Software development is changing, not because developers are writing less code, but because they’re increasingly supervising systems that generate and validate a lot of code. Test generation is one of the clearest places where this shift is already happening today. In practice, most teams aren’t asking “can AI write tests?” They’re asking something far more practical: How do we make changes to real codebases without breaking things we don’t fully understand? This post walks through a concrete, end-to-end workflow for embedding a test generation agent into the SDLC, using a scenario every developer recognizes: adding a feature to existing code, under real constraints, with real risk. No theory. Just how it fits into day-to-day development.