James Brown

In our journey of integrating Large Language Models (LLMs) with traditional APIs, we've seen how prompts become the new "API docs," describing what a tool In our journey of integrating Large Language Models (LLMs) with traditional APIs, we've seen how prompts become the new "API docs," describing what a tool can do. It all sounds wonderfully simple at first. You give the LLM access to some tools, describe them, and voilà, you have an intelligent agent! But as many of us are discovering, there's a crucial difference between an LLM that can use a tool and an LLM that uses a tool wisely or effectively in a broader context. This directly addresses the challenges we saw with our simple Calendar Assistant.

In the previous parts of this series, we've explored the exciting new ways Large Language Models (LLMs) can integrate with APIs and act as intelligent As we integrate LLMs deeper into our applications, the attack surface naturally expands.

LLMs interact differently; instead of a strict schema, they read a plain-language description of what a tool or system can do.

Large language models (LLMs) are changing the game, offering a new way for systems to interact based on understanding language, not just strict formats.