Document-Analysis

The first post covered why I split document analysis into multiple agents. This one covers how the specialists are actually built. The Python code is not the hard part. The specialist behavior mostly comes from: the system prompt the output schema the boundaries around what the agent should ignore The code is intentionally repetitive. Once you’ve written a couple agents, it’s a breeze. The shared base class Every agent needs the same basic execution logic: ...

I built a document analysis system for RFPs and contracts using multiple specialist LLM agents instead of one general-purpose prompt. The architecture is simple: PDF → text extraction → Technical Analyzer → Risk Analyzer → Cost Analyzer → Timeline Analyzer → Coordinator synthesis → final report The interesting part is not that it calls an LLM. That’s easy. The interesting part is how much the output changes when the model is forced to analyze the same document through different lenses before producing a final answer. ...