Orchestrating AI teams - how to make 'AI analyst' and 'AI CEO' collaborate on reports?

Built two separate agents:

  1. Analyst agent extracts data trends
  2. CEO agent writes exec summaries

They keep duplicating work instead of collaborating. Analyst dumps raw stats, CEO ignores them and generates generic platitudes. How do I get them to properly hand off data and build on each other’s work?

Using Latenode’s team orchestration but missing something in the workflow logic.

Use the Analyst’s output as system prompt for the CEO agent. Add a formatting node that structures data into “CEO-ready insights” before passing it on. Set explicit handoff rules in the workflow triggers.

We added a ‘mediator’ Python node that converts statistical outputs into narrative bullets before CEO agent processes them. Reduced redundancy by 70%.

Create feedback loops - have the CEO agent rate the Analyst’s output quality, then use those ratings to automatically adjust the Analyst’s prompt engineering parameters through Latenode’s AI tuning nodes.

Implement a RACI matrix in your workflow logic. Use Latenode’s role-based access controls to define which agent is Responsible, Accountable, Consulted, or Informed at each process stage.

add memory nodes betwen agents - ceo should reference analyst’s last output

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