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Google Cloud Course Breaks Down How AI Agents Work and Why They Matter

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A developer enrolled in Google Cloud's Agentic Summer course, powered by the Gemini Enterprise Agent Ready (GEAR) program, is sharing structured notes on how AI agents function. An AI agent is defined as a software system that uses a large language model (LLM) to accomplish goals on a user's behalf, built around three core components: an LLM, tools, and contextual memory. Tools are often accessed via the Model Context Protocol (MCP), which goes beyond standard APIs by providing agents with guidance on when and how to use specific integrations. Memory management is highlighted as critical, involving strategies like context compression, summarization, and selective retention to keep agents focused and effective. The course also introduces agent design patterns, ranging from simple single-agent setups to more complex multi-agent architectures suited for advanced tasks.

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Google Cloud Course Breaks Down How AI Agents Work and Why They Matter · ShortSingh