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Effective context engineering for AI agents \ Anthropic

anthropic.com · 3,103 words · saved by 6 readers

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

After a few years of prompt engineering being the focus of attention in applied AI, a new term has come to prominence: context engineering . Building with language models is becoming less about finding the right words and phrases for your prompts, and more about answering the broader question of “what configuration of context is most likely to generate our model’s desired behavior?" Context refers to the set of tokens included when sampling from a large-language model (LLM). The engineering problem at hand is optimizing the utility of those tokens against the inherent constraints of LLMs in or

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