Over the past few years, AI has improved software engineering, but the opportunity ahead is still massive. The first wave of models and copilots accelerated individual tasks, such as writing a function from a description, explaining what a code block does, drafting documentation, or other similar tasks. These were point solutions. You still had to decide what to build, understand the broader system context, integrate the code into your architecture, and debug when things broke in production. The cognitive load of understanding your systems remained unchanged.