Working with AI coding tools has changed how I think about architecture, but not in some huge “future of software” kind of way. It’s been more of a practical thing I started noticing while generating and modifying real code day to day. One pattern keeps showing up over and over again: When a system mixes too many responsibilities together, AI-generated code becomes harder to guide and less consistent. But when responsibilities are separated clearly, the output suddenly becomes much more stable and predictable. That sounds pretty obvious on paper, but the difference feels much bigger once you work with AI tools regularly. Where things start getting messy In a lot of real-world projects, especially older ones, responsibilities slowly drift into the same place over time. A single service might handle validation, database access, caching, orchestration, mapping, and sometimes authorization too. It usually happens gradually, so nobody really notices it becoming complicated until much later.…