I want the code to explain why it exists. Every abstraction, dependency, pattern, and
shortcut should be carrying its weight. I do not get much value from software that looks
sophisticated but is hard to change. The better version is usually plainer: a system
another engineer can understand, question, and safely reshape.
Technical depth matters when it changes what the product can do or makes the next change
less risky. The right architecture depends on the shape of the work around it: who uses
the product, who maintains it, what has to keep working, and what the existing code
already makes easy or hard.
I trust implementation as a way of thinking. Diagrams and discussions are useful, but
working inside the system exposes the details that decide whether an idea holds up.
Sometimes the important thing is not visible until the code has to run, migrate, fail,
or fit next to everything else.
I like learning tools well enough to know what kind of judgment they require. AI belongs
in that category. I use it to explore directions, draft rough material, search through
context, prototype, and automate small pieces of work. I do not use it to decide whether
the result is correct, maintainable, or useful.
Software is one of the ways I learn. The code teaches you about the product, the
constraints, and the people who will live with the decisions after you make them. I am
usually trying to leave behind something a little easier to reason about than what I
found.