Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Learn how to use gRPC and Protocol Buffers for high-performance communication between AI agent services, covering protobuf definitions, streaming RPCs, service mesh integration, and real-world performance benefits.
Design and implement a standardized API for agent-to-agent communication, covering interface contracts, service discovery, authentication between agents, and message formats that enable seamless multi-agent orchestration.
Build robust webhook systems for AI agent services, covering webhook design patterns, delivery guarantees with retries, payload signature verification, and event-driven architectures that keep agents reactive and loosely coupled.
Implement effective rate limiting for AI agent APIs using token bucket, sliding window, and adaptive algorithms. Learn per-user vs global strategies, proper response headers, and how to handle rate-limited AI agents gracefully.
Implement secure authentication for AI agent APIs using API keys for simple access, OAuth2 for delegated authorization, and JWT tokens for stateless verification. Learn token lifecycle management, scope-based permissions, and security best practices.
Design a single unified API that serves chat, voice, and task-based AI agents through a common interface. Learn channel abstraction, response normalization, and how to handle the unique requirements of each modality without code duplication.
Generate comprehensive API documentation for AI agent services using OpenAPI specifications, Redoc rendering, and interactive playground UIs. Learn automated spec generation from FastAPI, example-driven documentation, and SDK generation from your spec.
Build comprehensive monitoring and analytics for AI agent APIs, covering structured request logging, error tracking with context, usage analytics dashboards, and alerting systems that catch agent failures before users notice.
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