Agentic AI with Message Queues: NATS, Kafka, and RabbitMQ Patterns
Compare NATS, Kafka, and RabbitMQ for agentic AI workloads. Learn async tool execution, event-driven agents, and dead letter queue patterns.
Deep dives into the technology behind AI voice agents — LLMs, speech-to-text, real-time voice processing, and more.
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Compare NATS, Kafka, and RabbitMQ for agentic AI workloads. Learn async tool execution, event-driven agents, and dead letter queue patterns.
Explore how to build agentic AI data pipelines that combine traditional ETL with LLM-powered extraction, classification, and validation loops.
Design PostgreSQL schemas for agentic AI systems covering conversation storage, agent state machines, tool logs, and vector memory columns.
Comprehensive testing strategy for agentic AI — unit testing tools and prompts, integration testing agent loops, E2E multi-agent flows, and mock LLM patterns.
Master Redis patterns for agentic AI including LLM response caching, conversation sessions, pub/sub for real-time events, and agent performance optimization.
Design an API gateway for agentic AI with multi-model routing, API key management, rate limiting, WebSocket proxy, and health-based routing.
Build a full observability stack for agentic AI with OpenTelemetry tracing, Grafana dashboards, custom agent metrics, and alerting strategies.
Build CI/CD pipelines for agentic AI using GitHub Actions with prompt regression tests, LLM evaluation, canary deployments, and rollback strategies.