Podcast with Jakub Haláček: Artificial Intelligence, Agent Systems & the Future of Education
In this episode, we talk with Jakub Haláček, head of the Unicorn AI Center, who spent ten years teaching physics and mathematics before transitioning into AI research and its real-world application in business.
Jakub shares his insights on the current pace of AI development, its potential and risks, and introduces specific use cases developed at Unicorn – from agent systems to automated document processing.
What is this episode about?
✔ What the Unicorn AI Research Center focuses on
✔ What to expect from the course “Foundations of AI in Practice”
✔ Why now is the right time to dive into AI
✔ How AI could transform the way our children learn
Today’s guest on the podcast is Jakub Haláček – a graduate in theoretical physics who spent ten years in education, teaching physics and mathematics, while also leading a student robotics team. He now works at Unicorn Systems and has transitioned into the world of business. Jakub, welcome to our podcast!
Hi, thanks for having me.
Today, you lead the Unicorn AI Center and focus on research in the field of artificial intelligence. How did you get into AI, and what fascinates you most about it? When did you first realize the true potential of this technology?
That’s a great question to start with. I can’t say there was one specific moment, but I definitely remember that “wow effect” when ChatGPT came out. It was the first application that could communicate naturally and actually seemed to “know” something. I remember thinking: “This is really interesting.”
But it took about a year before I started engaging with the technology more deeply. Around the middle of last year, I was already working with AI—mainly language models and generative technologies—on a daily basis.
I began to dive deeper, watching lecture series from American universities, and it suddenly hit me that this isn’t just a chat tool. It can be a practical assistant that simplifies many daily tasks. Then I discovered an even stronger idea—that AI can function as an independent “brain” that integrates into processes, communicates with other tools, and actually gets things done for me.
That was the moment I realized: “This technology has enormous potential. And it will most likely profoundly change the world.”
That’s really interesting. How do you perceive the current development of artificial intelligence? And where do you see its biggest opportunities and threats?
I think the current pace of development is absolutely incredible. I don’t think I’ve ever experienced a situation where it’s necessary to follow updates not weekly, but practically on a daily basis. The major players in the industry are releasing something new every week, and just keeping up with the evolution of the core technologies is a huge challenge in itself.
On top of that, there’s another layer – watching how people are actually using these tools in practice. That’s why you need to be connected to various communities and channels that share new applications and use cases. The speed of it all is truly extreme.
In terms of opportunities – and I’m mostly thinking about the Czech and European markets – I see it as essential that companies finally start building products on top of these technologies. We have great tools available, people are somewhat familiar with them, but many businesses still don’t know how to apply them practically. They’re still relying on solutions that have been around for years – and meanwhile, the world is moving on.
I see huge potential in so-called agent systems – orchestrated systems in which multiple language models or tools communicate with each other. These systems can make decisions, choose the best approach, even call on other agents for support, and ultimately solve a task from beginning to end. Essentially, you can create a digital employee who is capable of fully handling, for example, a customer query – not just by chatting, but by actually interacting with systems. I think this is where the real future of AI in business lies – far beyond just “write me a nice article.”
As for threats, there are quite a few. Personally, I think about the world my son will grow up in. What skills will he need? What jobs will be meaningful for him? What will education look like?
And then there are some very concrete threats – generative tools that work with images, video, and voice are becoming increasingly accessible. Today, it’s no longer difficult to create a deepfake – a “digital clone” of someone who speaks in your voice, looks like you, and behaves like you. This used to be something only top experts could do – now, practically anyone with a smartphone can do it.
And if these things start spreading massively online, on social media, in schools… it could significantly undermine trust in public content. Maybe we’ll get used to it over time and stop believing anything unless it’s verified. And maybe we’ll start using it as an excuse ourselves: “That wasn’t me, that was AI.”
That honestly scares me – how easily manipulation could become everyday reality.
Do you have a favorite AI technology or tool that you use most often?
We’d probably need a whole separate podcast to cover that—it could easily take an hour or more. Most often, I work with ChatGPT, because it’s an “all-in-one” tool. It can do a lot of things I’d otherwise have to search for elsewhere, and I’ve been using it for a while now, so I know how it behaves and have it tailored to my needs.
I combine it with tools like Cursor, which is a great assistant for coding and prototyping. It can be directed with custom prompts, and the outputs are very effective. We also use models from Anthropic quite a bit, especially for generating code—they’re excellent in that regard.
There are also many smaller applications that help with things like photo enhancement or other small tasks. One technology I find particularly interesting is MCP server, which allows systems to be interconnected in a way where I can assign a task (like sorting old photos), let it run autonomously, and come back later with the task completed.
Another great tool is SuperWhisper Pro. I speak into the computer, and based on the context I’m in, it adapts the output accordingly. For example, if I’m working on code, it can translate my spoken language into technical terminology—like it’s being written by a developer.
Can you introduce us to the Unicorn AI Research Center and its main focus?
Simply put, our role is to observe AI technologies and look for practical applications. There’s a lot of focus today on language models, but we also work with classic machine learning—writing neural networks, training them on data, and similar tasks. We don’t do primary research ourselves; instead, we adapt existing technologies to solve problems we can then transfer into business use.
We work closely with Unicorn Systems and Unicorn Solutions. We collect their requirements and develop prototypes and proof-of-concept solutions that can be implemented in real-world scenarios.
Over the past three quarters, we’ve focused on two main areas:
AI for software development – While building websites is largely automated now, building robust systems requires advanced frameworks. We’re exploring ways to extract and transform this know-how into tools that help architects and developers accelerate and streamline their work.
Working with documentation – Being able to handle technical drawings, manuals, or contracts: understanding them, storing them efficiently, and making them searchable. For example, finding a technical object in documentation or inventory based on a description.
How do you see the future of the Unicorn AI Research Center in the context of AI development?
We don’t have ambitions in the area of primary development of language models—that type of research is extremely demanding in terms of hardware, expertise, and budget. We leave that to academic institutions, including Unicorn University, which specializes in this area and collaborates with other research partners.
We focus more on “fine-tuning”—for example, retraining models on specific datasets (like 10,000 question–answer pairs) to improve their understanding of context or domain-specific content. Training models from scratch is outside our scope.
The general public can enroll in the course "Foundations of AI in Practice." What can people expect from it?
The title "foundations" might be misleading—for someone working with AI every day, yes, it covers the basics. But according to feedback, the course is much more comprehensive than many expected.
The goal is not just to teach people a few tools, but to help them grasp the full range of possibilities, understand how to think about AI, where to apply it, and what its limitations are. We showcase demo applications, hands-on techniques for building simple AI tools (e.g., for children), and ways these tools can solve problems that, just a year ago, would have required a developer.
The course also includes practical guidance on how to integrate AI into a business—where to start, what questions to ask, when it makes sense and when it doesn’t. And of course, we address security and ethical concerns, including the upcoming EU AI Act regulations.
In my opinion, it’s a highly practical and valuable course—not just a glimpse, but a solid foundation on which you can build further.
You mentioned the course is suitable even for complete beginners—does it require any specific skills?
The most important things are a willingness to learn and the ability to stay focused for 4 to 8 hours, which can be tough when tackling a new and complex topic. It’s also important to not be afraid to ask questions, since I might sometimes assume something is common knowledge when it isn’t for everyone.
In terms of technical skills, nothing specialized is required. We walk through everything from the basics, but we do assume participants have basic experience with using a computer and the internet. If not, the course may be more challenging—but still manageable. For those with more experience, there will be moments where they can “switch off” briefly before diving into the next topic.
Can you share some interesting examples or areas where AI is being used?
One area I really enjoy is interactive work with data and systems. Usually, we have predefined views of data—charts, tables, dashboards. But what if the user could adjust those views to their own preferences? Want a bar chart? Sure. Prefer a pie chart? Something else? AI can help adapt the view in real time based on what the user wants to see.
Agent-based systems are also extremely powerful. I can submit a request and watch how agents collaborate, make decisions, and deliver a result. For instance, I once wanted to create a simple app, sketched out what I wanted, and within a few minutes, I had a working prototype. For people who have ideas but don’t know how to code, this represents a huge step toward democratizing technology.
It’s amazing to see your enthusiasm.
I don’t sleep, I don’t eat—on weekends I’m constantly thinking about what’s next. I haven’t felt this kind of “hype” in years.
What would you recommend to people who want to start learning about AI?
I definitely recommend our course, where you quickly get a big-picture view. It’s not just about writing prompts, but about understanding the full range of possibilities. It’s also crucial to stay on top of trends and not wait to “see what wins.” The pace is so fast that if you wait, you might find that your job is no longer competitive.
I recommend finding reliable sources of information, talking with others about it, and being active. This is IT on steroids.
How do you see the future of AI in education? Is it a new field of study?
Absolutely. There will be a whole new generation of professions that will need to master the orchestration of AI systems. I hope people will still be the ones doing that work.
In education, AI is already being used. My son comes home from school, struggles with something, and I take a picture of it. AI processes it, explains it, prepares a quiz or a game, and checks whether he understands. This is real. In fact, we have a bachelor thesis with one of my students focused on creating an AI assistant that helps kids with homework, and gives parents confidence that their child actually understands the material. Such technology could greatly benefit education.
Jakub, thank you for the conversation.
My pleasure.
Editor’s note: Transcript edited with the help of AI.
Links and resources
- ChatGPT (OpenAI) – most-used tool, an “all-in-one” solution for working with language models.
- Cursor – AI-first development environment for coding and prototyping.
- Anthropic – Claude – Alternative to ChatGPT, well-suited for technical use and code generation.
- Whisper (OpenAI) – Speech-to-text tool (including advanced versions like SuperWhisper).
- Product Hunt – Track new AI startups and tools (Jakub browses this monthly).
- Foundations of AI in Practice – Unicorn University course – the course Jakub refers to.
- DeepLearning.AI – Excellent resource for learning AI and ML fundamentals.
- Google AI Hub – Tools, research, and open-source projects from Google AI.
- EU AI Act (EU AI Regulation) – Overview of the regulation Jakub mentions.
- AI Alignment – OpenAI Blog – Articles on the ethical challenges of developing safe AI.
- Future of Life Institute – Non-profit focused on global risks from advanced technologies including AI.
- The AI Podcast (NVIDIA) – Covers real-world AI applications across industries.
- Latent Space Podcast – More technical conversations around emerging AI tools.
- r/MachineLearning on Reddit – Active community for AI professionals and learners.
