One thing we've noticed is that AI rarely creates the biggest problems through bad code it creates them through missing boundaries.
A generated endpoint that mixes HTTP handling, business rules, database access, external API calls, and validation can look perfectly fine in a demo. The problems show up later when requirements change and every modification creates unexpected side effects.
At IT Path Solutions, we've found that AI becomes significantly more valuable when architecture is defined before generation starts. Clear service boundaries, repository patterns, and domain ownership give both engineers and AI tools guardrails to work within.
The interesting shift is that AI has made architecture more important, not less. Generating code is becoming cheap. Maintaining, scaling, and safely evolving that code is where engineering discipline still creates the biggest advantage.
Speed gets you to production. Structure determines whether you can keep shipping six months later.