Fr. 105.00

Generative AI Design Patterns - Solutions to Common Challenges When Building Genai Agents and Applications

English · Paperback / Softback

Shipping usually within 3 to 5 weeks

Description

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Generative AI enables powerful new capabilities, but they come with some serious limitations that you'll have to tackle to ship a reliable application or agent. Luckily, experts in the field have compiled a library of 32 tried-and-true design patterns to address the challenges you're likely to encounter when building applications using LLMs, such as hallucinations, nondeterministic responses, and knowledge cutoffs.
This book codifies research and real-world experience into advice you can incorporate into your projects. Each pattern describes a problem, shows a proven way to solve it with a fully coded example, and discusses trade-offs.

  • Design around the limitations of LLMs
  • Ensure that generated content follows a specific style, tone, or format
  • Maximize creativity while balancing different types of risk
  • Build agents that plan, self-correct, take action, and collaborate with other agents
  • Compose patterns into agentic applications for a variety of use cases


About the author










Valliappa (Lak) Lakshmanan works closely with management teams across a range of enterprises to help them employ data and AI-driven innovation to grow their businesses. Previously, he was the Director for Data Analytics and AI Solutions on Google Cloud and a Research Scientist at NOAA. He co-founded Google's Advanced Solutions Lab and is the author of several O'Reilly books and Coursera courses. He was elected a Fellow of the American Meteorological Society (the highest honor offered by the AMS) for pioneering machine learning algorithms in severe weather prediction.

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