Context-Engineering

You build a RAG pipeline, connect it to Azure OpenAI, and the answers come back… meh. Generic. Sometimes it ignores the context you sent. Sometimes it makes things up. The model is powerful, but input quality usually determines most of the result. Context engineering is the discipline of assembling that input so the model gives you what you actually need. It is not just “prompt engineering” with a fresher label. It is engineering: structure, constraints, and trade-offs. ...

Three years ago, the question I heard most was: “what’s the best prompt?” Two years ago, it shifted to: “how do I do RAG?” Last year: “how do I build an agent?” This year, the conversation is different. People are asking how to transform an entire organization to operate with agents. Not a chatbot on the website. Dozens of agents embedded in business processes, with governance, observability, granular permissions. That progression tells a story, and we often discuss each phase as if it appeared out of nowhere. ...