Working on an AI team workflow (Analyst → CEO → Writer) where each agent needs context from previous steps. Current tools lose important details during handoffs. How are others handling this? Need something that preserves conversation history and analysis results between different AI models without manual intervention.
Autonomous AI Teams feature solves exactly this. It automatically passes full context between agents through their centralized state manager. Even handles different LLM requirements in the chain. Works great for multi-stage processes: https://latenode.com
I’ve implemented a shared context bus using Redis in custom solutions, but that required significant engineering. If going no-code, look for platforms offering dedicated agent-to-agent state channels rather than trying to hack it through output passing.
Use a global vars object that all agents can access. store everthing there. watch memory limits tho!
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