Post by Anirudh C.

AI agents are starting to look less like chatbots and more like orchestrated systems. The real shift? The model is not the system. The orchestration layer is. Think of it like an organization. A supervisor agent understands intent and delegates work. Specialized agents (recommendation, cart, knowledge) own focused responsibilities, each with clearly defined tool contracts. In a production-ready setup using Amazon Bedrock Agents: • Agents invoke tools through structured Action Groups • API Gateway enforces security boundaries • Specialized Lambda functions isolate business logic • ML models personalize results • RAG enriches responses with contextual knowledge Instead of: Filter → Rank → Display We now design systems that: Reason → Clarify → Invoke Tools → Personalize → Enrich As complexity grows, a single agent becomes a monolith. Multi-agent patterns isolate responsibilities — similar to how microservices evolved from monoliths. I explored and refined this architecture pattern while participating in the AWS BeSA community program. I shared the deeper breakdown (with diagrams) here: 🔗 https://lnkd.in/eiuYbuDS Would love to hear how you're structuring agents in real-world systems. #AWS #AgenticAI #SystemDesign #CloudArchitecture #BeSA