Enhancing LLMs: 7 Context Engineering Strategies That Work in Production
Last Updated on September 4, 2025 by Editorial Team
Author(s): Eivind Kjosbakken
Originally published on Towards AI.
The benefits of context engineering for scaling LLMs to millions of outputs
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This article discusses the science of context engineering, detailing how to provide LLMs with the correct context to enhance their performance through techniques like retrieval-augmented generation (RAG) and few-shot prompting. It emphasizes the importance of dynamically selecting relevant examples and managing context length to avoid performance drops, shedding light on both the methodologies and implications for effectively deploying LLMs in scalable applications.
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