Context: A Practical Project
Over the past days, I have been developing a Python Qt application to generate weekly meal plans for my baby and family.
The project itself is not overly complex, but it has provided a valuable opportunity to reflect on something broader: the role of
artificial intelligence in our everyday engineering workflow.
My Approach to AI Assistance
My background is in C programming, with solid experience in embedded systems and software development. When shifting
into Python, however, I still consider myself at a more basic level. This mix has shaped how I approach learning: I rely on my
technical foundation, but I also use AI as a complementary resource.
The process is intentional. I first explore documentation and form my own reasoning. If questions remain, I consult ChatGPT to
clarify an approach or compare perspectives. In this sense, AI becomes more of a sparring partner than a code generator.
It helps me validate ideas, overcome mental blocks, and accelerate learning without replacing my own judgment.
Benefits Observed
Working in this way has changed how I experience the project. Instead of focusing only on syntax or debugging details, I
can step back and act more like a software lead: setting direction, defining structure, and designing tests. This perspective
is motivating. It allows me to keep learning by doing, while also practicing the skills needed to think at a higher project level.
Risks and Critical Perspective
That said, I am also aware of the risks. Misused, AI can easily foster intellectual laziness. It can discourage deeper exploration,
making it too tempting to accept quick answers instead of working through problems. The danger is subtle: what feels like
efficiency in the short term may lead to dependency and a weakening of critical skills in the long term.
Final Thoughts
This tension—between growth and dependency—is, to me, the most important reflection. On one hand, AI can help us break
barriers, learn faster, and concentrate on the bigger picture. On the other, it can erode the discipline and rigor that define our profession.
So the real question is not whether to use AI, but how to use it responsibly.
Done well, it becomes a powerful ally in both
learning and leadership.
Done poorly, it risks undermining the very skills we aim to build.
