How to Run Multiple AI Agents Without Losing Control
Running multiple AI agents often leads to chaos due to conflicting outputs and lack of coordination. A structured three-layer system can help maintain control by establishing hierarchy and shared context. This approach uses an orchestrator, specialized agents, and a shared memory system to align actions and improve efficiency.
- ▪Multiple AI agents often fail because they operate in isolated contexts and lack coordination.
- ▪The solution involves a three-layer stack: an orchestrator agent, specialized worker agents, and a shared memory system.
- ▪The shared memory system includes files that define identity, priorities, decisions, and project context to keep all agents aligned.
- ▪Each specialist agent focuses on a specific domain while the orchestrator manages task routing and output synthesis.
- ▪Clean handoffs are ensured through a protocol where the orchestrator assigns tasks with clear context and output requirements.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3885095) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Michael O Posted on Apr 28 • Originally published at xeroaiagency.com How to Run Multiple AI Agents Without Losing Control #ai #solopreneur #automation #webdev Most people who try running multiple AI agents at once end up in one of two failure modes. Either the agents contradict each other constantly, or nothing gets done because no one is "in charge" of anything. The whole stack just produces noise. I've been there.
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