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Chief - ‘Agent’ might be the most misused term in tech right now Here's what separates real agents from glorified chatbots: At their core, AI agents are LLMs with a specific role and task that have access to memory and external tools. They use reasoning capabilities to plan steps and take actions to complete tasks. Four components that make an agent agentic: • An LLM (with a defined role and task) • Memory systems (both short-term and long-term) • Planning capabilities (to determine required steps) • Tools (like databases, web search, or APIs) 𝗦𝗶𝗻𝗴𝗹𝗲-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: In its simplest form, a single-agent RAG architecture functions as a router. This approach can combine reasoning, retrieval, and answer generation in one agent. 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: These systems chain multiple specialized agents together, often with a master agent coordinating the process. For example: • One agent might intelligently retrieve information from various internal data sources • Another could access, augment and clean the data • A third might specialize returning personalized results to a user Agents exist on a spectrum of autonomy. The level of agentic behavior largely depends on how much decision-making authority is delegated to the LLMs. Anyone here using multi-agent systems in production yet? 👀 Cre: Victoria Slocum

Agentic IA
Ten years ago, many of these roles didn’t even exist. Today, they are at…

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Agentic IA