or a video model and they try to use it and they don't get results out of the box. And then they say, it doesn't work for me. AI doesn't work for me. It doesn't solve my problems. But think of it like algebra. If you would go to someone who doesn't know algebra and tell them you need algebra can solve this for you. And they go and look at the page, don't know how to use it, and it didn't solve it for me. So it's kind of like this. You have to know how to use the tools, which tools to use and how to build and how to use the correct code workflows, and not just the tools that are hot right now or popular right now.
- [03:39]
A
Yeah. I could see some of the video tools that consumers can easily access jumping onto and be like, make me a video that does this. No. Okay, this doesn't work. And I can't get frames that are the same and the character won't stay the same. Obviously, I still need my agency to do this and write it off right away. Is that kind of what you're imagining with that?
- [04:00]
B
Yeah. So I think sometimes using AI for some of the stuff is really hard and requires lots of work. And you need to understand where AI can help and where AI can't help, where AI can bring immediate value and go from there. So when we're talking about visuals, you can start. I. I don't think you should start with saying, I want to create a full ad. Right. Because that's a hard problem. And I don't think there's any tool at the moment where you just type, I want to have this ad and it should have my brand identity and the characters can be consistent and it should be a minute long. And this is what's going to happen. This is a problem that AI just can't solve yet. AI can generate a video with a certain amount of seconds. Sorry. And some characteristics. So first you need to master what is the best way to create those short clips. And then you should use tools and not just. I think the best way is not just to use VO or SOA as they are, and all those models as they are, but use tools that wrap them and allow you to create a workflow that helps you to get to your target, which is a full ad. If that's the target. But I'm not even sure that for many ads we're just not there. Sometimes it's just more beneficial to use AI for passing part of what you're doing and not replacing all the workflow.
- [05:47]
A
Yep. Yeah. So now that you've touched on video a bit, I would love to for you to highlight your background a little bit and then also tell us what light tricks is. Just to help kind of let the listener know who you are and why we're going down this creative video route throughout the episode.
- [06:03]
B
All right, so my background is prior to becoming a CMO, I was studying computer science. We focused on AI. So I was doing my master's in AI and then did my four years of PhD studies, which I dropped off from to start Lightworks. Then in the last 13 years I've been here as a CMO, we built creative tools. First we started with apps. Our most known one is Facetune. And three years ago we pivoted and now we're doing AI models, LTX2, which is a model to generate videos and audio. And so we started by building apps for creative people. Our most known one is Facetune. And in the last three years we're focusing on AI models and products that make those models accessible. We have an open source model called LTX2, which is a diffusion model, allows you to generate video and audio. And we have LTX Studio, which allows creative people to have easy to use creative workflows for using models.
- [07:16]
A
Amazing. So who are your customers? Who's typically working with your products?
- [07:21]
B
It's a wide range for the model. We have both creators the that are using it to create their videos and developers who are using the model to create their own apps and services. That is a very wide range because those diffusion models are now helpful in many fields. And for LTX Studio, we have brands who want to give more tools for the creative marketing teams or just for their creative teams. We have animation studios and we have lots of marketing agencies using our products.
- [08:02]
A
Okay, that is a wide range. So tell me about thinking about the landscape we're in now when it comes to video creation. What are things that used to take weeks, months, that now take 10 minutes or, you know, where people look at it and they're like, oh, I used to spend a long time doing this one thing and now it's, you know, automated in a much quicker way than. And most people don't know it too. That piece.
- [08:26]
B
Yeah. So few years ago, when you needed an asset, an image or a video you went to stock photos or stock videos services and you started searching. Now most people don't do that anymore. They go to a text to image or image to video model and create the asset that they want. And this was a huge change on the creative marketing teams because first, it takes much less time to get what you want, and second, you get what you want and not something that is just similar to what you want that was available.
- [09:05]
A
Okay. So getting the images when you want right away, That's a good example. I'd love a couple more just to highlight this space. Yeah. Just for the efficiencies that have been created.
- [09:15]
B
It's getting the images, it's getting the videos, and there are many more tasks that are becoming more and more accessible and easier for people. So think about post production. Let's say that you want to translate a video, you had to take it to a translation agency and have someone dub it. And now this is something, for example, that can be done by an AI model immediately. And there are several services that provide that.
- [09:49]
A
Yep. Yeah, that's one that we've looked at, getting some of our episodes translated. And this was about five years ago. And the cost to get things translated back then, I mean, we didn't end up doing it because I'm like, that's too much. And I don't even know if I trust the translations of what's happening here and seeing how quickly, yeah. The space has evolved to be able to just have something like that that would take maybe weeks being done right in front of your eyes. I mean, it's crazy to think about how sped up the whole process of creating things has become now.
- [10:19]
B
Yeah. And I know, I'm sure that sometimes you want to edit what you said or stuff like that. And now sometimes instead of reshooting, you can just choose AI, an AI model and select an area of the video and it can change things.
- [10:37]
A
Okay, so I would love to hear. I know you've worked with a lot of amazing clients. I'd love to hear a story of how, you know, someone came in and they were doing a process, a workflow in one way, and then they completely transformed doing it a different way. Like, visualize it for me so I can imagine what the shift is of the environment we're in today.
- [10:55]
B
When those generative models came out, we got so excited. And my VP of creative marketing is also an AI enthusiastic. So we started playing with the tools and we said, hey, let's automate all of our video creation with AI. Spoiler alert. We failed miserably okay. We worked on all the phase tune creatives, and we wanted to be in a place when a designer imagine a new creative, he can just generate them. But it was so hard because there are so many cases why they think about X, they think about. Yeah. And then we started talking to them to see what they're working on. And we noticed that they spend lots of the time on iterations of ads that already worked. Because usually you make variation of what worked. 80% of your time, 20%, you experiment. And then we said, wait, but this is a repetitive task. And the upside is that the team hate doing this. They don't like iterating, they like thinking of new concepts. So we worked with them and wrote an internal product that only helped create video variations of stuff that we already had and worked. We just created templates. We, we saw that parts of it can be generated with AI. Once we had this flow, we wrapped it with Python code that we wrote with AI tools. And we called this product Simple Ads because it just solved the problem of creating the simple ads. And the nice thing about it that it saved the designers still 80% of their time, and it saved them the time that they spend of the things that they hate the most and allow them to spend more time on exploring new options, which is what they like doing.
- [13:08]
A
Okay, amazing. So you basically, this was your internal team who did this, and you essentially went from having a team build a bunch of different variations, of course, AB testing and all that of ads, to then taking the one that was working and then spinning off. I mean, how many different iterations of this ad did your team spin off to test?
- [13:28]
B
Oh, we can do hundreds.
- [13:30]
A
Hundreds. Okay. So instantly it's putting out hundreds, and then you're easily able to track of those hundreds which ones are doing well, and then kill off the bad ones.
- [13:39]
B
Yeah. And then this feedback can obviously go back to the AI, and then in the next situation we can improve. And it also has the upside of getting the team motivated. So I think one of the nice thing in implementing AI is to first do it on the tasks that people hate doing. This is where you get the most engagement. And this is the best. It's the best way to create a positive feedback loop.
- [14:14]
A
When I talked to you previously, you said you would go around to your team and ask, like, what are the things that you hate doing most? And so let's walk through training your team around AI and using it and experimenting like this, but then also how to find the bottlenecks and the tasks that actually should Be automated versus you might hate that, but that's still a thing that you need to do because AI is not ready for it yet. So tell me about your process with your team.
- [14:38]
B
When we started integrating AI, the first thing we did was getting everyone access. And then we expected people to start using it, but this doesn't magically happen. So instead of just telling them use AI, we start taking them to seminars and workshops and telling them, okay, what do you hate doing? And then. Or what is a boring, repetitive task that you have? And then they list it and then we start mapping what we think is solvable with AI tools. And I think a very easy way to do it now is if you have your list of tasks. You can put this list into an LLM of your choice. Can be Claude, can be GPT, Grok, whatever, and ask the LLM which of these tasks do you think is the easiest to automate using AI? And then you can get this answer. And then you start the process. There's a process there, right? Because first you need to find. It's very important to know how to break the task into subtasks because sometimes 80% of the problem can be replaced by AI, but 20% can't. And then you just implement those 80% and then you start an iteration when you're trying to solve these parts and you have to see that you get good enough results. And then when you get good enough results, you start iterating and you start putting things in production. And it can be very simple stuff. So, for example, at some point I noticed that when people send me emails with projects, proposals or presentations, then my LLMs already know how. I think. We iterate, they learn. And usually the first thing I do is I take this presentation, I put it into an LLM and tell the LLM, please grade this one to 800 to 100. Be very honest. You only care about business success. Don't try to please me. And I send them this feedback. So I told them, here's an implementation of AI in light weeks. People can't send me documents unless it passed an LLM first, which I think can save people lots of time. That's, I think, one of the best time saving, because lots of time you send the same feedback over and over again, right? And then it can just save them time. Okay? They get it from the LLM, they implement it, and they understand later.
- [17:44]
A
Yep. Yeah, I love that. I have in ChatGPT a personalization that I call it my mean GPT because it's like, don't be My hype man, my yes man, whatever it is. Like, it's a whole prompt being like, you're a business strategist and you're not meant to just, you know, like. Because a lot of times they could just cheer you on if you don't prompt it well or have a customization inside of it, it'll just be like, amazing job, Stephanie. That's the best proposal I've ever seen. Great job. And I was like, this doesn't work for me. I need it to be poking holes and really finding the gaps. After I put that in there, I'm like, yeah, any of my team can use this as well. And they know this is how I'm already. I'm running it through like this, like, this is how I'm going to look at it. And the results are always better in my mind because that is how I think. Where I'm like, I want, like constructive criticism and feedback constantly and poking holes. I don't want just like, good job. That was, that was, that was great.
- [18:37]
B
And this is so, so important because the way that LLMs are trained, they are trained to give you a result that you think is plausible and that you will be happy with in a way, if I simplify it. And what you want is someone to give you. It's like with humans, humans, sometimes we talk to them, they try to please us. So it's the same thing with AI. You need to tell AI no, you're my advisor. You care about my business success or you care about my success. You're not trying to please me. Otherwise, yeah, you can have this game with LLMs. If you don't put it to them and they give you an answer and you say, are you sure? Then they always change your mind.
- [19:26]
A
Yeah, this does open up a whole psychological question too, around how people are using GPT. And if they are really people pleasers and they need nice feedback and they can't handle criticism and just like training the team of like, it's just best ideas win here. Like, use the prompts in this way. And it might feel a bit harsh, but we'll all be better on the other side if we have, you know, something that's thinking very critically on our behalf and just showing people, like, it's okay to have your idea just get slashed by an LLM. Like, if it's good feedback, like, that's better than something, just slightly tweaking how you said something or writing it slightly different, like, I don't care about that. And so I think just even that mindset Shift is probably a good one to, to show teams like it's okay to get intense feedback from GPT or cloud or whatever.
- [20:15]
B
I really like the name Mean GPT. I'm gonna, I'm gonna steal this one.
- [20:21]
A
Yeah. I almost named it Karen, but I was like, I'll keep it with mean GPT instead.
- [20:27]
B
And, and, and we also have GPT is for products. So, you know, we just had a release recently. So the VP marketing of the model, he created the GPT with all the documents and the release notes and everything that we had about positioning, about branding, and it kept updating these documents. So whenever it needs to write some marketing content or think about a brief or whatever, they can use this GPT. And it's always updated. Always. It's.
- [20:57]
A
Yeah. And it's shared across the whole org and everyone can.
- [21:00]
B
Yeah, this is shared across the whole org. And I think this, this kind of stuff is an example for AI usage that doesn't have to be complex. If I'm going back to the question about, you know, AI isn't helping me, I think people are always thinking about the most sexy and complex problems, where they should start with the boring problems first.
- [21:22]
A
So when thinking about kind of going back to talking to the team, asking about the things that they hate, finding that. Do you have someone who is managing that process and working with your team and then also helping implement, let's just say 80% and being like the 20 we can't do right now, who's working with these team members to really get these processes automated and tested and seeing if it's working and all that?
- [21:47]
B
Yes. So we have quite lots of resources on that. We were always a very technical marketing team. So my VP of creative marketing, he's actually the VP of Creative Marketing Innovation, and he has an innovation team that are really good with AI and are helping people with automating problems. So people, when they reach to a place, when they cancel it by themselves, they go to this innovation team. The innovation team helps them solve the problem and then write a workflow that is wrapped with code and people can use. And in addition to that, we have a team of developers for the marketing department that are building internal tools. So if the task is hard or has some security issues or data issues, something that is sensitive, we are using the developers to build it.
- [22:54]
A
Got it. Okay. I was going to ask you earlier, you mentioned the flop with trying to create a bunch of ads at once with AI. Were there any issues that popped up when you were rapidly trying to build up AI intuition and skill base on the team and giving them access to everything. Were there any hiccups that happened along the way?
- [23:15]
B
I think that the biggest problem was with people not getting good enough results with AI like you mentioned before or they felt the need to show that they're using AI and then this became their number one KPI. So they knew that I'm obsessed with AI. So okay, now we need to show our goal is no longer the business. Our goal is to show near that we are using AI. And this is suboptimal so this can cause problem. You can use AI for stuff that it's not doing well and you start having like crappy copy for the ads and stuff like that.
- [24:04]
A
Yep. At the bottom it says do you want me to write this into five different ad versions? Hey, I know.
- [24:11]
B
Exactly. So it takes time and iterations and obviously solving part of the issues when we try to integrate AI was people fear of AI. It's I think a non issue that we also had to address.
- [24:31]
A
Yeah. So I mean if we think about the stages we've gone through at a pretty quick pace. If I think about even like last year I was talking to many companies who they were, you know, not allowing their team to have access of course to the LLMs training, even consumers using ChatGPT like there's so many new things happening that I felt like that was one big hump to get over of. Okay, now most people have probably tried it out. Most companies are starting to allow access now. People know how to use it. Where are we at? Where are we heading? Like what's next? Now let's just say for your team, like your team has been ahead of the curve. You've given them the tools, you've given them the training and now it's also you know, reminding people like don't forget your human self, don't just drop me a chat GPT response that doesn't work like now what, what's next for. Yeah, for a marketing team.
- [25:25]
B
I think we're done with toys and are going to have tools. If I have to sum it, I think look at how people use diffusion models. They think of it as text to video or image to video. This is how most people call VR serve. For example, they say hey, I'm using this text to video model. But, but this is not how those models are built. This is how they are exposed to us. I'll give an example. Those models, they take input and they create output. So one thing you can do and we're doing with our model is let's say that you have a problem. You shot an ad on portrait mode and it was really successful. A great problem to have. Okay. And now you also want to advertise it on YouTube. It's portrait. You need it on landscape mode, so you need to reshoot it. This is what you used to do. The models that don't just do text to image, text to video, image to video, they can actually do this. It's called outpainting. And they just take the portrait mode and generate stuff around it that looks like it was shot on landscape. And of course, for every aspect ratio to every aspect ratio. So that's a tool that is actually solving a business problem. Right. And even when I look. When we look on ad productions, I saw recently a TikTok by someone, I think his name was Nate B. Jones. He's doing lots of stuff on AI and he was talking about the Coca Cola AI ad. He said they used 70,000 prompts and he started doing the analysis. He said, okay, if that's how many they used, think of how many they tried and how much money they spent on this and the manpower. It was probably cheaper to just shoot the ad. I think we're heading to a place where we'll have tools that are trying, for example, to give more control. Because if the model take inputs, part of those inputs can be controlled when you give them a start frame and then end frame and maybe a frame in the middle. And. And maybe you put your brand guidelines and maybe you have a way that the character needs to move its hand. Right. There's so many things that you can add. It's not just, okay, I'm writing a text and I'm getting a 5 seconds or 6 seconds video. Usually that's helpful sometime, but it's not that helpful.
- [28:22]
A
I like this. Okay, so from toys to tools, that's the viewpoint which I actually love. How simple and like, I understand exactly what you mean by that. Are there any other examples like that? Because I love the one about, you know, you used to have to reshoot, but then also being careful about, you know, how many prompts are you using and manpower are you putting in to get this video versus maybe you should just actually shoot this. Are there any other examples like this of where you see the future heading right now in this world of video?
- [28:53]
B
It connects, I think, to the point of AI not replacing people, but people who are using AI replacing the people who don't. Because when I look on flows and AI flaws. Again, let's take you shooting something you put Constraint I, I think you're gonna find you, you will start looking for the expensive shots and start by replacing them, right? And not everything because it's so how to replacing all production. You will start looking for the either take your production and decide which parts of the productions that you want to replace or you're going to take a specific type of production that is easier to do with AI. Maybe it's easier to, maybe animation is more forgiving. You start by doing animation production with AI and some of it you still do without AI. I think it's augmented tool when you're using AI but also doing some manual work. I think now many times people, when they use AI for the sake of using AI, they try to do everything with AI and then you get those, okay, I'm using so many prompts instead of finding the hard tasks that are easy for AI.
- [30:13]
A
So I mean I'm thinking about this future that you're talking about and people really leveraging AI for this creative process. And I do wonder at what point does everything just become same of same because people are using the same models, same typing in prompts, kind of getting back similar responses and instead of competing against human creativity and like basically what I'm putting out as, you know, my creative project comes from my lived experiences, my wisdom, my, you know, all the things that have happened to me versus now we've got these models that are, you know, people eventually will be relying on heavily to create output. Like how do you make sure it stays creative and doesn't just, you know, get poured into a soup of all the same type of like content or ideas or feedback or you know, the prompts that are being used.
- [31:02]
B
I don't see AI taking the human out of the loop. I see AI changing the way that people are working. Let's take developers now. So developers, they have now cloud code and they have cursor. They started from copy pasting their code into the LLM but now they have this systems that save it for them. And now it doesn't mean that you don't need developers, you still need developers, but you need developers that know how to tell AI how to help them code. And you still can't have just one person come to work and say okay Claude, do this for me, okay now do this for me and replace the rest of the developers and you're not going to get the same output from every developer. And I think it's going to be the same for creative at the end of the day. We have many creative folks here. I know how to write prompts. I never get the amazing results that they produce because there's no. They have the creative mind. And lots of walking with AI is about curation. It's about knowing how to select the best results and knowing how to explain why they are better. So in a way, AI is just helping people become better.
- [32:45]
A
Yeah. Yeah, I. I love that last sentence. I haven't really thought it through of it that way of like, it's you knowing how to select the best results. I've seen that so many times where, like, put a prompt in there, same person put the same prompt, and, you know, I choose a different one, someone else chooses a different one, and knowing what's good, depending on the context, like, it really depends on the person who's picking that and also on the input that you're putting in there as well. So I love that reframe of like, are you still a good picker? Like, do you know how to select good things? If not, and you never were, it still might not work out for you. You still pick the bad output every time. Yeah.
- [33:24]
B
I think there's two skill sets here. The first is you mentioned you need to write the right prompt. That's an art. Many times when people think that AI can't solve their problems, they didn't experiment enough, they didn't learn how to write the correct prompt. It's something that you need to learn. That's one skill. And the other is the professional skill. It's unrelated to AI. If I'm a good designer, hopefully I can select the best assets and can iterate on them. And that's where the gap is going to grow. And that's why AI is actually increasing, I think the gap between. Between people.
- [34:12]
A
Yeah. If they're not using AI versus if they are, you mean.
- [34:16]
B
No, I mean first this for sure. Okay. If you're not using AI, you have a problem. But let's say I'm a copywriter, okay. And I'm. Let's grade my skills, and my copywriting skill is 7. And you're a copywriter and your copywriting skills are 10. And then. And then I think of AI as multiplying your skills. So let's say that it multiplies, that it doubles for simplicity. So I was a seven. I'm 14 now. You're 20. I improved, but you improved more because you're iterating fast. Right. You know how to write a prompt better, you know how to select results, whether the gaps are going to increase.
- [35:09]
A
Okay. So we've been diving a Bit into the weeds around the video production process and all the efficiencies that AI is bringing to it and how you should and shouldn't leverage it. If I zoom out and think from the CMO perspective, are there new questions they should be asking when it, like, they're receiving creative, they're receiving new branding, There's a whole bunch of new processes happening behind the scenes. Let's just say with something like light tricks, that they might not even know how things are being built anymore. What questions, if at all, should they start asking or looking deeper into with all these evolutions in technology that are happening?
- [35:45]
B
So every CMO will obviously handle it differently depending on their technical level and their priorities. But if I try to think of the framing, I think that, okay, there's a new technology that's here and it's gonna really change productivity. Right. It already started and hopefully will change productivity even more. Let's think of when computers started entering the field, right? If a CMO would ignore them, it can be a disaster in the first few years because after five, 10 years, everyone will adopt it. Right? But the difference between companies who will be very successful in the next few years and companies who won't is how quickly did they adapt AI. So adopt AI. So I think they need, as a cmo, you need to make sure that your team adopts AI for the expensive stuff, that if your competitors will do them faster and cheaper, they will beat you. So it's either you're into AI and you ask people, are you using this, are you using that, et cetera, or you have someone you trust and that's the role to make sure. Not, by the way, not that people are using AI, but people are solving business problems, that they are increasing efficiency and creating more value using AI. That's a huge difference. That's a great parody post by someone in X. I think it's Peter Greeners. He had a great parody post on a CEO that's getting ordered by the board to implement AI and how they do the process of buying seats and showing adoption. What is adoption? People who we bought seats for. Great. We have a graph. It goes right into the top. We succeeded. No, you need to make sure that people are creating business value using AI. And I think that CMOs need to make sure that this is happening. Not just CMOs, of course, but everyone.
- [38:02]
A
Everyone, yeah, that's. I love that. Like, being curious enough to be like, okay, awesome, you just put something in my inbox, like, tell me about how this came to be and like, what tools Are you using, if at all, like, are you using them? And just like being curious enough to dig in to see is your team using AI? But that also takes you knowing about it, to know the right questions to ask and to know the tools that exist right now of, you know, being mindful of that, to even have the right questions to ask of your team too.
- [38:28]
B
It's not just about using AI, but what are they solving? What's the problem they're solving. If they're using AI, all you know is, is that they are helping the business of OpenAI or Google or whoever you pay for your tools. You want to make sure that they also helping your business.
- [38:46]
A
Good. Okay, so one other question. Now that we're thinking about questions to ask. I'm hiring. I'm a CMO or I'm a marketing team and I see this new title of AI marketer. AI Marketeer. Like people just adding AI in front of their titles. What are your thoughts on this?
- [39:03]
B
I don't like it. I think it's LinkedIn fluff, to be honest. The title implies expertise instead of literacy. It's creating. Oh, I have this AI expert, so I don't have to know AI. I'm going to go to this AI expert and this AI expert will solve all my problems. But if we use the framework that there's like two parts, right? There's the prompt part and that is the selection part. The AI expert, he only knows AI. He won't know how to do the second part. He won't know if the AI actually creates something good. I think that everyone, everyone in the company should know to a certain level how to use AI tools. It's like, it's like. Okay, let's say that we have a spreadsheet Mocktir and no one else have to use a spreadsheet anymore.
- [40:01]
A
Yep, yep. I love it. All right, Nir, well, we are going to move on to the lightning round. Now. This is where I ask you a quick question and then you have under a minute to answer. Are you ready? Near. And knowing that I might just ask random questions, by the way. So it might not be at all what's on here, which is probably better.
- [40:21]
B
So I'll ask. So I'll answer random questions.
- [40:24]
A
Yep, answer random questions. It's easy. It's like everyday life. All right, first up, what is a book that you've read or listened to in the past year that deeply impacted you? It can be personal, business, marketing, AI, whatever you want.
- [40:39]
B
Oh, I listen to books, so I just need to.
- [40:45]
A
Yeah. Open up your Audible or whatever you listen to him on.
- [40:48]
B
Yeah, let me see, which Audible book did I like? Oh, I read Amp It Up.
- [40:56]
A
Who's it by?
- [40:58]
B
Frank Slootman. Great book on and how to win stuff.
- [41:06]
A
I will check it out. This does feel like a book. Right up your alley. I like it. Okay, what, what was a line? A piece of advice, Something someone said to you that really stuck with you and influenced your career.
- [41:20]
B
So when we launched Facetune for iOS, it was a great success and I think that we did really good marketing and we got good reputation in marketing and then we launched phasing for Android and I was certain that it's going to be easy. And we launched and it didn't work and I started telling many excuses to myself. Then at some point, I remember I was in the kitchen and our CEO Zev, who's my friend for 25, 26 years now, long before light weeks, he came to talk to me and I started giving excuse and he's like, listen Neil, these are our excuses and you need to understand when you are wrong and making mistakes so you can fix them. And I thought about it and I was like, fuck, he's right. Then whenever I start feeling that, you know, I have this feeling of trying to tell excuses, I remember that. And it connects to something that One of the VPs here, who's working here for 12 or 13 years told me once, he told me that being a marketer is about thinking of a great idea, executing it, seeing it failed, going to sleep, waking up, having another great idea and trying it again with enthusiasm.
- [42:56]
A
So it's like, I love that. Yeah, I really like that. And I love the directness. Like you've had your own mean GPT over here, just giving you good feedback like this for 25 years. This is what a blessing it is. Oh, that's so good. Okay, next one. What is a marketing hill you're willing to die on? You get in your team meetings and you're like, I will not back down from this thing.
- [43:25]
B
I'm not willing to get any document that didn't pass GPT or Claude or whatever, LLM and got at least 85.
- [43:34]
A
So you have a rating system. Do you give it to your team for this where it's like it'll give the rating on it?
- [43:39]
B
No, I don't send them the rating, but they know that they have to. When, when we started, people didn't always do it. So they sent me something. I was like, did this pass GPT? No. Okay, so I'm not Reading this, you know you have to. You have to do it first. It really helps.
- [43:55]
A
But did you give them your prompt of like Near's idea? Like, did you have your own custom GPT that you built up with your brain inside of it that then they can run it by?
- [44:06]
B
I didn't send. When, when we started, I sent people my prompt. But now I think people know how to write their own. But I think people. I think people who work here know me by now. Every CMO has the things that they care about, so they know what they care about.
- [44:22]
A
Yeah. Okay. Amazing. Because if not, I would probably just take any recording you've ever done and just take the transcript and upload it to understand what you care about. Amazing. Okay, last one. If every marketer listening could just master one AI skill this year, 2026, what should that skill be and why?
- [44:41]
B
I have. The thing is, I have two. But fine, give two.
- [44:45]
A
Give two.
- [44:45]
B
All right, the first is the out of prompting. It's so important when you come to the. You can just get totally different results and it's really, really easy to get the right prompt first. You can search people done tons of guides on the right prompts. You can search on X, you Google it. Or the best thing you can do is go to your LLM and tell it, hey, I. I want to solve this problem. What is the best prompt I should use? Usually you're going to get a great prompt, then you put a new chat, put it there, you're going to get results. The second one is if you come in and try to solve a very large problem, it's going to be very often hard for the AI. So, okay, as we said before, I want to create this ad. One minute full ad. Create it for me. It's hard. So there's an art in. You want to bring it to pieces, break a problem to pieces, that each piece is complex enough but. But also solvable and then the AI can solve those for you.
- [45:57]
A
Yep. I love it. Okay, well, Nir, thank you so much for joining Marketing Trends. It was amazing hearing about the space that you're in and more about lightrics and where you all are headed. So until next time, can you tell me more about where our listeners, our viewers can find you and light tricks?
- [46:15]
B
Yeah. So you can go to LTX IO where you will find links to our model and our products. And if you're a creative marketing person, I encourage you to try it and let me know if it doesn't work well.
- [46:31]
A
There you go. I love it. I love it. All right, well, thanks so much, Nir. I appreciate you joining. We'll see you next time.