AI Engineering

Everywhere you look, people are shouting that AI is replacing developers. Headlines say coding is now easy. Some claim anyone can be a programmer with the right AI tool. The message sounds confident and exciting. The reality is very different. AI is writing much more code than before, but software quality is getting worse. Bugs are increasing. Systems are harder to maintain. Teams feel busy, but progress is slowing down. The gap between how productive people feel and what the

AI coding tools can feel magical on small, new projects. But once you bring them into a real codebase, the cracks show fast: messy changes, repeated rework, churn, and code that looks “done” but falls apart under review. This is the gap that context engineering  is trying to close. Context engineering is not about finding a “perfect prompt.” It’s about building a workflow that keeps the model focused, accurate, and useful, especially in brownfield  codebases (large, older, co