LangChain excels at chaining LLMs together using agents to delegate actions to models. Its use cases emphasize prompt optimization and context-aware information retrieval/generation; however, with its Pythonic highly modular interface and its huge collection of tools, it is the number-one tool to implement complex business logic.

It will be instructive to observe whether model sizes for LLMs keep increasing at the same rate as they have. This is an important question since it determines if the development of LLMs will be firmly in the hands of large organizations.