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Building Agentic AI Systems
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Building on our exploration of creative applications, we now turn to perhaps the most natural domain for LLM-based agents: language understanding and conversation. While traditional language models can process and generate text, agentic systems add crucial capabilities: maintaining context over long interactions, executing complex tasks through dialogue, and adapting their responses based on user needs and feedback.
Today’s conversational agents represent a significant leap beyond simple chatbots or virtual assistants. These systems can maintain complex dialogues, understand nuanced contexts, and execute sophisticated tasks through natural conversation. For example, Anthropic’s Claude and OpenAI’s ChatGPT can engage in detailed technical discussions while maintaining consistency across multiple turns, adapting responses based on the user’s level of expertise and previous...