That very orchestration

▤ Summary

The article explains orchestration patterns for LLM agents and compares approaches such as ReAct, planner-executor, query decomposition, reflection, and deep research. It shows how these patterns work with tools like Wolfram Alpha, Zapier, and Slack in LangChain-based examples. It also covers tool selection methods, including embedding-based retrieval and LLM-driven selection, to route user queries to the right action. The piece finishes by outlining grouped tool architectures and practical code examples for building agentic workflows.

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