preface
In late 2022, something changed. Large language models (LLMs) stopped feeling like experimental demonstrations and started becoming genuinely useful. A quick attempt to summarize a paragraph evolved into a chatbot capable of answering questions, and a small script turned into a service that other teams wanted to try. Before long, LLMs were no longer a curiosity—they had become an essential part of the software development toolkit.
Here's why that’s so exciting: LLMs allow software to “speak human.” They can revise a contract, turn logs into meaningful answers, draft code, and plan the next step—and then invoke the right tools and data to actually accomplish the task. Combined with retrieval and tool use, an application stops feeling like a rigid machine and begins to feel more like a collaborative partner. The potential is significant, but turning that potential into production systems isn’t simple. It still requires careful work to integrate data flows, design effective prompts, ground answers with retrieval, orchestrate multi-step workflows, and monitor how the system behaves once it’s deployed.