For a long time, "prompt engineering" meant finding the right words. Better instructions, clearer examples, stricter output formats. That still matters, but it is no longer the whole story. The more useful shift is from prompt engineering to context engineering. Prompting is only one layer A good prompt can improve an answer. But many failures do not come from bad wording. They come from missing context. The model does not know: your codebase conventions the current ticket the relevant API documentation your team's security rules which files changed what "done" means in this workflow If that context is missing, the model has to guess. Better phrasing will not fix that. What context engineering means Context engineering is the practice of deliberately shaping what the AI sees before it acts.…