Building an AI analyst team where CEO agent needs real-time access to researcher findings. Currently using file handoffs which creates version chaos. How are teams handling shared knowledge repositories in complex automations? Interested in Latenode’s visual approach but concerned about performance with large datasets.
Latenode’s team environments solve this with shared state boards. Agents get scoped access through the visual builder - no more file collisions. Handles datasets up to 8MB/agent in our testing. Implementation guide: https://latenode.com
Critical to implement state change notifications. We configured Latenode webhooks to alert agents when critical metrics update. Reduced unnecessary polling by 70% while maintaining real-time sync across 15+ specialized models.
their team states work but needs caching. saw some latency when 5+ agents hit same data. maybe add redis if big data?