AI Commentary
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Prompt engineering, the craft of designing input text for large language models (LLMs) [], focuses on steering the model's output through instructions and examples. Context engineering, however, is a broader system-level discipline that programmatically assembles *all* information an LLM encounters during inference []. This includes not just prompts but also retrieved documents, memory, and tools. A travel booking agent example illustrates the difference: initially booking a hotel in Paris, Kentucky, instead of Paris, France, due to insufficient context []. This highlights that while prompt engineering addresses the wording of the request, context engineering ensures the LLM has the necessary environmental information, like the conference location, to plausibly complete the...
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Video summary will appear here after you start watching
Prompt engineering, the craft of designing input text for large language models (LLMs) [], focuses on steering the model's output through instructions and examples. Context engineering, however, is a broader system-level discipline that programmatically assembles *all* information an LLM encounters during inference []. This includes not just prompts but also retrieved documents, memory, and tools. A travel booking agent example illustrates the difference: initially booking a hotel in Paris, Kentucky, instead of Paris, France, due to insufficient context []. This highlights that while prompt engineering addresses the wording of the request, context engineering ensures the LLM has the necessary environmental information, like the conference location, to plausibly complete the...