Agentic System Architecture: Engineering Multi-Agent Swarms for Production

Answer-first: Moving AI agents from toy demos to enterprise production requires treating them as Stateful Distributed Systems. This series documents the 6 core pillars of production agentic architecture: Swarm Topology (Router/Worker vs Shared Blackboards), Hierarchical Memory Management, Resilient Tool-Calling Protocols, AgentOps Observability, Automated Evals, and Human-in-the-Loop (HITL) Gateways. 🎯 The Architectural Challenge of Autonomous Agents Building production-ready AI agents is fundamentally a distributed systems engineering challenge, not a prompt engineering trick: ...

Part 4: AgentOps & Production Observability

← Previous Chapter: Part 3: Resilient Tool Calling | Series Hub | Next Chapter: Part 5: Agent Evals → Answer-first: AgentOps observability requires capturing entire agent execution trees (spans for LLM inference, tool invocations, and memory lookups) using OpenTelemetry AI semantic conventions to detect runaway infinite loops and attribute token costs.