Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
Author:John Berryman (Author), Albert Ziegler (Author)
Publisher finelybook 出版社:O’Reilly Media
Edition 版本:1st edition
Publication Date 出版日期:2024-12-10
Language 语言:English
Print Length 页数:280pages
ISBN-10:1098156153
ISBN-13:9781098156152
Book Description
About the Author
Before his work on Copilot, John built an impressive career as a search engineer. His diverse experience includes helping to develop next-generation search system for the US Patent Office, building search and recommendations for Eventbrite, and contributing to GitHub’s code search infrastructure. John is also coauthor of
Relevant Search (Manning), a book that distills his expertise in the field.John’s unique background, spanning both cutting-edge AI applications and foundational search technologies, positions him at the forefront of innovation in LLM applications and information retrieval.
Albert Ziegler has been designing AI-driven systems long before LLM applications became mainstream. As founding engineer for GitHub Copilot, he designed its prompt engineering system and helped inspire a wave of AI-powered tools and “Copilot” applications, shaping the future of developer assistance and LLM applications.
Today, Albert continues to push the boundaries of AI technology as Head of AI at XBOW, an AI cybersecurity company. There, he leads efforts blending large language models with cutting-edge security applications to secure the digital world of tomorrow.
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