Good software is no longer a single category. Leadership must decide which kind they are building, or inherit the consequences of not deciding.
Most software becomes problematic because leaders avoid explicit lifecycle decisions.
AI and no-code democratize software creation, but maintenance, ownership, and longevity remain scarce skills.
AI changes how teams work, learn, and make decisions. Leadership must understand these shifts to maintain quality and coherence in complex systems.
AI accelerates output but not judgment. Quality must be engineered deliberately in an era where most code is machine-generated.
Bad software is rarely the result of weak engineers. It is the result of weak management decisions.
The definition of good software has split into two realities. Most leaders still haven’t realized it.