AI in Content Marketing: How to Simplify Your Workflow

In this episode of the We Marketers Podcast, host Andrew interviews Matej Stajduhar, CEO and co-founder of Stryng, an AI-powered content marketing platform. They discuss how Matej’s initial interest in AI and content marketing led to the creation of Stryng, a comprehensive tool for content creation, editing, and publishing.

Matej shares insights into the development journey, the unique features of Stryng, and its application for both small businesses and enterprise marketers. He also explores the challenges and potential of AI in the content marketing landscape. Learn about the future of Stryng, the importance of networking, and practical advice for marketers starting to explore AI solutions.

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Connect with Matej Štajduhar: https://www.linkedin.com/in/matej-%C5%A1tajduhar-200b0a81/

Try Stryng for free: https://stryng.io/

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Connect with Andrew Demianenko: https://www.linkedin.com/in/andrew-demian

WeMarketers Podcast Website: wemarketerspodcast.com

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WeMarketers RSS feed: https://media.rss.com/wemarketers/feed.xml

Key takeaways

🔍 Origin of Stryng

• Stryng started as an internal tool to solve a personal problem—promoting their DevOps consultancy online without a marketing team.
• What began as a hobby quickly evolved into a full-fledged AI content marketing suite due to strong personal interest in marketing and the power of large language models.

🧠 Philosophy Behind the Product

• The team was frustrated with juggling multiple tools for small tasks and set out to build an all-in-one platform for content marketing.
• Stryng is designed not only for enterprise marketers but also for small business owners and solopreneurs who lack the time, budget, or expertise to manage complex marketing systems.

🛠️ Core Features of Stryng

• Offers article, social media, and image generation, plus a visual content calendar.
• Integrates with platforms like WordPress, Wix, Facebook, Instagram, LinkedIn, and Twitter.
• Includes features like outline editors, predefined text transformations, and content publishing—all from one interface.

💡 Differentiation from General AI Tools

Unlike generalized tools like ChatGPT, Stryng is purpose-built for marketers.

• Addresses common AI limitations: context window, repetitive sentence structures, and content fragmentation.
• Eliminates the need for section-by-section generation and editing, offering cohesive and scalable outputs.

🚀 Marketing Strategy with Limited Resources

• Stryng is used as a case study and internal marketing engine for its own promotion.
• Content is distributed via a blog and social channels, focusing on consistency and engagement.
• Recently secured seed funding to expand the team and accelerate growth.

📈 Targeting the Underserved Market

• While most competitors serve experienced marketers, Stryng is accessible to non-tech, non-marketing professionals.
• The new Campaigns feature will allow users to generate and schedule a full month’s worth of content with minimal input.

🧭 Lessons from SaaS Founding Journey

• 💡 Ideas are worthless—execution is what matters.
• 🛠️ Product alone isn’t enough—marketing and sales are critical from day one.
• 🤝 Networking is essential—opportunities often come from unexpected relationships.

🤖 The Role and Limits of AI in Marketing

• AI is a powerful tool but not a human replacement—especially at higher marketing complexity levels.
• Current large language model progress is likely plateauing unless there’s a technological paradigm shift.
• AI lacks true reasoning or innovation—it regurgitates existing knowledge patterns found online.

⚠️ SEO & AI Content

• Google’s algorithm shifts are impacting small blogs, favoring authoritative domains.
• AI-written content can still rank—Google cares about value, relevance, and user experience, not authorship.
• Over time, AI training on AI-generated data may reduce content quality unless humans continue contributing original knowledge.

🧪 Getting Started with AI in Content

• Start small: use ChatGPT or Perplexity to experiment and build foundational skills in prompt engineering.
• Learn context limitations and strengths before exploring specialized tools like Stryng.
• Understand that input clarity and structure dramatically influence output quality.

🆓 Stryng’s Free Trial Approach

• Stryng offers a generous free trial—no credit card required—with access to all features.
• Users can generate blog posts, social media content, and images without limitations during the trial.
• Unlike many competitors, Stryng believes hands-on experience is key to user conversion and trust.

Transcription

[00:01:26] Andrew: Hello and welcome back to the WeMarketers Podcast. I’m Andrew, and I’m excited to welcome Matej Stajduhar, CEO and co-founder of Stryng, a content marketing platform. In this episode, we’re going to dive into applications of AI in content marketing.

[00:01:44] Andrew: Matej, happy to have you today.

[00:01:46] Matej: Thanks a lot. Happy to be here.

[00:01:47] Andrew: Let’s start with your journey. How did you become interested in AI and content marketing, and what inspired you to co-found such a great platform as Stryng and work on AI-driven content solutions?

[00:02:03] Matej: Before doing Stryng, my partners and I were running an IT consultancy agency. We were DevOps engineers, and we were always interested in promoting our service online, but we never had the time or resources to do it. So, when ChatGPT and large language models became a thing, we immediately saw an opportunity to start building our own internal tool that would produce content to advertise our business.

[00:02:37] Matej: It started off as a hobby project, but very quickly we got really hooked on it. I got hooked on marketing specifically, and it just evolved into the full-fledged AI content marketing suite we have today.

[00:03:00] Andrew: I think it’s a common story—how a lot of SaaS products appear. Companies develop them for themselves and then go to market. Just to understand, what kind of business did you run previously before Stryng?

[00:03:19] Matej: Yeah, we had an IT consultancy agency. We were DevOps engineers.

[00:03:25] Andrew: Mm.

[00:03:25] Matej: I know that’s a niche term in the IT industry, but it’s like a crossover of system engineers, network architects, and software developers. Our job at the time was to completely automate workflows for software companies—from developing the product to releasing it, securing the infrastructure, providing scalability, fault tolerance, and so on.

[00:04:02] Matej: We worked on enterprise-grade software.

[00:04:05] Andrew: And what was the main task for you? Why did you develop Stryng? What did it help you with?

[00:04:14] Matej: It helped us get the word out there. Our business mostly operated through word of mouth and LinkedIn. I have a ton of recruiters in my network, so there were always business opportunities. We didn’t lack in that aspect. But we still wanted to build a brand.

[00:04:40] Matej: We didn’t want to be just another DevOps agency—there are tons of those out there. But since we were engineers first, with that sort of mindset, it was hard for us to handle the marketing part. So yeah, that’s how we got there.

[00:05:00] Andrew: Could you tell us a little bit more about your platform? What opportunities does it offer? I’ve already started using it and found it really useful for content creation. It’s created with a sense of understanding how content marketing and writing actually work.

[00:05:24] Matej: Yeah, in broad terms, it’s an AI-powered platform for content marketing—specifically for creating, editing, and publishing content on both blogs and social media. We cover a pretty decent scope of marketing channels.

[00:05:42] Matej: Stryng is, I would say, almost a framework for content marketers, where you decide how much AI you want to use. The AI guides you through the process, but you can also automate and put everything on autopilot.

[00:06:00] Matej: You start by providing some brand information and marketing objectives. Then, you immediately start receiving drafts for articles, social media posts, visuals like images, and a really cool content calendar.

[00:06:20] Matej: There are also a bunch of integrations. You can connect Stryng with your blogging platforms, such as WordPress or Wix, and your social media accounts—Facebook, Instagram, LinkedIn, Twitter, everything. You can basically do everything from one tool, from ideation to publishing.

[00:06:50] Andrew: With so many tools currently on the market—and we’re not even considering LLM platforms like ChatGPT or Perplexity—why should marketers pay for your product? What makes it different?

[00:07:06] Matej: Yeah, the market is oversaturated with SaaS products, especially since large language models and AI became mainstream. There’s been a huge influx of tools. You basically have a tool for every small task in your day—you can buy a tool for that specific thing.

[00:07:28] Matej: And that started to get on our nerves. As we were developing Stryng, we had to use a bunch of third-party tools to accomplish what we wanted. So we started thinking, “Okay, we need a complete suite. One platform where you can do everything.”

[00:07:47] Matej: That way, you don’t have to pay for separate tools—visual design software, content writing software, and others. That became the main motive.

[00:08:00] Matej: Once we started doing market research, we quickly understood that even smaller marketing agencies use anywhere from five to fifteen different tools to do their daily work. That’s sustainable for companies with good revenue who can afford both the manpower and the high software costs.

[00:08:26] Matej: But we started thinking about the little guy—like we were. Someone who isn’t necessarily a marketing professional and maybe doesn’t have the resources to hire someone. We wanted to build a tool from that perspective.

[00:09:09] Matej: So yeah, I think that’s our main selling point—the scope we cover and the simplicity of the platform.

[00:09:10] Andrew: And I think that’s a great point. We as marketers have a lot of tools in our pocket, but what we want is a one-button solution. I want a platform to write an article, find images, post it on social media, and publish it on our WordPress website.

[00:09:32] Andrew: That’s why this concept really resonates with me. When we try to generate content through ChatGPT, for example, there are certain limitations on the length of the article, which is a big problem.

[00:09:58] Andrew: We need to generate section by section and then piece it all together. It’s not a pleasant process, and the tone of voice can vary between sections. How did you overcome this issue, and how is it solved in your platform?

[00:10:20] Matej: Yeah. ChatGPT is a great tool—everyone uses it—but it’s a generalized tool. It does a lot of things, but it’s not specialized for marketing, especially for content marketers.

[00:10:36] Matej: The first downside of ChatGPT is the interface itself. You have a chat box, and you talk to it—go back and forth—until you get something.

[00:10:54] Matej: Stryng is a platform designed specifically for marketers. It provides a user interface for doing these types of tasks. It’s very easy to configure content-related settings.

[00:11:21] Matej: It’s very easy to edit content. You have a visual editor where you can simply select a piece of text and execute predefined transform functions. If you want to switch your text from bullet points to a table, or if you want to shorten it—it’s all available. It provides a huge speed boost when doing content compared to using ChatGPT.

[00:11:49] Matej: Another problem you mentioned is the context size. ChatGPT, even with the latest model, GPT-4, can’t generate more than 1,000 to 1,300 words in one go. So, if you want longer articles, that’s immediately a limitation—you have to generate them section by section. That’s a very tiring process.

[00:12:14] Matej: It takes too long. That’s what we had in mind when building Stryng—to give you that efficiency boost over ChatGPT.

[00:12:33] Matej: Another issue, of course, is what we call “commonisms”—that’s the term these days. ChatGPT and other large language models tend to stick to specific sentence structures, phrases, and words, which makes the content easily recognizable.

[00:12:51] Matej: And the more context you give it before generating the output, the worse the content quality tends to get. These are all problems that Stryng successfully solves.

[00:13:14] Andrew: Yeah. What I particularly love is that you can generate an outline before writing an article. Then you can adjust the outline items so you can see in advance what you’re generating. I think that’s a really powerful feature.

[00:13:34] Matej: Yes.

[00:13:35] Andrew: It works amazingly for me personally.

[00:13:39] Matej: Yeah, definitely. Everything is in an interactive visual editor. As you said, the outline editor is like a small app by itself where you can quickly rearrange headings, rename them, or add specific instructions for each heading in the outline.

[00:14:01] Matej: When you think about it, if you were using ChatGPT, you would probably never do that. You’d have to open a hundred tabs and handle each specific task in a separate conversation. Yeah—it’s tedious.

[00:14:22] Andrew: Could you unveil a little bit of your internal marketing process? How do you promote your product? As I understand, you have a small team, right?

[00:14:33] Matej: Yes.

[00:14:34] Andrew: So, with such limited resources, how are you able to promote? What channels do you use? I’m particularly interested in that.

[00:14:47] Matej: Yeah. We’re using Stryng to promote our business, and that’s the basic foundation we want to build the product on. As you know, there are tons of products out there that are basically ChatGPT wrappers with fake promises.

[00:15:06] Matej: While we’re developing Stryng, we’re also using it to promote our own business and to present that as a case study—alongside others from our customers.

[00:15:21] Matej: We also have a blog and social media accounts, and we try to publish as often as possible and find ways to generate engagement with our content. We definitely need more help at this point because we’re a very small team.

[00:15:49] Matej: But we recently got approved for our seed funding round from a regional VC fund. So hopefully, we’re going to get some more manpower into our core team soon.

[00:16:03] Andrew: Congratulations! Congratulations! I’m happy for you. I have a question for you—what personally inspires you in building a SaaS product?

[00:16:14] Matej: I don’t know. I’m not even sure. Maybe it’s silly to say, but the risk-reward, high-risk-high-reward scenario that comes with it—I guess I’m that kind of person.

[00:16:26] Matej: My partners are too. People were very shocked when they realized we were leaving our core business, which had been extremely lucrative for years. We had become a very respectable service provider in that market.

[00:16:51] Matej: And we jumped into something completely different. Up to that point, we were selling services. Now we’re building a SaaS product and trying to sell that.

[00:17:09] Matej: I guess it’s the excitement and the adrenaline rush you get when you’re doing something outside of your comfort zone.

[00:17:16] Andrew: And then you receive results and you get rewarded.

[00:17:21] Matej: Yeah, yeah. And it’s unpredictable. It’s hard. It’s difficult. It’s a big challenge.

[00:17:26] Matej: And also, you learn a bunch of different stuff. Networking too. In order to build any type of business or startup, you need to develop multiple skills. You can’t just stick to the things you’re already good at.

[00:17:38] Matej: We’re great engineers—we’re techy people—but we won’t succeed just by doing tech and programming. So we had to shift our mindset and become open to learning other things and doing them, because there’s no other way.

[00:18:11] Andrew: And what are the top three lessons you’ve learned from this journey?

[00:18:18] Matej: From building a SaaS product?

[00:18:21] Andrew: Yeah. Yeah. Yeah.

[00:18:23] Matej: Number one: Ideas are worthless.

[00:18:28] Matej: Everyone has ideas. We all think we have ultra-revolutionary ideas every day. But they’re worth nothing, and nobody is going to steal them. That’s a myth. Because there’s a huge amount of work required to make an idea into a reality.

[00:18:47] Matej: That’s the first thing. The second thing is: the product itself isn’t that important—at least not at the beginning. As engineers, we went into a cave for six months, coded non-stop, and came out thinking, “Okay, we have this amazing tool. Now everyone’s going to buy it.”

[00:19:13] Matej: That’s when I truly understood the importance of marketing and sales.

[00:19:27] Matej: Because no one will ever hear about you if you don’t promote it and reach the right people.

[00:19:32] Matej: And the third thing is networking. It’s crucial to talk to as many people as possible and open doors wherever you can. The best things that happen to you are often completely unexpected.

[00:19:45] Matej: The things you expect to happen usually don’t, and you often get pleasant surprises instead. That’s just logical: the more people in your network, the more opportunities.

[00:20:11] Andrew: Yeah, yeah, yeah. I think these are great lessons to consider. They’re applicable to almost everything we start doing.

[00:20:29] Matej: Yeah. Maybe I wasn’t specific to SaaS that much—sorry for that.

[00:20:36] Andrew: No, no—it works. It definitely applies to SaaS.

[00:20:41] Matej: Marketing is a lot harder with SaaS, I would say, than it is with selling services. In my experience, running an IT services agency and now building a SaaS product—those are two totally different worlds with different challenges.

[00:21:04] Matej: Right.

[00:21:04] Andrew: You mentioned that you are actively using your product for writing articles on your blog. I’m approaching it a bit more cautiously. For example, right now I’m testing AI-generated articles on my personal blog, wemarketerspodcast.com.

[00:21:25] Andrew: I want to see how search engines rank this content. From your experience, what do you see? Are there any risks?

[00:21:42] Matej: That’s a tough one, because Google is changing a lot. Just in the past year, its algorithm for ranking content has changed drastically. I’m not even sure who to believe anymore. I hear totally opposite answers from different people—especially SEO experts.

[00:22:11] Matej: A bunch of them say SEO is dead—that Google is doing its own thing now. From my own experience, I’ve noticed that small blogs and niche content have been dropping in rankings.

[00:22:26] Matej: And Google is now prioritizing large, reputable enterprises like Reddit and Medium at the top.

[00:22:36] Andrew: Mm-hmm.

[00:22:37] Matej: But I still see people ranking with their AI-generated content. I think Google doesn’t care if it’s written by AI—they’ve stated that multiple times. What matters is the quality and whether it provides the answers the audience is looking for.

[00:23:01] Andrew: Value. Yeah, yeah.

[00:23:03] Matej: Yeah.

[00:23:04] Matej: It’s hard to give a definitive answer on this.

[00:23:09] Andrew: Looking ahead, how do you see the future of your platform? Can you share any interesting features you’re planning to implement?

[00:23:18] Matej: We intend to keep pushing in the same direction. We want to provide an all-in-one solution for both enterprise marketers and small business owners. A content machine that can run on autopilot if needed, or a flexible framework where you can fine-tune every little detail.

[00:23:42] Matej: We aim to give users control over every step in the workflow—from ideation, drafting, and editing, to publishing.

[00:23:54] Matej: Right now, we’re focused on small business owners and solopreneurs. We’re building a feature called “Campaigns.” You provide Stryng with your brand information and marketing objective, and it drafts a month’s worth of content and schedules it.

[00:24:10] Matej: It puts everything into the content calendar. Then you go into the calendar, open each piece, view the drafts and ideas, and fine-tune them if needed. If not, just hit “Next,” and Stryng generates the full content and schedules it for publishing.

[00:24:38] Matej: I think this is a niche that’s quite untapped. Most of our competitors target enterprise marketers—people who know marketing well and can fully utilize every inch of a platform. But there are so many small businesses out there—like a local cat café or restaurant—who have never done marketing but would like to start.

[00:25:07] Matej: These businesses don’t want to pay hundreds of euros per month to someone else. So we’re building Stryng to be extremely simple and intuitive for non-tech-savvy and non-marketing professionals.

[00:25:29] Matej: The idea is to let them upload a few photos or product images, give that to Stryng, and let the platform ideate, generate, and ultimately publish content across marketing channels.

[00:26:16] Andrew: You know what I’m thinking now? It’ll be interesting to see how the role of marketers evolves in the next three, four, or five years.

[00:26:28] Andrew: What you’re describing makes it seem like marketers might become more useful for marketing platforms than for actual businesses, since business owners may be able to do everything themselves.

[00:26:48] Matej: I don’t necessarily agree. I think that’s true only up to a certain level—or maybe up to a certain revenue point. Because we’re all perfectly aware of AI’s limitations. It’s great, it’s revolutionary—I know—but it’s still not better than humans.

[00:27:09] Matej: And the question is, will it ever be better than humans? Which is a good thing—for you, for me, and for everyone. At this point in time, I see AI as a tool and nothing more.

[00:27:26] Matej: For certain niches, it does a great job out of the box. You can generate and publish content without even reviewing it. But once your marketing reaches a specific level, you need to invest effort in reviewing and controlling the content to avoid errors or false claims.

[00:27:51] Matej: With the current approach to large language model development, I think we’re nearing a plateau. It’s not going to improve much further in the next few years unless there’s a complete paradigm shift in the underlying technology.

[00:28:26] Andrew: It reminds me of the moon missions. At first, there were several successful launches, and people thought, “Okay, in 10 years we’ll colonize the universe.” But 50 years have passed, and not much has changed.

[00:28:41] Matej: That’s a good analogy. Because the way large language models work is purely based on statistics. In layman’s terms, OpenAI—or any company—basically downloads the internet and uses that as a knowledge database for training the model.

[00:29:06] Matej: When you ask a question, it doesn’t actually think the way we do. It looks for similar occurrences in its training data, finds the most common answer, and gives that to you.

[00:29:25] Matej: A perfect example of its limitation is math. If you ask what’s two plus two, it doesn’t “calculate.” It just finds that most examples of “two plus two” result in “four”—so that’s the answer.

[00:29:44] Matej: But when you start asking more complex questions, there aren’t enough patterns in the database, so the model struggles. That’s where its limits become clear.

[00:30:17] Andrew: Yeah.

[00:30:18] Matej: We’re approaching a plateau very soon.

[00:30:20] Andrew: So the systems rely on existing knowledge, but they can’t produce new knowledge. For example, if we ask them to invent something new…

[00:30:32] Matej: AI was like a sci-fi term 10 years ago. And tech people—even today—are upset because the world adopted “AI” as the umbrella term for large language models. It is a type of intelligence, I would say, but it’s not human-type intelligence.

[00:31:00] Andrew: Your point makes me feel a little bit relieved, because I’ve had concerns about marketers losing their value.

[00:31:12] Matej: Just think about this: the first iterations of these models were trained on human-written data. The internet was entirely human-written. But now, more and more AI-generated content is filling the internet.

[00:31:30] Matej: So, with each new iteration, the models are retrained on increasing amounts of AI-generated content—which includes hallucinations and inaccuracies.

[00:31:33] Matej: Every next iteration picks up more false or low-quality data. So humans still need to be the ones who bring new knowledge and ideas. That’s the only way AI can adopt that knowledge—because it’s not generalized AI that can truly learn or invent.

[00:32:15] Andrew: That’s a very interesting point. Do you see a risk that in two or three years, the quality of AI responses will actually decrease? Since they’ll be trained on AI-generated content, which includes hallucinations—won’t that become a snowball effect?

[00:32:52] Matej: Definitely a possibility. Yeah, I think it’s on the table. I’m not completely sure—I’m not that much of an expert in this area, so I don’t want to claim anything 100%.

[00:33:03] Matej: But just from a logical standpoint—if AI is learning from AI, and posting content back to the internet at the same time—there’s no innovation happening.

[00:33:16] Matej: Even if the quality doesn’t get worse, there definitely won’t be any innovation. It’ll just be regurgitating itself at that point.

[00:33:36] Andrew: We’ve already covered a lot of interesting things about AI in content marketing and the future of AI. What’s one piece of advice you’d give to marketers who are just starting to explore AI applications in their content efforts?

[00:33:59] Matej: I would say—start small. Start by using AI as an assistant. I know this goes against my product in a way, but the key skill today is prompt engineering.

[00:34:14] Matej: There are many tools out there. You can generate text, images, videos, audio—but it all starts with human input that needs to be as concise and clear as possible.

[00:34:30] Matej: You also need to learn the limitations of AI—context size, how much information you can provide before it starts forgetting. That surprises a lot of people, because these systems have extremely short-term memory.

[00:35:00] Matej: So yeah, I would say try general platforms first, like ChatGPT or Perplexity. Use them to chat, to generate ideas, to learn about things related to your business. You don’t have to Google as much anymore—almost no one does.

[00:35:30] Matej: Then, once you have a foundational understanding of how large language models work and what their limitations are, start exploring more specialized AI-powered tools or wrappers. That foundational knowledge will help you in any use case.

[00:36:00] Andrew: Matej, for new users who register on your platform, Stryng, do you offer any free credits so they can try it out?

[00:36:12] Matej: Of course. There’s a free trial on our platform—no credit card required. I’d say it’s a very decent trial. If you’re a really small business, you can probably get a month’s worth of content from Stryng during the trial—multiple articles, a bunch of social media posts, images. Everything’s unlocked. There are no limitations.

[00:36:56] Andrew: That’s a great approach. What I’ve seen with many content marketing platforms is they don’t offer a free trial. So, as a marketer, I don’t even get the chance to try the product before paying.

[00:37:13] Andrew: And that just feels really weird to me.

[00:37:16] Matej: Yeah, it doesn’t work that way for us. I understand where platforms like that are coming from, though. There are a lot of costs involved in running a platform like this. First of all, we pay for LLM usage—like to OpenAI, for example.

[00:37:40] Matej: So free trials are expensive at scale. If hundreds or thousands of users try your product and you’re investing 50 cents or a dollar per user, you better expect a lot of conversions—or you’ll go bankrupt.

[00:38:06] Matej: So I think many startups are afraid to take that risk. But yeah—

[00:38:12] Andrew: Yeah.

[00:38:13] Matej: —we’re prepared for it, so we don’t mind.

[00:38:15] Andrew: That’s great. Matej, thanks a lot for the insightful conversation. What’s the best way for our listeners to connect with you?

[00:38:24] Matej: Whatever works—LinkedIn, social media—we’re everywhere. I’m everywhere.

[00:38:33] Matej: But yeah, LinkedIn is my preferred platform for doing business.

[00:38:42] Andrew: Okay.

[00:38:42] Matej: And visit our website—everything’s there.

[00:38:46] Andrew: Great, great. Thanks a lot for joining me today, and have a great day.

[00:38:53] Matej: You too, Andrew. Thanks a lot for having me. See you.