King Who Lives Everything (2023): Interview on One of the Earliest AI Self-Translation Projects

Robert, many fairy tales entertain readers, but this book seems to come from a much deeper place. What inspired you to write King Who Lives Everything, and what message were you hoping to share with readers?

I wrote King Who Lives Everything because it is, in many ways, a reflection of my own journey.

For many years, I worked as a business consultant and had the opportunity to meet highly successful people—business owners, executives, and entrepreneurs who had achieved wealth, status, and recognition. From the outside, they seemed to have everything. But in many cases, I noticed something surprising: despite their success, they felt an emptiness inside. They were asking themselves questions that money could not answer.

At the same time, I was facing similar questions in my own life. What is the meaning of my life? Am I living the life I truly want to live? And do I have the courage to make radical changes when I know something needs to change?

I wanted to share these experiences, but not through a traditional business or self-help book. Instead, I chose to tell the story as a fairy tale. The book combines lessons from my life, my work, and the people I have met along the way.

Writing this book was not only about helping readers. It also helped me. The process gave me the courage to make important changes in my own life and to follow a path that felt more authentic and meaningful.

At its heart, the book is an invitation for readers to ask themselves a simple but powerful question: What does a meaningful life mean to me? Who I am?

One interesting aspect of King Who Lives Everything is its English translation. As a first-time author, why did you decide to become so personally involved in the translation process instead of simply handing it over to a professional translator?

Because this was my first book, I wanted it to be as good as possible.

At first, I looked for professional translators, but I had a concern. A translation can be grammatically correct and still lose the feeling, meaning, and spirit of the original story. Since the book is very personal, I was afraid that a low-quality translation would weaken the message I wanted to share.

I had a similar experience with the book cover. Even when professionals are involved, the final result is not always what you imagine. That taught me an important lesson: if you want the highest quality, sometimes you need to take personal responsibility for the outcome.

My English is good enough to read and understand almost any text, but writing a book is completely different from writing emails or having conversations. Creating natural, engaging literary text is much more demanding.

At that time, I became curious about the possibilities of artificial intelligence, especially ChatGPT. I saw an opportunity to combine my understanding of the original text with AI's language capabilities. What started as an experiment gradually became a serious translation project.

I was also fascinated by the bigger picture. We are living through a technological shift that is changing how books, ideas, and knowledge move between languages and cultures. In a small way, I wanted not only to be part of the AI translation revolution, but also to explore the broader AI revolution and see what was possible.

In the end, the translation became much more than a technical task. It was another creative journey, and it allowed me to stay closely connected to every sentence and every idea in the book.

You mentioned that one of your concerns was losing the deeper meaning of the story in translation. Can you give us a specific example where a technically correct translation wasn't enough?

Let me give you a simple example.

The original Slovak title is Kráľ, ktorý všetkého má. A direct translation would be something like "The King Who Has Everything" or "The King Who Has It All." Both are grammatically correct. A professional translator could easily produce that translation.

The problem is that neither title captures the deeper meaning of the story.

The book is not really about possession. It is about experience. The king is searching, learning, suffering, growing, and ultimately living through all aspects of life. That is why I eventually chose the title "King Who Lives Everything."

Finding those three words took me almost two weeks. It was not a translation exercise anymore—it was a creative process. I was searching for a title that would communicate the soul of the story, not just the literal meaning of the original words.

I had a similar experience with the book cover. One professional design featured a golden royal crown. It looked polished and professional, but it also felt generic. If you walk into a bookstore, you can find hundreds of books with crowns on the cover.

The final cover uses a golden spiral instead. For me, that symbol is much more meaningful because it represents growth, life's journey, and the patterns we find throughout nature and human experience. It is more connected to the message of the book.

Of course, there is nothing wrong with professional translators or designers. Their work is valuable. But this experience taught me that sometimes the difference between a good result and a truly authentic result lies in understanding the deeper intention behind every word and every design choice.

That's fascinating. So would it be fair to say that you weren't really translating words—you were translating meaning? And do you think AI helped you preserve that meaning better than a traditional translation process would have been possible?

Yes, I think that's exactly right. I wasn't translating words—I was translating meaning.

That also leads me to a deeper question I often reflect on: what is art?

Can AI generate images? Of course it can. It can produce visually impressive results in seconds. But whether something becomes art depends on more than technical execution. It depends on intention, experience, and meaning behind it.

For me, art begins with a human being trying to express something that cannot be reduced to instructions or rules. Tools can assist, but they do not replace the inner source of that expression.

That is also true in my book. AI could suggest many possible translations of the title or text, but choosing "King Who Lives Everything" required understanding the essence of the story, not just its language. It came from lived experience and reflection, not from algorithms.

The same applies to the cover. Many designs can look visually correct or professional, but deciding that a golden spiral represents the journey of life better than a traditional crown was a human interpretation, not a technical one.

In that sense, I see AI not as a creator of meaning, but as a tool that can help carry meaning across language and form.

At the end of the book, there is a passage that reflects this perspective:

"What wisdom would you like to pass on to your successors?"

"I'd may sum it up in a few sentences:
You get what you create.
Everything is always perfect.
Life isn't in a hurry,
and yet it accomplishes everything.
I am everything I perceive.
The World is my Exact Mirror.
Humility is perception."

For me, these lines are not just a conclusion of the story—they are a reminder that perception, creation, and meaning are deeply connected. No tool, including AI, replaces that inner responsibility of how we perceive and shape our world.

AI can help express ideas. But the responsibility for meaning remains human.

When you were working on King Who Lives Everything, there was a lot of excitement around AI-assisted writing and translation. From your perspective, how would you describe that "AI translation race" and what was actually happening at the time?

From my perspective, there really was a short but intense "AI translation race," especially around 2023.

At that time, many people were experimenting with AI translation and AI-assisted writing. There was a lot of curiosity about who could be considered an early pioneer in this space, especially for book-length, high-quality work.

My book was part of that early wave. I would describe it as one of the first high-quality AI-assisted translations at a full book level, where the author was directly involved in shaping both meaning and language.

Interestingly, during that period, many translators were hesitant to openly acknowledge the use of AI in their work, partly due to concerns about reputation or income. In contrast, I chose to be fully transparent about it. In fact, ChatGPT 3.5 is officially listed as a translation assistant in King Who Lives Everything, because I wanted to clearly document the role of AI in the process.

But the interesting thing is how quickly the attention shifted.

By around mid-2024, the initial hype started to fade. The idea of "first AI-generated books" stopped being newsworthy in the same way. In fact, at that point, the first fully AI-assisted books by other authors had already appeared, and the media narrative moved on.

That led to an important realization for me: having a strong product is not enough on its own. Visibility matters just as much. If people don't know about your work, it effectively doesn't exist in the public space.

I experienced this very directly. You can send dozens or even hundreds of messages to media, journalists, or platforms, and still receive only a few replies. And over time, you start to realize that this is not just about effort—it is about relationships, personal connections, and access to the right people.

That was a difficult but important lesson. In many ways, media and distribution are not purely merit-based systems. They are networks.

So I started to understand that book creation is not only a creative process. It is also a form of brand building and positioning.

And by the time the initial AI hype cycle slowed down, I realized something else: media interest in "first AI-generated books" was already disappearing. The moment had been short. The race itself probably lasted only about three years.

After that, the technology stayed—but the attention moved on.

You've spoken about the importance of visibility around King Who Lives Everything. What did you learn from your early attempts at marketing and media outreach? Were there any failures or surprises along the way?

One of the most important lessons I learned is that a good product on its own is not enough.

You can create something meaningful, well-designed, and high-quality—but if it doesn't reach people, it simply doesn't exist in the public space.

In the beginning, I approached media outreach quite directly. I contacted magazines, editors, and platforms, sometimes sending dozens or even over a hundred messages. The response rate was very low—maybe a handful of replies, often polite rejections, and many messages with no response at all.

At first, that was difficult to understand. You start asking yourself: what am I doing wrong?

Over time, I realized it is not just about the message or the product. Media works through relationships, timing, and trust. Personal connections often matter more than cold outreach.

That was a hard but valuable lesson.

In many cases, visibility does not come automatically, even when the work itself is strong. Without some form of distribution strategy—whether through partnerships, networks, or professional promotion—many projects simply remain invisible.

In that sense, book creation is rarely just a traditional "business" model. It is closer to long-term brand building, where impact depends not only on quality, but also on how effectively the work is introduced into the world.

So I began to see publishing in a different way. Writing the book is only one part of the process. The other part is making sure it actually reaches people.

At some point, King Who Lives Everything evolved beyond just a literary work and became an AI Translation Case Study. How did that transition happen, and why was it important?

Yes, in this case it was planned from the beginning that the project would not only be a finished book, but also a fully transparent AI translation case study.

Most AI translation examples you see today are either private, simplified demonstrations, or hidden inside commercial systems. What makes this project different is that it openly documents the entire process from start to finish.

It preserves all three layers of the text: the original Slovak manuscript, the raw AI-generated English translation, and the final human-edited version. Alongside that, it includes commentary on decisions, corrections, and translation errors.

This structure makes it possible to see not only the result, but also the transformation of meaning during the process.

It is especially valuable because Slovak is a low-resource and morphologically complex language. When translating into English, AI systems often struggle with idiomatic expressions, stylistic consistency, and subtle shifts in meaning. The case study makes these limitations visible in a real literary context, not just a technical test environment.

Another important aspect is the workflow itself. The translation was not a single pass. The text was divided into sections, multiple AI outputs were generated, and results were iteratively refined. This showed clearly that translation quality depends not only on the model, but on how the process is designed.

In that sense, it becomes a practical demonstration of how human-AI collaboration actually works. AI handled a large part of the initial translation, while human editing was necessary for tone, nuance, and narrative coherence.

The project was already 90% complete in 2023, including all original input and export texts preserved and asigned ISBN. In 2025 I had to complete and publish an expert-level and scientific book. That shifted priorities.

I returned to complete King Who Lives Everything specifically as an AI Translation Case Study, because it had already become more than a literary project—it became documentation of a real technological shift.

Its importance lies in that combination: it is both a creative work and a reproducible experiment. In theory, the entire process can be replicated and studied.

In that sense, it also functions as an informal dataset for analyzing translation behavior—especially error patterns, stylistic drift, and consistency issues in narrative AI output.

What makes it particularly unique is that it applies this analysis to philosophical, metaphorical fiction rather than technical text. And that is exactly where AI translation is most challenged.

Finally, I chose to publish it under the Creative Commons CC-BY 4.0 license so that the entire work—text, translations, and structure—could remain openly accessible and usable for further study and reuse.

Why did you decide to publish all your work under Creative Commons CC-BY 4.0 instead of traditional publishing models?

I chose Creative Commons CC-BY 4.0 because I wanted the book to be more than just something you buy and read once. I wanted it to be something people can use.

The book is quite short, so it doesn't really fit the usual book market in a traditional way. It is closer to a philosophical story, similar in spirit to The Little Prince by Antoine de Saint-Exupéry—simple, symbolic, and meant to make people think.

At the same time, it didn't have a strong commercial brand behind it, so instead of forcing it into a sales model, I decided to change its purpose.

I started to see it less as a product and more as a resource that others can build on.

Another reason was that there are not many modern philosophical fiction works that are open, reusable, and easy to share.

So I made it available in different formats—PDF, HTML, EPUB, and also Markdown (.md)—so it can be used not only for reading, but also for teaching, research, or digital use.

It is also available in two languages, which makes it easier to use in different contexts.

I also included the AI Translation Case Study under the same license, so people can see not only the final book, but also how it was created.

Because of this, the book is often used more in schools, universities, and learning environments than in traditional bookshops. It works better as something to study and discuss than something to simply sell.

What kind of impact do you see King Who Lives Everything having today?

The book is quite short and easy to read—it usually takes around 15 minutes—but that is also part of its design. It is not meant to take a lot of time. It is meant to leave something behind after you finish it.

Even though it is short, it often doesn't end when the reading ends. Many readers come back to it later because of the questions it raises and the emotional space it creates. It works more like a reflection than a traditional story.

It is also one of a small number of openly licensed philosophical fiction works that combine storytelling with deeper questions about life, meaning, and personal change. That openness is important, because it allows the book to move beyond a closed publishing model.

In practice, it has found different kinds of use. It appears in online courses, in educational discussions, and sometimes as a shared text where people reflect on meaning together rather than just reading it individually.

At the same time, it is also used in AI-related experiments. For example, people use it to test how language models interpret narrative, translate meaning, or reason through symbolic and emotional text.

So its impact is not limited to literature alone. It exists at the intersection of education, experimentation, and reflection. It is a small work, but it travels in different directions at the same time.

You also mentioned something called "King Who Lives Tests." What does that mean in practice?

"King Who Lives Tests" is a way of using the book beyond traditional reading.

One of the simplest forms is imagination-based interaction. You can take the perspective of the king from the story and have a conversation with him. This is used to test how well emotions, personality, and consistency can be recreated—especially in AI models. The focus is not only on correctness, but on how believable the inner world of the character feels.

The book can also be analyzed from multiple angles. It can be studied structurally, emotionally, or philosophically, depending on what someone is trying to explore. Each approach reveals something slightly different.

Another use is translation testing. The text can be translated into different languages and then translated back again, which shows how meaning shifts during the process. This helps reveal where interpretation changes, not just language.

It can also be reformatted and reused in different contexts—such as teaching materials, workshop exercises, or discussion prompts. In that sense, it becomes adaptable content rather than a fixed form.

And beyond that, it can serve as a base for creative experimentation—like generating illustrations, testing alternative book covers, or exploring different visual interpretations of the story.

So in practice, the book becomes a flexible environment for testing language, meaning, and interpretation. It is not only something to read, but something to work with.

If you look at everything together—writing, AI translation, experimentation, and open publishing—what is the real legacy of King Who Lives Everything?

For me, the legacy of King Who Lives Everything is not about size or commercial success. It is about what it contributes to a very early phase of how humans and AI started to work together in creative writing and translation.

At its core, the book is a simple question: Am I really living my life, or only going through it? It uses a fairy-tale form to explore meaning, change, and personal transformation.

But beyond the story itself, it became part of one of the early practical experiments in AI-assisted self-translation. The project started in 2023, at a time when this type of workflow was still very new. In that sense, it belongs to the early wave of AI-self-translation pioneer works—where authors were not only writing with AI, but also directly involved in translating their own work with AI support under human supervision.

What makes it important is not only the final result, but the documentation of the process: how meaning shifts, how AI handles narrative language, and where human interpretation remains essential. This is why the book is often referenced today not only as literature, but also as a practical example of how AI translation behaves in real creative work.

Over time, it has found its way into different uses. It is read in educational contexts, discussed in learning environments, and also used as a reference point in AI-related experimentation. In that sense, it is not a closed work—it continues to be interpreted and reused in different systems and contexts.

Because it is openly licensed under CC-BY 4.0, it can circulate freely, be adapted, and built upon. That decision was important, because it allowed the work to become part of a broader ecosystem rather than remaining a fixed product.

Looking at it globally, I would describe its role as part of the early documentation of AI-assisted authorship and self-translation. It stands as one of the early real-world examples of AI translation pioneer practice, showing how an author can remain inside the translation process while using AI as a collaborative tool.

In that sense, it does not only describe a story—it reflects a moment when AI started to change how books are created, translated, and shared. It is part of that shift, and it continues to be used as a reference point in understanding it.

If I had to summarize its legacy in one sentence, I would say this: it is a small book that captures a transition in how stories are made—and leaves that transition open for others to continue.