Over the last few years, the conversation around AI has slowly shifted from prompt engineering to something more structured and more powerful: context engineering.
When you are working on a chatbot that answers questions around a knowledge base or working on an agentic AI framework that is very complex, the way you architect context depends entirely on the problem you are solving. Simply put, context complexity scales with the task uncertainty. Simple, predictable tasks require minimal context structuring, while complex, multi-step tasks require sophisticated context orchestration.
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