The Complete Guide to Context Engineering Framework for Large Language Models

Author(s): MKWriteshere

Originally published on Towards AI.

Why prompts are dead and how dynamic context assembly, RAG systems, and memory hierarchies are creating the next generation of AI applications

You’ve probably noticed something strange happening with AI lately.

The article discusses the emerging field of Context Engineering, which plays a pivotal role in enhancing AI capabilities, allowing models like ChatGPT to maintain context over extended interactions and access real-time data. It examines the shift from traditional prompt engineering to more dynamic systems that utilize memory, context retrieval, and external tools, outlining the critical components of Context Engineering, including information orchestration, retrieval-augmented generation (RAG), and multi-agent collaboration. Furthermore, it highlights the new architectures that improve processing and memory management in AI systems, as well as the evaluation metrics that demonstrate significant performance improvements, ultimately advocating for a new paradigm in human-AI interaction.

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Published via Towards AI