What We Learned from a Year of Building with LLMs (Part I) (oreilly.com)

Over the past year, the authors built real-world applications using large language models (LLMs) and identified crucial lessons for developing effective AI products. They emphasise the importance of robust prompting techniques, retrieval-augmented generation, structured workflows, and rigorous evaluation and monitoring to overcome the complexities and challenges inherent in leveraging LLMs for practical use.

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