Prompt Engineering Gets Attention. Context Engineering Gets Results.

Why reliable AI systems depend on context pipelines than clever prompts. For a while, prompt engineering felt like the center of the AI universe. Everywhere you looked, there were new frameworks for writing better prompts, chaining instructions together, and squeezing better outputs out of large language models. In the early wave of LLM adoption, this made sense. If the model behaved poorly, the first instinct was simple: rewrite the prompt. That approach works for s but it does not hold up for production systems.