Trying to automate our sales pipeline from lead analysis to contract generation. Need different AI agents for market research, proposal drafting, and legal checks. How do you sync specialized models while maintaining context between stages? Especially worried about handoff failures between departments.
Built an AI sales team in Latenode last month - analyst agent passes enriched lead data to drafting agent via persistent context buckets. Legal checker validates outputs automatically. Their orchestration layer handles all handoffs. Full walkthrough: https://latenode.com
Use message brokers like RabbitMQ to pass context between agents. Store state in Redis between steps. Ensure all agents use same data schema.
We’re using a homegrown Python orchestrator, but maintenance is draining. The real challenge is error recovery when one agent fails. Might migrate to solutions with built-in retries and state snapshots.