02 – AWS Agentic AI Patterns: From Reasoning to Multi-Agent

Agentic AI patterns are the reusable blueprints that turn a generic language model into a purposeful production system. Where Part 1 covered the why, this guide maps each pattern — reasoning, retrieval-augmented, orchestrator, multi-agent — to the AWS services that bring it to life. Agentic AI Patterns: What You’ll Learn You’ll recognize the core patterns,… Continue reading

03 – AWS Agentic AI Frameworks: Strands, LangChain, and MCP

Agentic frameworks turn a raw LLM into a dependable agent. Here we look at the frameworks, platforms, and protocols you actually install and ship on AWS: LangChain, Strands Agents, CrewAI, AutoGen, MCP, and A2A. Agentic Frameworks: What You’ll Learn Agentic frameworks encode the critical plumbing — prompt assembly, tool calling, retry loops, memory, tracing —… Continue reading

04 – AWS Multi-Tenant Agentic AI: Isolation and Cost Architecture

Multi-tenant agents turn one agentic AI system into a SaaS serving many customers from shared infrastructure. Siloed, pooled, or hybrid deployment determines your unit economics and security. Multi-Tenant Agents: What You’ll Learn This guide maps the AWS-recommended deployment models, tenant-context propagation patterns, and isolation primitives across siloed, pooled, and hybrid topologies on Bedrock AgentCore. By… Continue reading