Experience artificial intelligence: Insights from the AI Hackathon
On October 7, the second AI Hackathon took place in Braunschweig—a day full of creative energy, practical experiments, and inspiring teamwork. The focus was on a question that is currently on many people’s minds: How can we meaningfully integrate artificial intelligence into our everyday work—and where are its limits?
Ideas were pitched, teams formed, and exciting projects launched early in the morning – from automatic SQL generation to a support chatbot for PDF summaries to the Professional Icon Generator (PIG). Participants used technologies such as OpenAI, Spring AI, and LangChain4j to develop real-world use cases.
The 6 Lessons Learned from the AI Hackathon
1. AI is only as good as its Context
Whether text-to-speech, image generation, or data retrieval: without human guidance, AI remains disoriented. One team experienced this impressively when the model drew a table (desk) instead of a chart—literally. A smile, but also a valuable moment of insight: intelligence needs guidance.
2. Practice beats Theory
Reading, discussing, planning—all of these things help. But nothing can replace the moment when you sit down and write the code yourself. The hackathon showed how important hands-on experience is for truly understanding the potential and limitations of technology.
3. Collaboration is Key
Innovation arises where knowledge is shared and ideas are combined. In mixed teams of developers, designers, and analysts, functional prototypes were created in just a few hours.
4. Mistakes are Part of the Learning Process
AI can be fascinating—and frustrating. It rejects prompts, counts incorrectly, and interprets terms strangely. But that is precisely where the learning value lies. Every failure opens a new window of understanding: What can AI do—and what can’t it do (yet)?
5. Security through Understanding
At the end of the day, the mood was clear: our jobs are safe—as long as we understand how AI works. The hackathon confirmed that AI is not a replacement, but a tool. One that can make our work more efficient, creative, and exciting—if we use it consciously.
6. Context & Meaning: Learning through Experience
The debate surrounding artificial intelligence fluctuates between fascination and concern. But at BREDEX, we take a different approach: understanding through doing.
The hackathon was not just an event—it was a space for experimenting with future skills.
Conclusion
The AI Hackathon proved once again that learning at BREDEX is teamwork.
It was a day spent not only writing code, but also thinking about the future together.
And perhaps the most important lesson learned was not a technical one, but a human one: innovation begins when we have the courage to try new things.
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