Summary

This chapter explored different techniques for integrating LLMs into workflows to automate prompting at scale. We looked at easy template options such as SheetSmart for Google Sheets as well as no-code automation platforms such as Zapier. For more advanced customization, developer tools such as LangChain, Flowise, and Langflow enable building pipelines and applications using multiple LLMs. We walked through sample use cases for competitive intelligence, customer data enrichment, and conversing with documents to see how integrations could work in practice.

Looking ahead, tight connections between conversational AI and everyday productivity apps will enable LLMs to provide more relevant, contextual recommendations and automation. However, while integration unlocks usefulness, it also raises important ethical considerations; we will explore this in the next chapter. As these powerful technologies become further embedded into daily life, principles such as transparency, accountability...