#277 Pivot or Perish: A Startup’s Explosive Growth in the Age of Gen AI

Summary

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Embracing Digital Transformation, Episode #277

Pivot or Perish: A Startup’s Explosive Growth in the Age of Gen AI

Host: Dr. Darren Pulsipher
Guest: Joaquin Cuenca, CEO of Freepik
Release Date: July 10, 2025

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Episode Overview

This episode dives into the high-stakes journey of Freepik, a major stock image platform, as it confronts existential disruption from generative AI. Host Darren Pulsipher and CEO Joaquin Cuenca discuss how startups can survive, adapt, and thrive amid waves of technological revolution. Joaquin shares Freepik’s pivot strategy, organizational changes, the vital role of user feedback, and their unique approach to leveraging (not building) AI to deliver enhanced value.

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Key Discussion Points and Insights

1. Joaquin’s Origin Story & Bootstrapping in Spain

• Joaquin began coding at age 8, studied physics and computer science, and co-founded several startups. His first was acquired by Google, integrating geolocated photography into Google Maps/Earth.
• Freepik was bootstrapped due to Spain’s limited venture capital, relying on lean teams and iterative development.
• [01:41] Joaquin: “My first startup was acquired by Google... three years later I came back to Spain and co-created a couple of companies... they have been growing since then and we are pretty happy.”

2. Technology Abstraction Layers & Gen AI’s Impact

• Joaquin details how each technological wave removes barriers to starting new companies, from home-hosted servers to cloud, and now generative AI as an “abstraction layer over almost any position.”
• Gen AI allows startups to do more with less, supporting engineering, design, and marketing with a “decent” baseline of outputs.
• [04:13] Joaquin: “The next one is AI, which ... makes an abstraction layer over almost any position. So you can now have an engineer, ... designer, ... marketing person... you get something that is decent, okay, which is pretty important.”

3. How CEOs Use AI as a Double-Check

• Joaquin finds AI often more reliable than unknown human “experts,” using it to verify advice and speed up decision-making.
• [05:21] Joaquin: “When I start working with a new expert, typically I double check what they say with AI, and then... it builds trust on this new expert. But to me is helping as a double check on everything that I do.”
• Both agree AI is a “magic wand”—it speeds up work but occasionally makes small mistakes users must catch and fix.

4. Generative AI: Existential Disruption in the Stock Image Market

• Freepik’s core business: world’s most popular site for free stock images, massive user traffic, with a premium subscription model.
• The launch of DALL-E and subsequent generative image models posed a direct threat—users might now easily create unique images without traditional stock libraries.
• [12:33] Darren: “So you guys saw this as a huge threat to your business model.”
• Joaquin: “It was.”
• He describes an existential crisis—hundreds of employees at risk if they didn’t pivot.

5. Strategic Pivot: Focus on Strengths, Not Competing on AI Models

• Despite initial fears (“no right to win”), Joaquin leverages lessons from the PC revolution: as technology standardizes, the real value is in the layer above the commodity (here, the user interface, customer experience, and workflow on top of AI models).
• Freepik decided not to compete building foundational AI models. Instead, they:
  • Licensed open source models (e.g., Stability AI’s SD 1.5) and tailored the user experience for creators.
  • Focused on user feedback to improve interface and prompt design.
• [18:46] Darren: “You didn’t go off and say, ‘I need AI experts.’ ... You said, no, I’ll license that. That’s right.”

6. Building the AI Stack: Integrate, Innovate, Acquire

• Freepik took a multi-pronged approach:
  • Integration: Quickly adopted open-source models and improved UX.
  • Internal Research: Hired researchers for custom features (like inpainting, region-by-region editing).
  • Acquisition: Bought Magnific AI (creative image upscaling), which improved image quality by adding artistic detail, especially for AI-generated content.
• [23:19] Joaquin: “When something is really critical to your company... try a bit of everything.”

7. The Limits and Pitfalls of Gen AI for Stock Assets

• Not all users want AI images—some need consistency and reliability. Early mistakes included allowing too many AI assets into the standard stock library, which led to quality issues (e.g. “Why does this chair have six legs?”).
• Freepik corrected by filtering, clearly labeling, and user-segmenting AI-generated vs. traditional assets.
• [24:33] Joaquin: “We had to remove most of the AI generated content because it was not good enough. And that means detecting when it was generated, removing it from the platform...”

8. Organizational Agility and Decision-Making

• Freepik’s scale (~580 people) meant creeping bureaucracy; rapid adaptation required dismantling committees, empowering individuals, and streamlining authority.
• Key decisions reverted to individuals rather than groups, freeing the company for quick, course-correcting actions as they experimented with AI.
• [27:29] Darren: “You have to delegate that decision making to an individual ... Otherwise you get stuck and you can’t.”
• [27:42] Joaquin: “We were ruthless, like removing committees, removing group thinking, and coming back to very quick decisions, extremely fast executing them.”

9. Strategic Refocus: The Professional User as Target Market

• With consumer-grade generative image creation commoditized by ChatGPT/Google/etc., Freepik’s future lies with creative professionals who need detailed control, collaborative workflows, and higher-quality outputs (video, audio, specialized images).
• Strategic decisions (set at the top) are translated into tactical actions closer to where the work is done—product teams and engineers are deeply involved with user feedback and empowered to act.
• [30:53] Joaquin: “The decision high level is we work for professionals. What they need that they don't have today is control over the image...”

10. Engineers’ Role and Skillset Evolution

• Modern engineers must engage with users, understand business needs, and creatively solve problems—not just “take orders.”
• AI enables smaller, more effective product teams; tools automate mundane tasks and summarize user interviews, further tightening the feedback loop.
• [34:12] Joaquin: “If I need precision, what I want, I'm not gonna need you in one year, man... you need to understand the user, ... come up with ideas...”

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Notable Quotes & Memorable Moments

• On Disruption:
  [14:51] Joaquin: “We were at the time around 500 people. ... How do we deal with this and how we can turn the company into something that is useful to people and still be relevant.”
• On Gen AI as Magic Wand:
  [07:26] Joaquin: “The metaphor of a magic wand is quite spot on because ... sometimes there is a spell that doesn’t work ... but it is overall right...”
• Pragmatic Approach to AI Build/Buy:
  [19:00] Darren: “That cost of retraining all your people and not relying on your strengths is astronomical and it will kill a company.”
• On Adaptation:
  [25:35] Darren: “You can move quickly, you can adapt to a too much AI, back off a little bit. In large companies, they have a lot harder time with that...”
• On Leadership in Growth:
  [27:42] Joaquin: “We were ruthless, like removing committees, removing group thinking, and coming back to very quick decisions, extremely fast executing them.”
• On Engineers’ Future:
  [34:12] Joaquin: “If I need precision, what I want, I'm not gonna need you in one year, man... you need to understand the user, ... come up with ideas...”

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Timestamps for Important Segments

• 01:41 — Joaquin’s background and bootstrapping in Spain
• 04:13 — Generative AI as a new abstraction layer
• 08:16 — Freepik’s history and the existential crisis from AI
• 12:33 — Recognizing generative AI as disruptive threat
• 18:46 — Pivot: Focused on strengths, not building models
• 23:19 — Multi-pronged AI adoption: integration, innovation, acquisition
• 24:33 — Realizing the limits of Gen AI for core stock content
• 27:42 — Organizational changes to speed up adaptation
• 30:53 — Shifting strategy to focus on professional users
• 34:12 — The evolving role of engineers in the age of Gen AI

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Conclusion

Joaquin and Darren’s conversation is a compelling roadmap for how startups can not only survive but also harness disruptive technologies. By focusing on core strengths, integrating rather than competing on AI, being agile in organization and product, and listening closely to users, Freepik was able to pivot quickly and find new growth in the age of generative AI.

For anyone navigating digital transformation—especially in high-disruption sectors—this episode is a blueprint for resilience, adaptation, and strategic focus.

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Find out more about Freepik at freepik.com.
For more episodes, visit embracingdigital.org.

Transcript

[A]

It feel like at some point I feel a bit trapped. It's like, you know, there's no way to go. Like we don't have any right to win. We don't have the, like, the technology to make it happen.

[B]

Yeah, I bet that would be very disconcerting. Right, because you've pumped all of this time and injury into this company. You found a great niche, largest download site. Right. Making good money and all of a sudden, something from the side, completely disruptive. Welcome to Embracing digital Transformation, where we investigate effective change, leveraging people, process and technology. This is Darren Pulsford, chief solution architect, author, and most importantly, your host. On today's episode, Pivot or perish. Freepik's explosive growth in the age of Gen AI. With special guest CEO of freepiks, Joaquina Bella. Joaquin, welcome to the show.

[A]

Thank you, Darren. Very happy to be here.

[B]

Hey, Joaquin, you're in Spain, so it's the afternoon for you, it's the morning for me. So welcome. How's the day going so far?

[A]

Brilliant. Like, I was recently in London. I'm here in Spain for the whole week and we have, like, beautiful weather. Very nice so far.

[B]

All right, so maybe it'll be a beautiful day here in California for me. So before we get started on our topic today, which is the digital transformation, how adopting gen has really helped you and your company. I only have superheroes on my show. Every superhero has a background story or an origin story. So, Joaquin, what's your origin story?

[A]

Okay, so I started coding when I was 8 years old. I don't know why, I just love computers. I managed to get one in 1984 that I use mainly to play, but I've been hooked since then. I've always been coding since I remember. My background is in tech. I studied physics and computer science and then I started making startups because a friend of mine pushed me a little bit to create a startup. My first startup was acquired by Google. That was in 2007.

[B]

Congratulations.

[A]

Thank you. Thank you. So it works around photography, was geologated photography and it became part of Google Maps and Google Earth. And three years later I came back to Spain and I co created a couple of companies and well, it's been. They have been growing since then and we are pretty happy.

[B]

Yep, that's. That's a. That's a great story. So in Spain, making things happen with startups and technology there. I think that's awesome.

[A]

Yeah, yeah, it's been like the main difference with the US is that there is not so much venture capital so actually all my companies have always been bootstrapped. Like we started calling them. We are using like a couple of friends that join forces and then we just take it like little by little.

[B]

Well that, that's great. Now has that changed much at all with, with the new technologies that are out there, like generative AI? Because you could bootstrap a lot more with gen AI helping you out than you could in the past. In the past there were so many barriers to entry into different markets. Either capital I had to, I had to raise capital so I could have equipment. Now there's cloud, now there's generative AI. I need a salesforce. I. There's a whole bunch of really interesting things that come to play. So have you guys been able to leverage that at all?

[A]

Yeah, absolutely. Like, and I think now it's better than anyone like that anytime in the past, like, I remember when we started the number of things that you had to deal with. Like on my first startup, we had the server on the living room, you know, you had to host yourself. And since then, you know, we got more and more levels of abstraction. So at some point we were able to host servers and warrants in a data center. And that was great because when the electricity went down, the website was not coming down, you know, like very important things. Then I remember for me like the next big step, it was AWS S3 because then you will have like an infinite hard drive. And we have been building like those abstraction layers one on top of the other and the next one is AI, which basically makes almost like the whole company. It makes an abstraction layer over almost any position. So you can now have an engineer, you can have a designer, you're going to have a competent marketing person. In general, it doesn't yet achieve like the 99% level of genius. But you don't get incompetent either. Like you get something that is decent, okay, which is pretty important. Like helps you double check, it helps you. It's a basic level of intelligence that you can use now and I find it super useful.

[B]

No, I totally agree. I can't completely trust it, but I can give it mundane tasks to do or to give me some ideas on prioritization or what are the next steps to move forward. Right. Is that what you're seeing too?

[A]

You know, funny thing is that nowadays that's a bit surprising. But I'm interested in it more than some experts. And the reason is when I don't know the expert.

[B]

You don't know yet, right?

[A]

Yeah, it's like you don't know if they are really competent or not. And sometimes it happens that you met people that were supposed to be competent, but they just screw up in some major ways. Okay. We think, I, I don't have, I don't have that fear. I think that they are quite decent overall, you know. So when I get, when I start working with a new expert, typically I double check what they say with AI and then you know, if it's, if it's over. Right. And it builds trust on this new expert. But to me is helping as a double check on everything that I do. And that's why it's so useful I guess like when you kind of know what you're doing but you know it can help you tremendously if you have no idea eventually the parts where it does wrong, where it fails, you will not be able to correct it and everything falls down. But if you kind of know what you're doing, you can, you know, it's like a person that is quite proficient, you know, with diy, you know, doing work at home and things like that. And, and you have like a magic wand that can put things in place but every now and then makes a little mistake. You know what you're doing. You can get there with a hammer, you know, correct than this one. But it will be so useful. Okay. It's a little bit bad. It's a magic wand. Every now and then things don't fit together properly and you know how things work. You can go there and fix that little one, you know, and keep going.

[B]

That I, I totally agree with that. I, I, I see the same thing with my production company that produces the podcast. Most of the time it's, it's pretty good and it's, but I have to still be there and guide it and, and, and we share ideas back and forth. But it's still my direction.

[A]

Yeah.

[B]

And right. It's, it's still me guiding and directing.

[A]

The direction that I think the metaphor of, of a magic wand is, is quite spot on because you know, you, you, you are the magician that, yeah, you're the magician. Yeah, I love that. And sometimes there is a spell that doesn't work for some reason and it just, you know, and sometimes it's just some, some little screw up into something that it does, it's overall right, but not 100%.

[B]

Now the, the startup that you're working on right now give me an idea of, of its background and the shift that you guys were able to make quickly to take advantage of Gen AI because you Guys have a unique. A unique position in the market.

[A]

Yeah. I mean, this company, we started it at the end of 2010. So as you can imagine, it was not AI when we started. We started the company on the stock image industry. So for those who don't know how it works is stock images are images that can repeatedly be used for a single use case. Okay. So you can imagine like two people are smiling in front of the camera and that they look like construction workers. Okay. So you can take that image and you can use it in multiple websites that just work with construction workers. And over the years, we got like digital libraries with millions, tens, hundreds of millions of those images. Okay. And we were one of those. And we were extremely popular because our library of free assets, those who you could download for free, it was. It was the biggest in the market. And we. That's why we came extremely popular. We started doing illustrations and then we jump into icons, photos, slides. So it's pretty comprehensive.

[B]

Yeah, I can use it in a lot of different marketing materials or slide decks or whatever. Right?

[A]

Yeah. So in terms. Exactly like. And in terms of traffic, Freepik was still is the most popular in the world by quite a gap. So it's pretty big in terms of traffic. Now in terms of revenues, given that we give so much for free, we were always like one step below of Shutterstock I stock and other players, but catching up. Okay. So the business was doing pretty well. We have a premium component, so you. If you sign up on freebig, you get access to even more resources. Okay. That's. That's the added value. So that. That was the product in 2022. So you can imagine when Dali 2 came south, it's like, yeah, didn't that disrupt you guys?

[B]

Like, do I even need you guys anymore? That's.

[A]

That's tough. Like, wait again.

[B]

Yeah.

[A]

No, but even. Honestly, even Dali1, I was quite puzzled. So with Dali1, it was like, wait a second. So you ask for a radish that is walking little dog with a tutu, and it made that like, you know, it was. It was like. It was quite crude as a drawing, right?

[B]

Yeah, at first it was.

[A]

Yeah, it understood. The whole thing to me was amazing. It was like, what the heck is that? But I didn't thought that it was going to get down to the last mile. You know, like when you work with images and people have like so much creativity, you get those beautiful images like this. Impossible, like to get to a photography like this with the makeup, with the lining, with all the. There's no way. Like this thing was miles away. Okay, right. Came out. And the improvement it was the quantum lip. It was just I was looking at this and it was like this thing there already it was useful. There are use cases where I say, I will rather use this than to hire somebody to make myself administration.

[B]

Oh yeah, absolutely.

[A]

Some use cases, not all of them. And we all understand the Dall E2s. When it came out, plenty of images that were a piece of crap.

[B]

Oh yeah, yeah, yeah, yeah.

[A]

So. But you spend five, 10 minutes, you struggle through it, you squeeze it, and you can get an image that was decent. And to do it manually, it was like one week with, you know, with an illustrator. So there were use cases already there with Dall E2. And of course, to me, it was like, to me Dalito, at least mentally, to me, it cross the limit of this thing shows hints of having creativity. It got some tasks and with there were sometimes like a prompt that explains so little. And it came with an image that was so original. This thing is showing what they call creativity.

[B]

Yeah. So you guys saw this as a huge threat to your business model.

[A]

It was.

[B]

So what do you do? Do you just close up shop and live on the the Spanish Riviera? I mean, what do you do?

[A]

That was plan A. No, plan B is okay. I thought a lot about this and I started remembering when we started the company, why we did it. And it was because of a need that we had. Like we were creating websites and finding the right image was always the bottleneck. Okay. So I said, like, listen, this technology really helps you find the right images on so many more use cases than just stock images. Like, stock images are great if it's okay to use something that exists already. But there are many use cases where you cannot do that. Like if you want a logo for your company, you cannot use something that already exists. You want something unique. Right?

[B]

Right.

[A]

You want to make an illustration with like yourself and, you know, your loved ones. It has to be bespoke. Like you need to provide. Those are who we are. And I want an illustration roughly like this. So there are plenty of cases where people wanted to get easily like a particular image. And we were not an answer for that before. So it just helped me understand. Okay. You know, is so much more that we can do if we adopt this. It's not just stock images, but we didn't knew how to do it at all. You know, it was like it feel like at some point I feel a bit trapped. It's like, you know, there's no way to go. Like, we don't have any right to win. We don't have the, like the technology to make it happen.

[B]

Yeah, I bet that would be very disconcerting. Right. Because you've pumped all of this time and injury into this company. You found a great niche, largest download site. Right. Making good money and all of a sudden something from the side, completely disruptive.

[A]

Yeah.

[B]

And now you may not have a company.

[A]

Exactly. So we were at the time around 500 people. So all that was going through my head, okay, how do we deal with this and how we can turn the company into something that is useful to people and still be relevant. So I had to revisit all the reasons why we didn't have a right to win, which is, okay, we don't have the technology to actually make this happen. But then I started thinking about, wait a second, this is gonna keep getting better and better. This is gonna keep getting cheaper and cheaper. And this is gonna keep betting, getting in general, it will just keep improving exponentially. We're already on that trend. Okay. So I bet there's gonna be competition like creating those models. Okay, how is this competition gonna discriminate? How are they gonna put themselves apart? Well, in capitalism, you usually when you have a product that is very similar, you make it cheaper, you want to sell more. So my intuition is that there's going to be some strong competition that is going to drive margins down on those things.

[B]

Right? Yeah, that's typical. Right. That's the typical market.

[A]

And I started thinking on the times of when we got CPUs, I thought that was very similar. Okay. And I remember like Microsoft and Bill Gates went through that through process is okay, CPUs and general chips, this thing is going, is getting better and better, cheaper and cheaper exponentially. So that means that all the margin is going to be captured on the layer that is on top of it. Like, if you start developing software that uses CPUs automatically, this software is going to get more and more useful to more and more people without you doing anything. There is a tremendous amount of value that will, will just be able to capture by sitting on top of.

[B]

On top of. Oh, that. Yeah, that's. That's right. Yeah.

[A]

And if that happens, I don't need to have expertise creating models. The only thing that I need is somebody creates a model and they want to license it. I need to be able to put it in the website with a nice UI. We have some people that know how to build UIs, because that's what we have been Doing for the past 14, 15 years now. So we said, okay. And indeed somebody came out. So Even before Dall E2 came out to the market, we got stability AI and they launched their first open source model. Was great. Let's pick that one. Okay. So we picked what was at the time SD 1.5. So we took it and we put it on the website and we started getting feedback saying, yeah, it's very difficult to explain. When I want a visual style, of course you can prompt it. You can say, hey, I want the style of any artist and make something that looks okay. Can we make it easier? Okay, maybe we can just give them, like little previews of different styles that we will collect. And when you click there, the only thing that we do is invisible to you, but we add to the prompt in the style of xyz.

[B]

Right.

[A]

So that happened behind the scenes. Okay. And then people started coming with more feedback and we gave it the rating on that feedback and the product started getting better and better. And that was basically at the end, it's exactly the same thing that we're doing with before. We started with an idea and we just listen to users and iterate on that. But now the potential, it is much bigger because it is really much more useful to the user. They can do exactly the image that they want.

[B]

I love how you said there, we knew what we were good at, and I leveraged what we were good at. You didn't go off and say, no, oh, I need AI experts. You said, no, I'll license that. That's right.

[A]

Right.

[B]

Because that cost, that cost of retraining all your people and not relying on your strengths is astronomical and it will kill a company. So I love how you guys said, hey, let's. We're good at certain things. Let's double down on that and integrate with these other layers, these new technologies that are in. I'm sure you had to buy. You know, you had to go out and get a couple engineers that understood the fun fundamentals of these models. But you didn't need to create your own model.

[A]

No. Right. We got extremely lucky because there were a few people in the company where as excited as I was on AI, and they were very happy to, you know, they knew all the different things that were popping up and they lean in in terms of, okay, yeah, we want to work on this. Let us help here. But, you know, like, we had this for us was so critical that when something is so important, we had in front of us, like, multiple options. We can build something in house. We can integrate third parties or we can buy something. Right. We did the three of them, actually. So it's, yeah, we integrated. As I mentioned, I was like first. Yeah, yeah, yeah, yeah, that, that exists. I started creating an AI team. So we hire our first researcher and then a second researcher. And they have been doing things a little bit on the edge that helps improve images. We, we are not competing on the core image generation thing. Okay. But we are competing a little bit on the edges. Like for example, when we, you can inpaint an image, you can go over an image or a small region and regenerate it. Okay, so that was something that helps because.

[B]

So that's right. So you were finding unique value added to the current models that maybe the big researcher guys weren't paying attention to because it wasn't that important to their customer base. So you guys understood your customers really well, played on your strengths and, and found additional niches where you could leverage. I, I, this is a great strategy. Walking.

[A]

Yeah. And then eventually, like the third one, why we were lagging of, like, I was getting close to everybody that was kind of somebody on, on AI, at least in Spain. And one of those people created a company called Magnificent. I tried to hire them before they created the company. He was telling me, hey, if it doesn't work, do you still have that offer? Sure. But the company was a phenomenal success. It was an incredible success. I never seen anything like this in my life. But, well, I still doubled down and we managed to get an agreement and we actually acquired the, the, the company, which is called Magnificent, is a very popular upscaler. It actually created a new category which is a creative upscaler. An upscaler is something that gives more resolution to an image and yeah, so.

[B]

That'S very, that's very cool. Especially if you've got a grainy image.

[A]

Exactly.

[B]

Right. So you're, you're predicting or guessing what the pixels would be if I were able to zoom in post.

[A]

Sorry. Yeah. The insight that they had is that more and more people were creating images with AI and they didn't care that much about the image. They wanted something that had more detail. So their insight was we don't need the upscale image to be exactly identical to the original image. We can call freedom because nobody cares really about the original image if it's AI generated anyway. When they did the upscale, they had more little details. And that helps a lot because sometimes they are adding more texture to the skin or, you know, to anything. It just makes the image better. So this concept of an upscaler that makes the image better. It was a perfect fit. And, well, we acquired them and it's now part of the company, part of Freebie. So we actually did the three things. So it was a bit of everything. But I think that when something is really critical to your company is like, you have to go all in, like, and try a bit of everything. So.

[B]

So here. Here's my next question. Your stock images, are they still available? And do you use Gen AI to tap into those? Meaning, hey, I've got a stock image that fits your description pretty well. Can I show you that as well? Are you still leveraging some of the. The assets that you already have is, or are you just saying now we'll just go to Generative AI and everything?

[A]

No, no, we are. We are still leveraging it. Listen, people that come to Freepik to download stock assets, very often they do not like AI assets. And there are multiple reasons for that. Like, I remember a customer that was complaining because he got one of the very early AI images and he didn't realize it was not clearly level. Hey, this has been AI generated. So he downloaded it. He went to the printer and just went just before he was going to print a big banner. Then he looked at the image was, wait a second. Why does this chair has six legs? That's for them. That's money. You know, they were going to.

[B]

Yeah, yeah, yeah.

[A]

And then you are screw up. It's like, man. So that begins. That was. I said that we were ready to get it wrong by doing too much AI. You see, we did too little AI. If we make that mistake, we will be screwed up too much AI. We make that mistake, we'll end up in an okay position. Something that we can correct. And I think we did like too much AI. Like, part of it is accepting all the AI generated content as a stock content that was very high quality, and then the quality became lower. So that's something that we had to correct. We had to remove most of the AI generated content because it was not good enough. And that means detecting when it was generated, removing it from the platform, and correctly leveling the one that we keep. Okay, so, yeah, there were. There were a few. A few mistakes along the.

[B]

Along the way, but we still adapted quickly. That's one of the benefits of being a small company is you can move quickly, you can adapt to a too much AI. Back off a little bit. In large companies, they have a lot harder time with that. Right. Because they have committees. Oh, we're not even gonna. We're gonna look at this for nine months or 18 months to figure out what would be the perfect thing to go out. I love your guys's approach. Let's get it out to the customers. Oh, a little too much AI Back it off a little bit. You had that flexibility in your business model to do that. I, I think, I think it, it's gonna, what, make small companies thrive in this atmosphere.

[A]

You know, we, we were on the path to that. So we were already like 580 people at the end. Like, we're starting to have committees and, and to make it work, we need to get back to, you know, one person has the authority. We don't discuss this. It's his opinion. Go ahead, you know, and, and just give responsibility to people. And this is your thing, you dumb. You're it up. It's you and you succeed. It's you.

[B]

So that's hard. That's hard though, when you get more and more people, right? You hire people because they're, they're contributing to the company. So it's this really weird thing in our culture today where everyone, everyone wants to have a say, but ultimately, as the owner of the company, the buck stops with you. So you either have to delegate that decision making to an individual instead of to a group, because anytime you have a group, group thought and group decision, it takes forever to make a decision. Right. It's good to hear all the opinions and then have someone making a decision. This is where we're going. Let's move forward. Otherwise you get stuck and you can't.

[A]

We were ruthless, like removing committees, removing group thinking, and coming back to very quick decisions, extremely fast executing them.

[B]

And how was that, how, how was that transition? Was that a hard transition to make or.

[A]

Some people. Yes, for some people. Yes, for some people it was actually much better, much less stressful because sometimes when you get also a meeting, it is not exactly clear who owns the bug. You know, who, who is actually taking like, and what is the agreement. And sometimes we have like, we came out of the meeting and somebody thought that the conclusion was a somebody for the.

[B]

I'm laughing because that happens in all companies.

[A]

Yeah, we got like, yeah, you put it in writing, but you put it in writing and then nobody was reading it. And then people came back. No, no, no, no. That was not the agreement. And what you brought is, you know, it's not what we are. But like, man, it is just. It is very difficult to make a group of people be more efficient than a single. And single person is extremely efficient. Like, if you manage to Keep everything in your head. It has some little downsides. You know, I'm okay with the downsides.

[B]

But. But still you need some kind of scale. So how. What do you guys do at Freepix? What do you guys do? Do you have the decision, Are you pushing the decisions down closer to where the work is done or is everything still at a higher level? Decision making, this is what we're going to do, go do it. Or are you pushing those decisions down?

[A]

Is we create a level of very, very high level of strategic decisions. Okay. In our case it was reflecting the market. That's my opinion. Okay. My opinion is that the market for consumer grade casual usage of generative image, that this is dead. Okay. My opinion is that ChatGPT is doing it. Your iPhone will do it, Google will do it like you will, anywhere that you want an image, just a regular image, you will be able to get it for nothing. Okay. So I don't see there a way where we can survive if that's what we do. They say okay, but there are people who really care about the final image. We are ready to go on a journey and a process to improve the image. Share it with others. They need other opinions, you know, iterate on that. And that iteration, that process requires sharing data requires like having having state of the art model visual styles like upscalers, like, you know, like you have to put everything together. So we say, okay, we are going to work for these professional users, not so much the casual user, which we think are going to go to ChatGPT. Right.

[B]

Okay. So you retarget. So that was a decision that you made at the executive level. Right. Hey, this is our new target. This is where we're going to focus our audience, our customer. And then you're pushing tactical decisions down in the hierarchy.

[A]

Exactly. So the decision high level is we work for professionals. What they need that they don't have today is control over the image. So you can type something and then you get an image. Sometimes you want that because sometimes you want inspiration. Okay. But you don't have to this. If you have a clear idea, you want to pass that into an image. The AI does whatever it wants. Right? Right. It's very difficult to get a controllable steering wheel. Wheel so to say. So we are working to provide that, to provide them with videos, audio, everything that they need to make a media production. Okay. So it's professionals, it's giving them control and it's video, image, audio, everything. That's a high level direction. Okay. But then the teams need to translate that into. Okay, what can we do to support that? Okay, so for example, let's check out the team that handles subscriptions. They know that we are going to go for videos. They know the videos are way more expensive. Okay. We need to put in place a subscription that is more expensive. And those things, they cost so much that we need to charge credits to the user. Okay, that's, that's a natural consequence. Like you are just doing image generation maybe, and cheap image generation, maybe you can get away without credits. It's relatively cheap. You can put it under a subscription. That's what Saggy PD does, for example. But you do. Videos are very expensive. You need to account for how many, how to create it and charge credits.

[B]

But this whole, this whole idea is that as we go down the layers in the organization, the decisions are made close to where they need to be made.

[A]

Yeah, exactly.

[B]

They didn't have to come back up and say, hey, is it okay if we do this one thing? Because you've already established what the direction was.

[A]

No, no. And we encourage them to talk to users so that they understand what are the next pain point where they can help. And we do like plenty of user interviews with surveys, data collection, like all of it. Yeah, but it's the people around the ground taking decisions. And actually we are pushing it below the PM level. We are working more on. We want the engineers to understand to whom are they working for and what are their needs and why they are doing what they are doing.

[B]

I love that because I think a lot of times the engineers get disconnected from their real purpose in writing code or doing a deployment or whatever. They. They're so disconnected from the end customer that maybe they're not going to do the right thing.

[A]

And I actually think that that's where the profession is going. Like some of them, and I, I got some people that don't like that they have a different idea on what an engineer is. That is more like, you tell me what you want and I got that for you. And that's not how it works. Okay. Especially today. Because if I need precision, what I want, I'm not gonna need you in one year, man. Like, if you don't adapt to this new reality where you need to understand the user, you need to be able to talk to them and you need to come up with ideas to how to.

[B]

Well, it's just like your company, Joaquin, if you guys just said, this is what we do, this is all we do. And you didn't adapt. And so software engineers need to adapt as well. I need to talk to customers. I need to understand how to ask questions and because generative AI can do a lot of the heavy lifting of coding.

[A]

Exactly right.

[B]

But software engineers know how to take requirements and gather and ask, ask those abstract questions to now, you know, put that into a way that a machine can actually make the work done.

[A]

It's actually helping us like, get also, like smaller teams. I mentioned the committees before. Like, the smaller the team, usually the more efficient they become. Okay. Like, the more they can do and using AI, they can do way more than before board. And like, sometimes it's in both ways. Like, somebody takes the interview, they. Sometimes they don't go to the interview, but ChatGPT makes a summary of the interview. You know, it fits them what are like the main points and you know, you can even ask the ideas on how to solve the main problems. You know, and they can also think, talk with others and then they come with the ideas they want to implement. And AI is helping improve. Absolutely.

[B]

Hey, Waken, this has been incredible. If people want to find out more about your company, it's freepiks.com is that.

[A]

That's it. P I K. So freepik.com yes.

[B]

That's great. Thank you for coming on the show. This has been very insightful. I think you guys, I think you guys adjusted really well to, to this very disruptive technology. So way to go, man.

[A]

Thank you. And I guess this is going to just keep going. Like it looks like every year there's a new revolution going on.

[B]

Oh, yeah, yeah. You got to be. You got to be able to adapt quickly, that's for sure. Thank you for listening to Embracing Digital Transformation today. If you enjoyed our podcast, give it five stars on your favorite podcasting site or YouTube channel. You can. You can find out more information about Embracing Digital [e-mail] Until next time, go out and embrace the digital revolution.