Strategies for Mitigating Context Failures in LLM Applications
By
itzlambda
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Summary
This article provides practical strategies for mitigating and avoiding context failures in large language model applications, focusing on information management techniques like Retrieval-Augmented Generation (RAG) and context window optimization. It builds on previous discussions about how long contexts can fail and offers 6 specific tactics for improving context management to build better AI agents, referencing insights from experts like Andrej Karpathy about properly packing context windows.
Key quotes
· 4 pulledEverything here is about information management. Everything in the context influences the response.
We're back to the old programming adage of, 'Garbage in, garbage out.'
Building LLM-powered apps means learning to 'pack the context windows just right'
Retrieval-Augmented Generation (RAG) is the act of selectively adding relevant information
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