Context Engineering extends beyond prompt engineering by supplying comprehensive context for LLM tasks.
The quality of context, not just model capability, determines the success of AI agents.
Context comprises system prompts, user requests, conversation history, long-term memory, retrieved data, tools, and output formats.
Context Engineering systems dynamically gather and format relevant information and tools before each LLM call.
Supplying the right context at the right time transforms simple demos into powerful, reliable AI agents.
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