Working on document processing workflows where different AI agents handle reading, analysis, and output generation. Current setup loses state between agents, requiring constant data rehydration. How are folks handling persistent state in multi-agent systems?
Any no-code friendly solutions that maintain context between specialized roles?
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We implemented a message bus architecture with temporary storage pockets. Each agent writes to a shared memory space that persists for the workflow duration. Requires careful cleanup rules but maintains context effectively between processing stages.
try useing workflow tools with auto state passing. some platforms have pre-built mem nodes that dont need code. just chain agents and check state persistance in settings