Problem Solving
Repairing, fixing, and problem solving is probably one of my strongest traits. I studied it in school, and I’ve built up experience—and a lot of fun stories—over the years. I’ve always enjoyed the challenge of figuring out how things work—and more importantly, why they don’t. Whether it’s a broken wire or a broken workflow, I enjoy digging in and making it work again.
Foundation
My approach to problem solving is built on a strong foundation in electronics. That’s where I first learned to isolate issues, trace signals, and find faults using logic and observation. Over time, I’ve carried those skills into working with code, systems, and machines. I usually start by looking for clarity—understanding how a normal state should work. Once I see that, it’s easier to spot what’s broken.
Electronics
This is where it started for me. Debugging electronics taught me to be patient, methodical, and observant. I’ve learned to look for small signs: a voltage drop, a pattern glitch, or a warm component. I don't just test for failure—I try to understand the conditions around it.
Here’s my typical workflow when approaching an electronic issue:
- Visual inspection
- Feel for heat
- Smell (burnt or chemical smells can say a lot)
- Check obvious voltages and grounds (GND should always be 0 V—if it’s floating, it won’t show correctly)
- I primarily test using voltage. From that, I can calculate current and find shorts or broken connections.
Favorite Test Tools
- Scope - for seeing what the system won't tell you
- Freeze spray - for catching thermal issues
- Short wire - to bypass or bridge suspected faults
- Square wave test - for tracing signals across boards
- Isopropanol or rosin atomizer - to detect hot spots or weak joints
Code / Systems
When it comes to code or system-level problems, I apply the same mindset: isolate, test, observe. I avoid assumptions, and I like to start by asking: What should this actually do? Then I compare that to what’s happening. Whether I’m debugging firmware or troubleshooting automation scripts, I treat it like signal tracing—just in a different language.
Machines
Machines are a different kind of system, but the thinking is the same. I listen for changes in sound, check physical wear, and look for patterns in failure. I treat mechanical troubleshooting as a conversation—the machine is giving signals, you just have to pay attention.
General
No matter the problem, I try to avoid jumping to conclusions. I prefer to slow down, observe carefully, and start with what I know. I often sketch out the system or talk it through out loud—anything to get it out of my head and into something I can interact with.
I don’t aim for elegant solutions right away. I aim for understanding. Once I have that, the fix usually follows.
I also believe in testing early. If I have a hunch, I try to prove or disprove it with minimal effort before diving deeper. It saves time, avoids guesswork, and usually leads me somewhere useful—even if it’s not where I expected.
Fixing
After identifying the problem, I work on a fix and decide whether it’s acceptable long-term—depending on how critical the system is. Sometimes a temporary solution is fine as long as it buys time until the proper spare part can be sourced.
One memorable on-the-spot fix: five minutes before going live, the broadcast mast wouldn’t raise. I quickly identified a faulty relay, grabbed a screwdriver, shorted it—and we went live on time.