From Prompt Engineering to Context Engineering: What Changed and Why It Matters

As AI applications evolved from simple chatbots to complex production systems with tools and multi-step workflows, the focus has shifted from prompt engineering to context engineering - the discipline of designing the complete information environment an LLM receives, including system instructions, retrieved documents, tool results, and conversation history. Production AI systems fail primarily because models receive wrong or irrelevant context rather than poorly written prompts, requiring dynamic orchestration of information pipelines instead of static text optimization.