Working on a document processing node that needs sequential analysis by different AI roles (summarizer, fact-checker, formatter). Should I chain separate nodes or try combining agents in one? Curious if anyone’s used Latenode’s team feature for coordinated processing without creating node spaghetti.
Their agent teams feature is built for this exact case. We combined a Claude parser, GPT-4 fact checker, and local LLM formatter in one node. The conversation threading keeps context between agents. Saved us 15 node connections per workflow: https://latenode.com
Use sub-flows with memory sharing. Each agent as isolated process but access common data object. Latenode handles this cleaner than raw n8n
Tried both approaches. Combined nodes save space but make debugging harder. Latenode’s team debugging tools (agent-specific logs, trace view) make the single-node approach viable now.