E44 – The Future Of Content With AI Advancements with Branko Kral

E44 – The Future Of Content With AI Advancements with Branko Kral

In this episode of the Pipelineology podcast, Gary is joined by Branko Kral, a growth marketing advisor with a background that includes leading Backlinko at Semrush. Branko shares his journey through various roles in growth marketing and technical SEO, emphasizing the crucial role of firsthand experience in content creation amid rapidly improving AI and LLM models. He discusses where AI has significantly impacted efficiency—including in video editing and data analysis—and highlights the importance of maintaining transparency and moral standards in AI applications. The conversation explores practical strategies for integrating AI into workflows without sacrificing authenticity and the irreplaceable value of human judgment and relationships in business. Branko also shares insights into how he helps tech and health companies enhance their expert authority and build effective teams.

Discover:

00:00 Introduction and Guest Welcome

00:25 Branko Kral’s Background and Experience

02:34 The Future of Content with AI

04:37 The Importance of Firsthand Experience in Content

09:22 Ethics and Moral Standards in AI

15:48 Effective Uses of AI in Workflows

19:49 The Role of Humans in an AI-Driven World

28:16 Branko Kral’s Services and Contact Information

30:34 Conclusion  

 

linkedin.com/in/brankokral
branko@chosendata.com

 

Transcript:

[00:00:01] Gary Ruplinger: Hello and welcome everybody to another episode of the Pipelineology podcast. Today I am excited to be joined by a very special guest. I’ve got Branko Kral with me, ex-head of Backlinko at Semrush and current growth marketing advisor. Branko, welcome to the show.

[00:00:20] Branko Kral: Hey Gary. Thanks for having me.

[00:00:22] Gary Ruplinger: Yeah, I’m, I’m excited to, to have today’s conversation. I know, before we jump into all that stuff around AI and where it’s going and you know, what the, you know, state of content is, can you just tell a little bit, about your background for people who may not be familiar with you or some of the work you’ve done, with some of your previous organizations?

[00:00:42] Branko Kral: Yeah, sure. I’ll go chronologically back in time. Right now I’m a growth marketing advisor. I work a lot with CEOs of, for instance, marketing technology companies and health companies. Those are my main two niches. I also work with investors quite a bit. And sometimes with CMOs and marketing VPs where I come in and bring my expertise in how to grow authority of a technical brand, how to hire the teams, how to manage agencies, how to keep up the moral standards, as well as the quality standards and what systems you need around those.

I’ve also been authoring quite a lot of content, like a Content SEO Essentials course for marketing operations professionals. Before that a comprehensive long form, super long form guide to programmatic SEO, for instance. And I’ve been working with some AI content companies to help scale, set up systems, build deliverables and such.

Before that, like you mentioned, I was the head of Backlinko at Semrush. Really, I was the growth program manager, where Semrush was acquiring websites such as Backlinko and other publishers or communities such as Traffic Think Tank, and I would build an internal agency for growing them. And we had a budget and it went really well, so it turned to a pilot that inspired a few more programs like that at Semrush. Which is funny to see how that led to then helping Semrush get acquired. Proud of that. Before, before Semrush, I was in my own agency, which was called Chosen Data, and there I built it from a freelance gig into a, a company that I sold. And that was a content SEO and analytics agency.

I also have some other background in analytics, paid media, but especially analytics, because I made that into the differentiator of my agency and used it heavily, ever since.

[00:02:31] Gary Ruplinger: Gotcha. Well, thanks for, thanks for sharing that. So we’d love to kind of, kind of jump into the topic today, which is where do you think content is headed now that AI has been getting better and better, right? It seems like every week there’s a new, a new frontier model releasing and all the various tools around it are improving, and they all talk about, you know, we’ll help you write, you know, content or produce better images and all that.

So where, where do you see it going? As with all the improvements we’re seeing now with these new LlMs and AI models?

[00:03:03] Branko Kral: Yeah, good question. Thank you for that one. I think a part of my answer will be what I hope is happening, and the other part will be what I see is happening. So of course we see the increased quantity of content. And what’s good about it is that we are able to do that now. We’re able to maintain some level of quality and still scale it like crazy more, more than before, much more than before.

In the past, you would’ve to have a proper database with a system and a lot of engineering around your database to turn that into a programmatic content engine, and it was only mostly the big companies that will do that. Now you can have something that works almost like, like a programmatic approach and you can use AI and build your workflows.

That’s, that’s a huge change in how content is made. But end result, what happens especially when companies get content from AI content agencies, is that the promises are lofty and you get very low quality. And those agencies, some of which I worked with this year, have massive just depressive, depressing churn rates both on the client side and the team side, gets bad.

So what I think is the only thing that’s gonna sustain, is gonna maintain, is what I see as the only type of content that’s still worth producing. When you think about that, what is it, right? What is the content that’s worth producing now that will continue to be worth producing 10 years from now? And what has been the best content to produce for decades?

Well, it’s always the firsthand experience. As of right now, the, the AI tools we work with, the AI engines, their, their brains, they do not generate their own experience the way humans do. Of course they can learn, but it, that’s different. They don’t have the lived experience. They kinda know everything, but they have not lived anything.

So content based on firsthand experience in, in the SEO jargon has been a part of the Google algorithm and the factors in EEAT. Right, expertise, experience, authoritativeness and trust. And I feel like experience, firsthand experience coming from an expert is it. So whenever, with my clients in my work, we build systems and workflows around content production, we base it on some experts, like let’s say it’s the implementation team, the engineering team, the design team, whatever is the expertise of the company that the company is selling and making money on. We’ll take that team, the core team, use a bit of their time, a little bit of their time because you don’t need that much anymore, and we’ll build a workflow around parsing what they’ll say from their firsthand experience with methodologies, with overcoming problems, with designing solutions. We’ll turn that into content. One proof of this claim of that content based on firsthand expert experience is going to be the content to survive and the content that’ll help us all raise a level of quality and maintain it, is the, the advent or the, the massive growth we’ve been able to see on Substack and other platforms where individual authors with their own experience, and sometimes strong opinions accounts too when they’re based on experience, will be publishing in their own name on YouTube. They’ll be publishing with their own face. People, you know, humans want humans. So, YouTube’s great for that because you have the human face. Substack is great for that because you have your entire history. Like, like your brain dump structure though, and this is where I think we’re going, even if we’re publishing it on a company blog.

[00:06:42] Gary Ruplinger: Very interesting. I’ve, I’ve noticed that, you know I tell people with, with LinkedIn is it’s, I like that as another place where you can have real people. Right, there’s plenty of bots and, and AI comments too, but they’ve got verifications and to a large degree, you’re like, okay, the person I’m talking to is probably a real person. Versus nope, that was, that’s a fake bot. And you, you know, the whole, I don’t believe anything I see anymore because everything could be AI now. And I, I even regular people who aren’t in the tech industry, you know, anything like that tell me that all the time is I, I just don’t believe anything I see anymore. It’s because they feel like it’s all AI slop now.

[00:07:23] Branko Kral: Yeah, you know, I’ve, I’ve watched a documentary and then I watched an interview with the director, and it’s not important what documentary was, but in the documentary they make some very strong claims about, about something. If I said what it was, it would be distracting. So I’ll just say it that way.

And then he says, but you know, we have 45 experts who have been interviewed for this, and they’re all in the documentary. And that’s the best proof of that, these things are happening as the best proof of our claims. Because yeah, you don’t even know who is the bot and stuff, but when you have people who are putting their careers on the line, who are putting their personal reputations into the claims that they’re backing, that’s it, right? Like you have the human who’s saying I vouch for it with my name. And when you have authors with their own name and their own face publishing, that works really well. And it doesn’t have to be an individual on Substack who has a day job somewhere else, or a consultant. It can be that you have a company page and you have a sales team that never had a good enough collaboration with the marketing team. But now it’s so questionable whether a keyword data still works or how to use it that you can just, you know, if you’re a marketer, you can just go to the sales team for insights about pain points, and write about those. You can go very bottom funnel. Or if you have your implementation specialist for whatever service or solution it is that you offer, you can have the articles written in their names. So it doesn’t have to be one person again, it can be five people on your team, but it’ll be in the name of someone every time an article is published.

And to me, that’s just how it’s always worked really well. And over the years, even Google has been increasing the weights of who it is that wrote it, and now I think we’re continuing to see it working better and better.

[00:09:21] Gary Ruplinger: Great. I think that kind of is a good transition point into what are some of the, you know, things about moral standards and ethics around AI. Because you see so much stuff now where, you know, it’s supposedly a person, but clearly written by AI. You know, fake actors and everything now. So, you know, where, where do you kind of draw the line on some of this stuff? And, you know, with all the misrepresentation and overhyping of different features in, in the industry right now.

[00:09:58] Branko Kral: So again, it’ll be part what I hope and also what I see, and how it works well for those who do it. So for instance, Chris Penn, shout out, he has a YouTube channel. He publishes often enough, it’s called Almost Timely. It’s a newsletter and a YouTube channel with a video version. He has a disclaimer about how much of the content was made with AI.

So I think this is one thing, right? I I think we, we will see that being a standard element. I think ghost writing will be even easier to see through. I think publishing something in your name without you actually writing it, or your own thoughts being in it at least, like you don’t have to do all of the work, but it has to be your thoughts.

That too will be easier to see through. So being very honest and very transparent I think will pay off even more than before. Because before, if you did it, it was kind of a nice to have, if you’re transparent about what happens behind the scenes at your company or in your content program. Now it’s almost becoming a must have and is also a differentiator because companies are so slow right now about adopting that.

You know, we, we cannot rely on governments in making sure that AI is used ethically. We probably cannot really rely on the large corporations that have the biggest investments and the fastest adoption curves ever, and they’re on, on this race. It has to be us practitioners who apply the moral standards. And that’s doable, because there’s so many of us that we can actually set a standard for how it can be done before we are asked to buy a government entity in some bureaucratic way. Like, like GDPR that caused all those annoying boxes we all need to get rid of every time we visit a new website, right? It kind of works, but it’s kind of just super annoying. It’s probably more annoying than how it works. But anyway back to, back to AI transparency. I, I feel like it’s the age of transparency again, because it’s something that’s now going to be expected more, but still also allows you to stand out. And also, what happens a lot is I work a lot with agency management, budget allocations, streamlining agencies that are already hired. Because I would say eight out of 10 agencies are not worth the money they’re charging.

And then there’s some very, very good ones out there. So how do you tell which is which? Well, these days, transparency is one of the big factors. Because again, before maybe it was a nice to have. Today, you have so many agencies that work with AI content that over promise, that present themselves almost like a software company, like they’re a B2B SaaS, but really they are an agency.

And then you come into the working relationship, you expect a workflow that’s smooth because you expect a SaaS solution, but really there is an agency team and everybody’s overworked. That happens a lot with AI content production these days. So there too, to avoid massive churn rates in both agency employees, teams, and then agency clients, I think we all need to be very good about transparency and high moral standards and lead by example. I feel like people I work with or what I see when I read what somebody else wrote, people get so much relief when they see that somebody’s honest and on point about their moral standards, that they’re saying the things and then they’re doing the things.

That it actually builds trust even faster because I feel like now when, like you said, I don’t trust anything anymore, your friend doesn’t trust anything anymore. In that kind of an environment, trust has even more value. And I’ll go a little bit on a tangent, but it relates closely. And that’s like, I’m in Slovakia here now, which is where I come from.

I’m a citizen in the U.S., I’m a citizen in the European Union. I love both, but I’m, I just happen to be spending more time here now, and it’s really corrupt right now. So what you see in business is that it’s even more relationship based and trust based than before, because in an environment of low trust, trust has even more value.

So how do you get trust, right? Well, being transparent is the best way, and being consistent is another one. So that, that is my little, my little talk on, on how I see that evolving and what I think works.

[00:14:20] Gary Ruplinger: So I noticed you, in your LinkedIn posts, I think I looked at some recently, you, you do disclose that. You say, nope, I wrote this. AI was not used to write this. Do you find that that helps? Does that make it more believable?

[00:14:36] Branko Kral: My LinkedIn presence is not big enough, so I get some one-on-one feedback, but I wouldn’t be able to say whether that’s representative. I also find that sometimes when I say that, I get off track. But when it’s content that’s on a blog, on a Substack, on YouTube, then yeah, by all means, yes. Yes, I also do it in some implicit ways.

Like when I interview someone, I ask them about their own experience, their own opinions. I ask them questions that would not be that standard. When I ask someone to contribute to a technical piece of content, again, I ask them for their own methodology. I want it to be not just high information gain. I want it to be something that nobody else could write because they didn’t experience it.

Like somebody’s method in setting up measurement and attribution and how they need to change up the setup now with more AI search in the mix, right? Like that kind of stuff. I, I find that we have the disclosures, but we also have some very implicit ways where people can tell, okay, this is real. And we need to do both.

So yeah, they, they do help. My, my link, my LinkedIn is not a representative example, but yeah, it, it helps. And you, you do feel that.

[00:15:48] Gary Ruplinger: So what are some of the areas where you, you like to use AI? What do you find that for, for your, in your experiences, your, you know, n equals one, experience. Where do you find it’s most useful in your work?

[00:16:03] Branko Kral: Yeah, so time savings, definitely time savings. So not, not authorship, not the source, the core ideas that we’ll be publishing about, because I need that to be my experience. But let’s say I interview someone like you’re interviewing me now. Now, of course it’ll be much easier than a couple years ago to make clips out of this.

You can, because you can use AI, but it’s the two of us talking. And then you make the work more efficient, you make it faster. I work with Descript a lot, which gives you transcripts and then you edit the text and that edits the video. So definitely video editing, which I would, you know, before, mostly stay away from, but, but now it’s quicker.

And then in my role of, setting up teams and setting up systems, the workflows. Like when you combine AirOps with a few language models and then you build a workflow, for instance for content updates. Or I’ll give a shout out to Seer and Will Reynolds there who posted a handful of pieces of content about how they built a workflow around refreshes of existing content.

They would even have, or they still do, a voice AI agent call the subject matter expert. Which is super convenient because the subject matter expert can schedule the call to the exact time they’ll be driving to work. It’s no extra time for them and they can take it from the car. The voice AI agents have become so good and believable that it’s actually a pretty pleasant conversation.

They also are very good at coming up with questions to ask. Like whoever tried prompting AI to come up with questions and, and, collect requirements, you experience that AI is good at that. So then they, parts of the interview, they, there’s a human involved. There are updates made to existing content, and then a human does the final approval.

So that, I, I love those examples. And again, that’s based on firsthand experience, but it’s making it way more efficient for everyone. It, it’s no lop, it’s, it’s just more efficient. And then also deliverables and making them more interactive. So for instance, what I’m building right now is that putting together a lot of strategy files. You know, keyword research, competitive research. I’ve analyzed the scopes, the, the proposals of that company, it’s a video production company. And in NotebookLM, I’m making them an AI brain and in the future when there’s something new about them, like they tried new copy for an ad campaign on LinkedIn, we can put it in there or we can AI analyze the performance.

And if there is some wording that work particularly well, you could use it for their content production. And that also takes me to my last one, which I love because it became a lot better lately on both Cloud and Grok, which are my two favorite, and that’s data analysis. You know today when you put even just CSV exports, like me the other day when I didn’t have the, the access rights that I was hoping for, but I did get CSV exports of Google Ads campaigns. I put them into Cloud and Grok, and they made very good analysis for me about what worked and what we could do more of, as well as what we should do less of and change. Along with data visualizations, and they were consistent between each other. And also when I crosscheck, when I looked at the data myself, they were, they were on point and they didn’t, they didn’t miss much, and they were not wrong about much. They were probably on the level of a human analyst who could still get some things wrong. So maybe you go in and check or make some of your own conclusions, but they were so helpful and they made it so much faster for me. That end result, I was able to not just analyze Google Ads, but I used the same process for the Meta ads and the LinkedIn ads and I was just so, so quick about analyzing it all, thanks to how well it worked.

[00:19:48] Gary Ruplinger: Great. So with the organizations you’re working with, where do you find that the people still fit into the equation? Where, where are they still best suited to, to be involved and their work is, you know, still valuable?

[00:20:02] Branko Kral: Well, hopefully we all get to work less. Hopefully with AI we can actually all live by design even more. We can all design how we want to live, live where we want to live, work the hours we want to work. At least, you know, whether that’s morning or evening, like, you know, I prefer evenings, especially when I’m in Europe right now. That works out really well, when it’s quiet outside. So that’s, that’s something where I hope it all goes. But then yeah, where do humans still count? Well, of course, that firsthand experience and then like when I hired a new executive assistant for myself, now I’m not having her do the, the tasks like I did before.

Maybe 70 to 80% of what she does for me is systematizing and automating everything. Because now there’s so much more we can automate. So she’s a systems builder, you know, they still take time, right? The, the systems to set up, the automations to set up. Even just evaluating which idea for speeding something up is the best one takes time.

So I have a person do that for me. And that to me is a pretty good example. How, how much easier, how democratized it is now, the whole field of systematizing. And then I think decisions and judgment, and also everything that’s relationship based. Which, you know, humans prefer humans. Whether that’s when reading content from someone or being called by someone about a potential sale, humans prefer dealing with humans, most times.

So, everything interpersonal as well. Like, sorry. I’ll give you an example, right? Like you, you would have buyer agents and, or you have buyer agents and seller agents. Sellers adopted them first because those are B2B services. But that led to agents calling people and they got old and tiring too, too quick.

And then agents became more accessible. So now buyers can use them, like buyers can call, use agents to call up companies, but really it’s not sustainable, right? Like if, if you have bots talking to bots, I think it’s gonna be messy. And you are also just gonna put so much strain on the phone, phone bandwidth, just the network bandwidth that I don’t think it’s something that’s actually gonna work. Because a lot of these things you’re trying to figure out about where to go, what to buy, will be much easier and nicer to do if you get to talk to a human. We all have experiences with, with AI support or just talking to machines when we actually need to talk to a human and how terrible that can be, even when it’s set up well. But the impersonal character, is just, a deal breaker many times.

[00:22:52] Gary Ruplinger: Say in my, my own experience, what I’ve found is that as somebody who uses, I use AI tools and LLMs and all that stuff pretty frequently. And you interface with other companies using it. And I’ve kind of found that where, where I, I like, where I like it is when I know that it’s AI.

If it’s, as you said earlier, is if it’s disclosed to me that this is an AI assistant, great, I, I don’t mind. And you know, it, it tells me its capabilities and we can figure out, what we need to do. And if it can’t solve my problem, I can get to a human. And I’m, I’m totally fine with that type of process. It’s where I don’t know if I’m, if it’s AI. If it’s pretending to be a human, then, then I’m, then I’m not so happy about it.

[00:23:37] Branko Kral: Mm-hmm. 

[00:23:38] Gary Ruplinger: I’m like, just, just be a human or, or don’t. Just tell me. Either way is okay, just let me know. Because if I’m guessing, then I don’t trust you.

[00:23:46] Branko Kral: Mm-hmm. No, I think that’s natural, right? Like you want to have clear expectations that saves you time, it saves you energy. It’s like when you are on chat support. If you know whether that person is based in the U.S. Let’s, let’s assume you are based in the U.S. If you know whether they are as well, it gives you context. Like do they understand my cultural context from living it or do they only understand it from talking to people on chat support a lot. Like both are fine, but if you know which is which, you’ll have healthier expectations and you will not be dissatisfied so easily.

I find that it’s super important, but what about, what about you Gary? What, what else do you think about the roles and how humans, the place of humans five years from now?

[00:24:30] Gary Ruplinger: You know, it, it’s been interesting as somebody who’s, I’ve had to, I’ve grown my headcount, this year at my

company because like, it seemed like the first half of the year everybody’s saying, you know, AI is gonna replace everything you do. We do outreach and business development work. And then about June, everybody figured out that, no, that’s not the case. They, the tools aren’t there yet. You still need a human in the loop for these things. so we’ve been finding that. There is still a place for, for humans helping run the systems. Yeah. As you said, making some of these judgment decisions and still interfacing with, with people. I, you know, talk to clients.

I meet with clients. I don’t see, you know, in the next five years, I’m not seeing a scenario where. That’s just totally unnecessary and handled by AI. I don’t, I don’t think those relationships are going to be as la long, LA as long lasting. I think if we move tried to pivot to that, we, we would just see a lot of people leave for, you know, a peer software solution.

Whereas we try and, you know, market ourselves as, you know, we humans still have value to what we’re doing, so.

[00:25:37] Branko Kral: I think teaching is another one where if you think about it, if somebody is to teach something, you need to be able to relate to them. And you are a human, you’re trying to figure out your human problems and challenges, and you want to get inspired by other humans because you know they’ve had similar ones.

If there’s AI teaching you, they could pretend they’ve had challenges, but they don’t have the same one, the same ones as you. So would you actually relate to any form of AI when you’re trying to learn something more complex like career advice? Of course we all talk to Grok and Claude and ChatGPT for career advice and, and different decisions, but it’s nowhere comparable to human advice. Even when it’s smarter, even when it’s more complex, even when it’s more informed.

There’s a different weight to when a human is trying to teach you or lead you because you know, they’ve, they’ve been there, ideally, right? Ideally they’ve actually been there, but when they have, that’s not something you could just replace with a machine in, in my perception.

[00:26:42] Gary Ruplinger: I think some of it’s just, you know, that when you’re interacting with the, the LLM, there’s no, it has no skin in the game.

[00:26:49] Branko Kral: Yeah. Yeah.

[00:26:50] Gary Ruplinger: it’s, it might, you know, like, Gemini right now really, in its current iteration, I know this will be dated, you know, six months from now, but it loves to give confidence scores at the end of all its output. And it always tells me it’s got a confidence score of five out of five. And I, I’ve had to tell it I need you to stop saying that. You don’t, you, you, there’s no, there’s nothing for if you get it wrong, it doesn’t matter. So you’re just always gonna tell me you’re super confident, even though I know it’s inaccurate. I know it’s way, way, over overestimating its capabilities. Like I just need you to stop.

[00:27:25] Branko Kral: Yeah. And then if it gets it wrong and you tell it, it’ll apologize profusely. But what does it even mean? Like when a human apologizes, you appreciate it when you know that next time they’ll do it differently. And of course, you can train your model, you can set up a cloud project. There’s your history, the memory, and it’s getting better now.

But it doesn’t mean the same thing as when a human apologizes. It’s a, it’s a pretty silly thing to get from an LLM. Like what? Like you have this emotion about getting something wrong. What, what does that actually mean? It’s, it’s, it’s funny. It’s entertaining.

[00:28:00] Gary Ruplinger: No, it’s, yeah, it’s because if, if a human apologized and then did the exact same thing five minutes later, you call it a sociopath.

[00:28:08] Branko Kral: Yeah. Yeah, yeah, yeah. 

[00:28:13] Gary Ruplinger: Well, good deal. Well, this has been, this has been a good conversation. For anybody who’s kind of looking for more help in their organization with, with implementing some of these things. Can you kind of talk about what you’re able to help with and who you work with?

[00:28:25] Branko Kral: Yeah. Yeah. So I work a lot with tech companies, for instance marketing, technology, analytics, data companies. And health companies like clinics, authors E-commerce, and D2C. And what, what I do is strategy, team. So hiring and training, setting up the team. And really my recipe is in growing the expert authority on your technical area of topic where, where people need to go deep to, to learn. And then we build your authority so that you are in the trust, and really good things happen for your business.

So I said strategy, team, budget allocations between your tech stack and your team and your campaigns. And then also systems, because you need to systematize everything to run it well. I’m a, I’m a builder. I have a, I have my marketing senior background, but, but also my business senior background. So I like to work on that level of VPs or work directly with a CEO if it’s a, if it’s a small to medium sized company, and work with the leadership who has an easier time hiring someone external.

Then also a big part of what I do is super long form content, like big guides and courses. So if somebody’s company, if you’re a company listening to this, has an area of knowledge and you’ve been thinking about, hey, maybe this is worth publishing as something complex, like a big guide, course or a series.

Then, then I’m your guy too. I, I love geeking out on technical topics and conveying complex information in a structured way that’s, that’s easy to understand.

[00:30:06] Gary Ruplinger: Good. And if somebody is looking for help there, how should they get in touch with you?

[00:30:10] Branko Kral: LinkedIn is great, it would probably be best. Or branko@chosendata.com. B-R-A-N-K-O at chosen, like when you choose someone chosendata.com. But I love LinkedIn for, for new connections. Just send me a connection invite, ideal with a, with a note, and we’ll take it from there. I’ll be, I’ll be thrilled. LinkedIn has been working really well for me lately.

[00:30:33] Gary Ruplinger: Okay, well, sounds good. Well, if you need to get in touch with Branko, reach out to him on LinkedIn. We’ll make sure his profile is in the show notes, on Pipelineology.Com. if you need to look him up. But otherwise, find him on LinkedIn. Let him know that you heard about him on the Pipelineology podcast. Branko, thanks so much for coming on the show, really appreciate you having you.

[00:30:51] Branko Kral: Yeah. Thank you Gary. Thanks for organizing this. Thank you very much.

[00:30:54] Gary Ruplinger: Yeah, absolutely have. Have a great day.

[00:30:57] Branko Kral: You too. Bye-Bye.