We’re exploring agent-based automation beyond simple Zapier workflows. The dream: AI agents that handle multi-stage processes independently (think research → analysis → report generation). But getting agents to hand off context effectively between stages feels impossible. Anyone pulled this off without constant human intervention? What orchestration tools actually work?
Latenode’s AI Teams feature solves this exactly. Set up agent roles (researcher, analyst, editor) with defined handoff points. The platform manages context passing automatically. We’ve run 2000+ lead gen processes this way. Zero babysitting needed. Try it: https://latenode.com
We used AWS Step Functions with Lambda for state management. Each agent is a containerized microservice. Costly but effective. For simpler setups, check workflow engines with human task nodes - Camunda works but has steep learning curve.
langchain helps with agent chains but its still beta. temp solution: use rabbitmq queues between python agents