As a professional working with legacy marine automation systems, troubleshooting outdated electronics is routine. But when I integrated AI into my workflow, it pushed me to rethink not just the tools I use but my entire approach to problem-solving. What I’ve come to realize is that solving complex problems in marine automation goes beyond just having the right technology—it requires a flexible, adaptive approach to thinking. Drawing on methods used in coaching and problem-solving techniques, I've learned that how we frame our challenges and approach solutions can be just as important as the tools we use. This mindset shift has been critical in my work with both AI and legacy systems, helping to break through technical roadblocks more effectively.

One day, while reverse engineering an aging control system on a ship, I turned to AI for help mapping out the logic. My goal was to accurately document the system for future reference, but the AI kept producing results that didn’t quite match up.

What started as a minor inconvenience soon became a bigger challenge—much like dealing with old marine automation systems. Outdated systems often hide deeper issues, and it’s easy to get stuck repeating the same steps without making real progress.

After several rounds of frustration, I paused and asked the AI: “What stops you from doing that?”

This simple question was a turning point. Although I had directed it at the AI, the question was really for myself. I realized that the problem wasn’t just with the AI—it was my own mindset. I was stuck in a loop, repeating the same actions and expecting different results.

This shift in perspective was crucial. Much like troubleshooting aging automation systems, I had to step back and ask: Where was I overlooking something? Why was I assuming this method would work?

In marine automation, especially when dealing with obsolete systems, assumptions can easily become roadblocks. These systems often have hidden dependencies or flaws that only emerge when you dig deeper. This is where reverse engineering is invaluable—breaking down a system piece by piece to uncover the root cause.

By reframing my approach with the AI, I was able to get the results I needed. This mirrored my work with legacy marine automation systems, where successful troubleshooting often boils down to challenging assumptions and asking the right questions.

Since integrating AI into my troubleshooting process, I’ve not only been able to predict system fragility and identify potential failures early, but I’ve also taken ownership of a larger initiative: leveraging AI to pass down expert problem-solving techniques to younger service engineers.

AI doesn’t just offer solutions—it replicates the thinking process of seasoned engineers, guiding younger professionals step by step through troubleshooting procedures. By embedding these strategies into AI systems, I’ve created a system where AI acts as a reliable collaborator and a virtual mentor.

Through this initiative, we are also exploring ways to enable anonymous data sharing, which respects privacy while allowing us to gather insights from real-world systems. This data, along with shared experiences and learnings from industry professionals, will help refine AI-driven solutions, ensuring that these tools continue to evolve based on real-world challenges.

For younger service engineers, AI can serve as a valuable learning companion. It can suggest proven solutions and highlight potential hidden issues, giving them the tools and knowledge to tackle complex systems without having to rely solely on trial and error. This collaborative approach, fueled by shared learnings and anonymized data, allows both seasoned and new engineers to continuously improve their troubleshooting processes.

Next time you find yourself stuck—whether with an aging automation system or a frustrating AI—step back and ask: “What’s stopping me from making progress?” Sometimes, the answer lies in changing your mindset, not just the tools at hand.

If you’re a ship technical superintendent, ship technical manager, or marine electrical/automation technician, I’m developing a set of guides, white papers, and tools that address these challenges. Join the waiting list to be the first to access these resources and to contribute to anonymous data sharing that helps improve solutions industry-wide.

By participating, you’ll have the opportunity to share your experiences and learnings with peers, shaping best practices in marine automation. Let’s work together to bring AI-driven solutions to your operations and ensure smoother, more efficient ship management for the future.

• Questioning assumptions is critical when troubleshooting legacy systems and working with AI.
• Adapting your mindset and approach can reveal hidden problems that traditional methods overlook.
• AI is a valuable tool, but it requires clear inputs, collaboration, and continuous learning.
• In both marine automation and AI problem-solving, success is driven by flexibility, shared knowledge, and openness to new ways of thinking.