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7 min read
Creating a Multi-Agent System with Python and LangChain
I had a pipeline that kept eating itself. The task was straightforward: research current trends in vector database pricing, then write a short summary. One agent, a handful of tools, a careful system prompt. It started well — pulling results, skimming content, taking notes. Then halfway through composing a paragraph, something it wrote made it doubt its own data. So it searched again. Then wrote some more. Then re-searched because a sentence it drafted referenced a number it couldn't confirm. Four minutes and $0.80 in API calls later, I had output that mixed raw search snippets with half-composed paragraphs. Not a bug — just the expected behavior of one model trying to do two incompatible jobs at once.