What you need to make an agent
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A practical breakdown of the four core components needed to build an AI agent: RAG (Retrieval Augmented Generation), tool calling, memory management, and feedback loops. Includes a concrete example using Anthropic's Python SDK tool_runner, explains how tool calling enables iterative data retrieval, covers memory compaction strategies for long sessions, and discusses feedback mechanisms including human-in-the-loop approaches.
Table of contents
RAGTool callingMemoryFeedback loopScaling Fast book free previewSenior Mindset BookSort: