Preface
Between 2023 and 2025, the release of OpenAI’s large language models (LLMs) as REST endpoints captivated professionals across industries with their ability to understand and respond to natural language. In 2024, we marveled at their ability to produce context-aware answers grounded in a corpus of documents. This approach, known as retrieval-augmented generation (RAG), quickly solidified itself as a cornerstone technique in modern AI.
As we experimented with this technology, we discovered that LLMs could do more than answer questions: they could be extended to use tools to solve problems. This unlocked new possibilities for software engineers, who began developing the tools necessary to enable what we now, in 2025, refer to as agents. ...
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