Agents & LLMs

Agents & LLMs are autonomous systems: They combine a Large Language Model (LLM) with planning, memory, and external tools to execute complex, multi-step tasks without continuous human oversight.

This technology moves LLMs beyond simple chat responses: Agents integrate the LLM (the 'brain') with a core loop of reasoning, action, and observation. Key components include a memory module (for context and history), a planning module (for task decomposition), and a toolset (for external actions like web search or code execution). Projects like AutoGPT and BabyAGI first demonstrated this autonomy; today, enterprise frameworks like LangChain, CrewAI, and Microsoft's Autogen standardize development. The objective is clear: Delegate complex, sequential workflows, allowing the system to self-correct and achieve high-level goals—for example, a financial agent analyzing Q2 earnings calls and summarizing key technological moats.

https://developer.nvidia.com/blog/introduction-to-llm-agents/