Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Learn how to design WebSocket-based architectures for AI agents, covering connection lifecycle management, protocol framing, heartbeat mechanisms, and automatic reconnection strategies for production reliability.
Build a production-grade real-time dashboard for monitoring AI agents, featuring live metrics pipelines, streaming log aggregation, agent health indicators, and efficient frontend rendering with React.
Design event-driven AI agent systems using pub/sub messaging, event sourcing for full audit trails, and CQRS to separate read and write models for scalable, observable agent architectures.
Implement real-time communication between distributed AI agent instances using Redis Pub/Sub, covering channel design, message serialization, scaling patterns, and understanding delivery guarantees.
Build AI agent communication systems using NATS messaging, covering subject-based routing, queue groups for load balancing, request/reply patterns, and JetStream for persistent message delivery.
Design systems where multiple users interact with shared AI agents simultaneously, covering session sharing, conflict resolution, turn management, and maintaining consistent state across concurrent participants.
Build a notification pipeline for AI agents that delivers push alerts, emails, and SMS messages based on configurable trigger conditions, with deduplication and user preference management.
Learn how to create and enforce latency budgets for real-time AI systems, breaking down time allocation across network, preprocessing, inference, tool execution, and response delivery layers.
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