Shifting the Paradigm: How GEO is Changing the Brand Narrative
The fundamental way users interact with the web is transforming. For decades, Search Engine Optimization (SEO) was the holy grail of digital discovery, forcing companies to battle for top positions on the first page of search results. However, as LLMs increasingly act as digital research assistantssynthesizing information from across dozens of web pages and serving users a singular, unified answertradi
tional consumer journey is shrinking. In this new reality, companies must shift their focus toward Generative Engine Optimization (GEO) to measure, improve, and control how their brand is understood and recommended by artificial intelligence.
Achieving category leadership through these tectonic shifts requires more than a standard tech stack; it demands a distinct operational velocity and a highly intentional culture. In the latest Techspace Pod episode, Daniel Drabo, CRO and Co-Founder of Berlin-based Peec AI, shares how his organization cracked the hiring and product code to scale exponentially, growing from 30 to nearly 70 employees and hitting $5 million in ARR in under a year. From mapping the impact of social media authority on LLM citations to executing high-visibility guerrilla marketing campaigns, Drabo offers a blueprint for how modern startups can leverage speed to outpace slow-moving legacy institutions.
4 Key Takeaways from the Episode
- 1. SEO and GEO Rhyme, but Success Requires Breaking Silos
While traditional SEO remains the baseline index that language models query, AI search criteria are far more diverse. LLMs look past standard domain authority to synthesize information from subreddits, digital PR, and social media platforms. To win, marketing departments must break down functional silos so that SEO, PR, and community management work in tandem. - 2. Social Footprints Control the AI Political and Brand Narrative
A collaborative study conducted by Peec AI and The Guardian analyzed over 5,000 prompts to see how UK political figures were represented by AI. The data revealed that entities with massive, active social media footprints (such as Nigel Farage) gain significantly higher visibility in LLM results. Because AI lacks traditional journalistic filters, an active social presence directly impacts the narrative the model builds for users. - 3. Proactively Audit and Correct LLM Hallucinations
AI models frequently cite incorrect or outdated online sources, creating "false facts" that can actively cost a company revenue. Peec AI uses its own platform to pinpoint exactly where these hallucinations stem from, enabling automated workflows to correct the underlying source data. For modern brands, continuous monitoring of AI output is mandatory to ensure feature and compliance accuracy. - 4. Build or Adapt Into the Workforce You Need for Next Year
When operating in a hyper-growth venture space, stalling on decisions or waiting to hire until a role is desperate is a critical mistake. Startups must have the courage to hire for the scale they expect to reach in 8 to 12 months, accepting that fast execution means making decisions on imperfect data and adjusting along the way.
Check out the full conversation below.
------------------------------------
Jane Wakefield
Hello and welcome to the Techspace Pod. And I'm very pleased to say that I'm here with the co-founder of Peec AI, Daniel Drabo. Welcome.
Daniel Drabo
Thank you so much for having me.
Jane Wakefield
So before we get into the discussion about Peec AI, let's talk a little bit about you. Have you always been an entrepreneur? You know, what was your journey to get to Peec AI and what is your role within the company?
Daniel Drabo
So I am the CRO of the company, so I handle everything revenue and sales related. However, I have a background in law, so I was once a law student that didn't want to become a lawyer. I was always running—I spent a lot of days surprised—I was running my little side businesses, always interested in tech, entrepreneurship, etc. So after uni, I was working in Texas for about three months and pretty much immediately quit to start my first proper startup where we turned layoffs into payoffs.
Daniel Drabo
So we held people that got fired, get a severance payment, did that for a year, and then went through Antler Startup Incubation program, where I met my co-founders and we started Peec AI.
Jane Wakefield
And what was it that attracted you to Peec AI? What is the thing about it that excites you?
Daniel Drabo
So I was always super excited about discovery and search.
Daniel Drabo
I was always excited about AI and what we're doing at Peec AI. Pretty much bridges all of those in a perfect way. I also think that there is—it's pretty much the most exciting times to run a business. I always like to compare it to, like the .com times where the internet is coming up.
So we're going through a very big platform shift right now, and there's nothing more exciting as an entrepreneur to pretty much be at the forefront of that platform shift, where everything is changing in tech.
Jane Wakefield
So yeah, and yeah, there's a lot of AI companies. The UK seems inundated with companies that are claiming to be using AI. Is it the same in Germany? Are there hundreds of AI companies and how do you kind of get your voice heard above the noise?
Daniel Drabo
Yeah. So Germany, we still have a pretty solid startup ecosystem. However, it kind of moved a bit more towards the south of Germany, Berlin.
Daniel Drabo
We still have like a few companies that are making noise, but if you're looking at it right now, with our growth pretty much in the last few months, and also with our marketing campaigns and everything we did around hiring, we were able to cut through the noise quite, quite easily.
Jane Wakefield
So let's talk a bit about those marketing campaigns, because on the billboards and in your adverts, you're kind of positioning yourself as a very ambitious company, as a company that's like working in Silicon Valley.
Jane Wakefield
First of all, why have you gone with that sort of marketing campaign? And secondly, is it working? Are you getting people?
Daniel Drabo
Yeah. Good question. So if you are driving through SF or if you're driving through New York right now, you're pretty much seeing like startup advertisements everywhere. And if you're in Germany, Berlin, you do not see that.
And we realized after being in that this is a super, super obvious play, because if you again want to cut through the noise, if you want to be seen, you kind of have to go different routes.
Daniel Drabo
And yeah, we have a very, very kind of tight ecosystem in Berlin where most of the tech companies sit. So with a relatively low investment, we were able to cover a lot of ground in terms of gaining visibility, in terms of attention.
And that way it was pretty much like a no brainer for us to start with our other form campaign very early on to attract talent and also just to make some noise.
Jane Wakefield
And has it attracted talent?
Daniel Drabo
Yes, for sure. So we have a lot of people that come in inbound that mentioned, hey, we've seen the stickers on the ground, we've seen the billboards and the train. So it was a pretty great employer branding campaign. And of course the weeks have seen it and everyone in the ecosystem has seen it.
Daniel Drabo
People were sharing it on LinkedIn, on social. So generally super, super successful campaign.
Jane Wakefield
So what is the headcount now? How have you grown and how do you find people with the specific kind of talents you need? Because this is the big problem for AI companies, isn't it, that they're kind of almost ahead of what people have been learning at school and at university?
Daniel Drabo
So there's a very small pool of talent out there. So we pretty much exploded in size in the last few months. So towards the end of 2025, we were still about 30 people or even less. And now we're almost 70 people here in Berlin.
Finding talent is one of the biggest challenges as a startup. I never realized it before. It was like, okay, it's about selling and building the product. In fact, it is about finding the right talent.
Daniel Drabo
We also have a very, very high bar when it comes to tech, when it comes to people that are willing to put in the work, and therefore we really had to crack the hiring code. I think for engineering, we did it very, very well because from the get go, we knew, okay, we have to over-invest.
And we worked with a lot of different recruiting agencies and we started to do it in-house. We now have a super strong talent team.
Daniel Drabo
We cracked it for engineering, and now we're in the process of cracking it for sales, growth, etc. And yeah, over the last few weeks it has been going super, super well. We now have the processes down, we have good challenges, we have a good interview process. So we're now on our way to just continue the growth and add headcount as long as we need it.
Jane Wakefield
So when you say crack the code, what is that? Is there sort of a process that you found kind of works to get the best?
Jane Wakefield
And are you prepared to share that?
Daniel Drabo
Yeah, 100%. So in the end it is a bit like sales. Or you can think of it like a funnel. Yeah. You will have an amount of input and an amount of people that come inbound, an amount of people that you book meetings with—just like the top of the funnel.
Daniel Drabo
And then obviously at the end of it, you will have a conversion rate. You will have a percentage of people that actually convert after you're sending out an offer. And you can, you know, look at it very analytically and just see, okay, if we are hiring 0.1% of the people, then obviously if we want to hire ten this month, we have to, you know, add X amount to the top of the funnel.
Daniel Drabo
Then through the interview process, then through the different challenges, etc., obviously that amount of people becomes less and less, and this is kind of how we're approaching it. And if we're seeing, okay, we are losing a lot of people here at the challenge or we're losing a lot of people at the initial first interview, then, you know, those are like the things where we have to tweak the process.
Jane Wakefield
But is it also a case of, you know, you have to put out a competitive salary?
Jane Wakefield
Because we look at the companies like OpenAI, they're offering bar salaries for anybody with any AI expertise. Can European startups compete with that?
Daniel Drabo
Good question. So I think this is one of the main reasons why we're in Berlin. Because in Berlin you do not have any OpenAI or Anthropic that you're competing with. Of course, you have some people that actually move to London, that move to US.
Daniel Drabo
SF, but generally here in Berlin we compete much less when it comes to tech talent compared to, for example, a city like SF. And of course the salaries—they have to be competitive, but it's a very different story if you're comparing SF salaries to Berlin salaries.
So being in Berlin can also be a competitive advantage because obviously you burn through your funding much slower than a company that has a SF office and a New York office and is hiring engineers at like 200 to 300K yearly salary.
Jane Wakefield
So you mentioned that as an advantage for Berlin. What else makes Berlin an attractive place to be for a tech startup?
Daniel Drabo
Good question. So Berlin is still relatively cheap if you're comparing it to Paris or London. Not everyone would say that, but especially if you're looking at like people that work in tech, it is relatively cheap.
Daniel Drabo
We have great nightlife, we have great summers. Winters are rough, but summers are a lot better than in other European cities. So therefore people like Berlin. I was born and raised in Berlin. I have my network here, so generally a great city.
Jane Wakefield
And you talked about a lot of the startups have moved to the south of the country.
Jane Wakefield
Is that what's caused that? What's that migration about and what city are they based in?
Daniel Drabo
Good question. I think that has to do with, of course, the technical universities in the South, like Munich. Generally you have a lot of engineers in the South. You have like a lot more hardware and everything around this.
Daniel Drabo
So it's just that you kind of have those universities pushing out the talent and therefore also bigger companies deciding to open up their offices in Munich, for example, instead of Berlin, because you have a certain type of person, certain type of talent there, which of course then kind of has an effect of an ecosystem evolving there.
And in Berlin, I think we had this a few years ago. Of course, when you think about like Rocket Internet, etc., etc., when you really, really had like a real ecosystem going, this kind of dipped a bit in my opinion, but now I feel that it's actually coming back on the rise again.
Jane Wakefield
Yes. Good to hear, good to hear. Now let's talk a little bit more about Peec AI and what it is that you do. It sounds like a fascinating company. Probably best for you to explain what your kind of key customers and what it is that you offer them.
Daniel Drabo
Yes. So generally, I think the most important thing to understand is that consumer behavior is shifting quite a lot right now.
Daniel Drabo
So a few years ago, people were on Google searching for something and then scrolling through those classical ten blue links, usually only looking at the first two, and then kind of making the decision and going on about their research. If you really, really want to find out about something, you might even touch page two on Google.
Daniel Drabo
But this is very, very rare. And with the rise of LLMs, with the rise of AI—people watch language models—large language models. Exactly. People suddenly have a different way of getting to the answer of a question they might have. And that way actually is a lot more convenient, right? Because they do not have to scroll through all of the different sites and links.
Daniel Drabo
But this is very, very rare. And with the rise of LLMs, with the rise of AI—people watch language models—large language models. Exactly. People suddenly have a different way of getting to the answer of a question they might have. And that way actually is a lot more convenient, right? Because they do not have to scroll through all of the different sites and links.
Daniel Drabo
It's rather the LLMs synthesizing everything that they can find on, for example, the first 20 or 50 pages and serving the user that answer. So this is a lot more convenient, especially if you're thinking about research—every product—especially if you're thinking about a buyer's journey where you have to learn something along the way. So this is pretty much what we're seeing in the market. This is pretty much what we're seeing in the data.
Daniel Drabo
And of course, as a company, as a brand, as a service, you want to be visible on the web, right? You want to be where your users are actually searching. And in order to find out whether you are visible, you want to measure this. So this is the first thing we're doing.
We're actually measuring the visibility of brands, entities, pretty much whatever in large language models.
Daniel Drabo
And then the next step, which is even more exciting to companies, is optimizing that visibility or improving that visibility in order to drive revenue. And this is the second part of what we're doing. We're providing our users with actions and recommendations in order to improve their visibility.
Jane Wakefield
Yeah. So you were talking earlier about this big shift in the way the internet works.
Jane Wakefield
And the move from search doesn't just affect consumers, it affects businesses. I remember back in the day, working at the BBC, search engine optimization—SEO—became a very important thing to us: getting the headline right, being up there at the top of those search things, because as you say, people are quite lazy.
They don't look below the first few things. That was really important. That was a key thing that we had to do as journalists, and it's key to lots of brands.
Jane Wakefield
But if that's changing, if the way people are looking for products and allowing AI to do their hard work for them, you're no longer really trying to appeal to consumers. You're trying to appeal to AI. So what does that shift mean? What are you seeing in terms of brands? Are they prepared for this huge shift?
Daniel Drabo
Yeah. Very good question.
Daniel Drabo
So obviously SEO is like the foundation of all of this, right? Because if you're thinking about how an LLM provides information to you, it does search the web on behalf of you. So you can think of it as like an intern, for example, doing research for you. You have a question. They go out, they look at a ton of different sites, and they kind of compile everything into an answer with citations, etc. So the foundation of being visible in AI search still is SEO, because the LLM queries a web index, right?
Daniel Drabo
And this might even be like the Google Index or any other index, and then retrieves those sites to give you an answer. So SEO still is the foundation of it. And I always like to say that SEO and GEO (Generative Engine Optimization)—they rhyme in a sense, because if you have bad SEO, you will likely also have bad visibility on AI search.
Daniel Drabo
However, when an LLM goes and does a web search for you, it takes into account a much larger amount of information. And this might be your own site. But the most interesting thing about it is that the LLM also looks at a lot of different other sites, and you will have a big chunk of social media in there.
Daniel Drabo
You will have a big chunk of publishers in there. Usually you will see editorial blocks, just like a much more heterogeneous set of different sites, which means that only by having good SEO, you won't be able to dominate the AI search results. You kind of have to think of all of the other areas too, which makes it a bit of a different challenge than just SEO.
Daniel Drabo
And the best brands we're seeing are taking this into account, right? Others that only want to focus on the SEO can be beaten by maybe a smaller player—a player that is deeper into what is happening right now in search, that is monitoring the results and that finds a way to move around the competition.
Jane Wakefield
And this is kind of illustrated really well by a study you did recently into political parties in the UK. And anybody that knows the political scene in the UK knows that the traditional political parties of Labor and Conservatives are being challenged on both sides of the political spectrum, both by the Green Party, but also by a company set up by Nigel Farage called Reform.
Jane Wakefield
So talk me through the findings of your study because I think it's absolutely fascinating.
Daniel Drabo
Yeah, it is in fact fascinating because we've been talking about brands, consumers, etc. before, but we did not talk yet about what other things AI might influence. Right.
Daniel Drabo
And this kind of makes a topic even bigger, because people are not only trusting LLMs when it comes to buying decisions, they're also trusting LLMs when it comes to political decisions, when it comes to health-related things—when it comes to a lot of very, very important things where you have groups of interests that, of course, have high interest in actually controlling that narrative.
Daniel Drabo
And politics obviously is one of them, because people do trust LLMs quite a lot. And when I want to learn about a certain political subject, maybe even when I want to make my decision in terms of who do I vote for, then I'm already asking an LLM. And obviously this will continue as the trust kind of grows.
So what we did is we were looking at the landscape of parties in the UK and we wanted to find out, hey, Nigel Farage and other leaders, how are they actually being represented within these LLMs?
Daniel Drabo
So we took a large set of prompts, over 5,000, and did a study together with the Guardian. And what we learned is that Nigel Farage is actually quite a lot more visible than his counterparts of the other parties. And that was the case because Nigel Farage is very, very visible on social. Right. And the LLMs, as mentioned before, they really like to take social media into account.
Daniel Drabo
They really like to take platforms like Reddit, YouTube, Instagram, even TikTok into account. So if you are a party that is very strong on social media, you will have an advantage in AI search.
And the interesting thing about it is that a few years ago—or still for many people, right?—if you would be using Google, you would rather click on media, maybe some sites that you know before—just like you would click on strong journalism, usually, because those sites have a high domain authority.
Daniel Drabo
Google also trusts them a lot more, which is why you usually find them in the top positions. With AI, you do not have that type of filter anymore, because the AI will just look at all of the results in a sense, right, and would give you a summary.
And if then social or maybe even media of a lower quality dominates the results, or if the content of those sites kind of resonates better with what the AI wants to see, you might find yourself in a situation where journalism of lower quality, in the end, controls the narrative and is pretty much what the user then sees, believes it, etc.
Jane Wakefield
Well, there's a lot of food for thought there for politicians, for journalists, for the public and for marketers. So what's your advice to customers? You know, if they're moving into this era where AI search dominates and AI can make its conclusion based on a vast amount of data out there, what can marketers or marketing departments in companies do?
Jane Wakefield
What are the key things they need to do to make sure that their brands are still kind of getting heard and getting seen?
Daniel Drabo
Yeah. Good question. So it kind of starts with breaking the silos, because right now everything usually starts with the SEO team. The SEO team is the first team that gets asked by the CMO or CEO, hey, what is going on with our visibility in AI?
Daniel Drabo
Right? It was their job before to make a website or to make the brand entity visible on the web. However, as mentioned, it is not only about your own site, it is also a lot about visibility on social. It is also a lot about PR and digital PR. And it's also, for example, interestingly, about how my product documentation—that the cloud bot might visit in order to explain my product to a user—is handled by the AI.
Daniel Drabo
So suddenly we do not have just the SEO team; we have a lot of different teams. And if you want to win at that or if you want to be visible and control your AI visibility, you kind of have to break those silos and start working on all of those things at the same time together. So this is quite the challenge.
Daniel Drabo
And the best teams we're seeing—they're already doing this, mostly starting to measure things from the SEO team and then coordinating things together in order to work on that subreddit that is about your company, or in order to work with the right media outlets that you're seeing appearing within the sources, or in order to work on the YouTube channel or like Instagram Reels or LinkedIn.
Jane Wakefield
Short video strategy. One of the problems with large language models is they don't always get things right. So what can companies do when an AI has picked up a false fact about a company and is amplifying that to the audience or to consumers?
Daniel Drabo
Yeah. Very good question. So the first thing that needs to happen is actually measuring what is going on. Right.
Daniel Drabo
So you want one layer of information that actually tells you, hey, I'm showing up here; here I'm showing up good; here I'm showing up bad—a way for you to kind of look at what the LLMs are actually propagating around your brand at scale. This is the first thing. And then what you mentioned before, the hallucination aspect or the aspect of potentially wrong facts, is a real issue.
Daniel Drabo
We had this a lot because we are growing very, very fast also from a product perspective, and we're shipping a lot of new features pretty much on a weekly basis. So we had the problem in the past where when you were asking an LLM about Peec AI having an API, or Peec AI having this and that feature, the LLMs were actually citing sources that got it wrong. Right.
Daniel Drabo
So we obviously knew this was a problem because it was kind of costing us customers. So with our own software, we were able to find out, hey, here are the specific chats or the specific problems where the AI models are getting that fact wrong about having an API or Peec AI having SOC2 or ISO.
And we were able to kind of pinpoint where those false facts were stemming from, and then reached out to the respective sources, or built workflows to reach out to those respective sources.
Daniel Drabo
And in order to change that, over time, those facts were corrected by the LLMs. And we made sure that this didn't happen again. But it's also an ongoing process as your product evolves and as new content gets published.
Jane Wakefield
Now, you talked about your product—your company is evolving quickly and your revenues are growing. You've gone from 0 to 5 million in 11 months.
Jane Wakefield
Yes. So what is it that has prompted that exponential rise? What are the products that you're shipping that are bringing in these very impressive revenue figures?
Daniel Drabo
Yeah. Very good. So I think one point is definitely timing. So we started to look into the space at the end of 2024 when we were at Antler and looking at things that were evolving and kind of just forecasting, okay, what will happen within the next few years in marketing.
Daniel Drabo
So we started to look into this very, very early on back when there were maybe 2 or 3 companies doing this. So we were at the right time in the right place. This is number one. And on the other side, we do have a very, very talented tech team and a very talented CTO, because it's one thing to know what you have to build.
Daniel Drabo
And then the other thing is actually building it, going to market quick enough, and being able to sell the product. And because we knew, okay, we have something here, right? We have that timing and we have a good product, we knew, okay, it's all or nothing. Right.
So we pushed very, very hard. We worked very, very long hours—we're still working very long hours—in order to capture as much market share as possible, because with those shifts, you often only have like a small time window of a few months or a few years where kind of the category winner is decided, and we're going for that category win.
Jane Wakefield
I gave the example of the study you did on politics. Can you give some examples of the types of customers that you have and the kind of things they're doing with your products, just to sort of put this in context?
Daniel Drabo
Okay. So generally companies that have been strong at SEO or that have had a strong focus on SEO, they were our first customers, right?
Daniel Drabo
Because they were impacted by losing traffic the most. They had to do something. Traditionally those industries are travel, e-commerce, but also software as a service. Generally everything that gets researched heavily, because here the LLMs took out a big chunk of the user journey because they were actually giving the users a much better search experience.
So that was pretty much the companies we started with that kind of fueled that initial growth.
Daniel Drabo
Besides that, we also are working with publishers a lot—again, because they have been impacted by the decreasing Google traffic. And of course, they care a lot about influencing the narrative that the AI creates around any topic, pretty much.
So we do have a lot of brands. We also do have some publishers, and we even have political institutions that we're working with.
Daniel Drabo
This kind of, you know, touches on the Nigel Farage topic. And my take is that this segment will actually grow quite a lot in the future, because if I'm, for example, working in a lobby group or if I'm working for any kind of political institution, the narrative is my job. So I really have to be able to measure and find out, hey, what is AI actually telling people around certain topics?
Jane Wakefield
Yeah, the political stuff is really fascinating. Obviously, we had the big scandal a few years ago with Cambridge Analytica and getting a lot of data from Facebook, but actually it turned out that—I don't think Cambridge Analytica was very good at helping explain who was going to vote for what party.
Jane Wakefield
Do you think that sort of predictive element of politics and democracy is changing? Do you think we are going into an era where we're able to take enough data to really kind of predict the results of elections, or is that still a way off?
Daniel Drabo
I think it's not getting easier. I think this is always like the master question that is quite difficult if you're looking at our software.
Daniel Drabo
In that sense, you can kind of compare it to social listening a bit. And social listening historically also has been used to forecast how certain political events will turn out. And what AI does is pretty much this, right? It looks at a lot of different sources, pulls all the data and then gives you its answer.
Daniel Drabo
Whether AI will be better at forecasting an election than, for example, studies you can do around what is going on on social—I do not think so. I think it is pretty much the same because they're looking at the same data as the foundation. But obviously politicians are going to have to change their behaviors and where they're kind of reaching out to audiences.
Jane Wakefield
Fascinating stuff. Now, we talked about SEO. You've used another phrase quite a lot: GEO. Do you want to explain what that is?
Daniel Drabo
Yeah. Very good question. So Generative Engine Optimization or Answer Engine Optimization are just acronyms for improving your visibility on AI. However, there has not been yet consensus on the actual acronym that we use right now.
Daniel Drabo
GEO and AEO are pretty much dominating, but we've also had LMO or other acronyms to kind of describe that process.
Jane Wakefield
Let's talk briefly about culture because, you know, you've been on this great growth spurt. Before we sat down, you talked about how you've recently moved offices. Have you seen a big shift in the way the culture works?
Jane Wakefield
Startups are always fascinated by this because they start with a very small team, and if they're successful—which they all want to be—that team often grows much quicker than a traditional organization would. What's the impact on that, and what have you learned from being in this from the start, when you had a very small company? What are the changes you've seen?
Daniel Drabo
Yeah, of course, growing means that the culture changes. In the beginning it was like very, very clear and easy to kind of maintain a certain culture without actually being aware of it, because you were just like a lot of people in a room kind of having the same mindset.
The earlier you are, the more like obsessed people are with the product. And as you grow, you actually have to make sure that this culture remains a lot more intentional.
Daniel Drabo
And right now we are going through like a high growth phase. So we suddenly have things like HR within the company. And we have to make sure that when we're hiring people, they're actually aligning with our values—that people are actually willing to work hard, that people are actually willing to be committed.
Daniel Drabo
But so far, this is going super, super well, simply because we're being very transparent with what we want to see from people and our expectations already within the recruiting process. So I think one thing that always makes us stand out is that we do tend to be very, very hard working.
And we're always telling people within the interview process that, hey, if you will work at Peec AI, you will be working long hours, and you might also be working on the weekend here and there if stuff needs to be done.
Daniel Drabo
And the people mostly are happy with that, right? It's always like a decision: what type of career do I want to have? What type of working environment do I want to have? What type of people do I want to have around me?
And the cool thing about our culture is that everybody is super ambitious, everybody is super entrepreneurial, and usually people think of their time at Peec AI as the station that will open a lot of doors to them.
Daniel Drabo
A lot of people want to go and find their own companies afterwards, and there's no better way than pretty much being as close as possible to that entrepreneurial journey before you go and find your own company. And this is pretty much the experience here you're getting at.
Jane Wakefield
It's interesting that you say about the long working hours because there's debates over that now, isn't there?
Jane Wakefield
There's some startups that are like, actually, I don't want my employees to work all hours; I want them to have sort of downtime; I want them to have a good work-life balance. Being upfront about the fact that you have to work hard is—if you're saying that up front, then you're obviously going to get people that take that on board.
Jane Wakefield
How do you deal with that then in terms of burnout? Do people kind of get a bit fed up with working such long hours? Are you seeing any kind of bad issues from that?
Daniel Drabo
I think the most important thing is, again, to be super transparent about it during the hiring process. So people really, really, really know what they sign up for. Yeah, this is the most important thing.
Daniel Drabo
And then besides that, it is of course important to be super transparent with the people and have the people also being transparent with you. So if an employee comes and tells me, hey, super, super long weeks the last month and I need some time off, or I need 2 or 3 days off—of course this will always be possible.
Because it is a situation where we have to capture a lot of market share, a lot of growth very, very quickly.
Daniel Drabo
But also we want to build a company that outlasts this like fast first burst of market growth. So of course you have to make sure that your employees are also in it for the long run and that they also know, hey, right now it's like a super intense period. But of course, as you grow as a company, this kind of always flattens.
Daniel Drabo
It's just like the natural development of things—that the smaller you are, the higher the intensity, and that the bigger you grow, the more normal it gets.
Jane Wakefield
Good advice. You've mentioned, you know, brands and other organizations that use your software. What about startups though? Because startups really want to get noticed, don't they? Do you have many startups on your books and if not, what would your advice be to them as they enter this new world where, you know, it's not so much search-driven, it's AI-driven in terms of marketing yourselves?
Daniel Drabo
So right now we have like a very, very broad mix of different customers—everything from very large enterprise brands to mid-market companies. But we also have a very good chunk of startups. And startups actually have a great advantage right now in times of AI and GEO, simply because a lot of the bigger companies that they might be challenging are moving quite slow, right?
Daniel Drabo
Some of them really get it, but the biggest chunk of them is moving quite slow. This is just like naturally if you're like a big organization. So what we're seeing, for example, in the CRM space or your space, is that startups that use our tool that understand, okay, those are the levers I need to pull to become visible.
Daniel Drabo
And I search by, for example, being active in this Reddit thread, by being active on LinkedIn and by, for example, producing a few YouTube shorts that seem to be working very well right now. Startups are actually able to beat the legacy players for certain problems or for certain topics, which obviously drives them revenue.
Which is super cool, because this is all about learning and kind of passing on information, and you've done plenty of that already.
Jane Wakefield
But is there something that somebody has said to you—piece of advice or something you've read recently, maybe on LinkedIn or a book that you'd recommend—just something that has had an impact on you and the way you go about your working day that you'd pass on to anybody listening?
Daniel Drabo
I think the most important thing that we learned—that we also learned the hard way—is that it makes sense to start hiring very, very early if you're in the venture space and if you want to make a big bet.
Daniel Drabo
Because naturally, people are kind of hesitant to start investing a lot into people they necessarily do not need right now, but you will need those people in like 8 to 12 months. And it's quite hard mentally to do that exercise of saying, hey, I need to hire those 10 or 12 people right now because I will kind of grow into them in a sense.
And, you know, realizing this and then being courageous about it and actually going for the hire because you're making that bet of being that company in 12 months.
Daniel Drabo
I think that's a very, very important piece of advice that I had to realize. And then the other thing is about decision making, I would say, because if you are moving quite fast, you will always have to make decisions based on a bad informational basis; you will often have to decide between two things where you really, really cannot clearly forecast the outcome.
Daniel Drabo
And if you stall and if you're slow about it, the outcome will just be worse than simply making a decision, going for it, and then correcting later. So moving fast actually means making decisions fast. And this is another thing I really had to realize along the way that—I'm getting a lot better at no dithering, as we'd say in England.
Jane Wakefield
So thank you so much for joining us on the Techspace Pod. It's been absolutely lovely to talk to you.
Daniel Drabo
Thank you so much for having me. It was great.
