Hands-on tutorials for Claude Code, AI agents, cloud and system design
AWS Guidance for Enterprise Agentic AI Platform on AWS is an opinionated, deploy-ready reference platform published in the official aws-solutions-library-samples org for running production AI agents on Amazon Bedrock AgentCore. The repo, authored by Mehdi Nemlaghi and Cristian Balint and released under the permissive MIT-0 license in June 2026, takes a problem that every enterprise… Continue reading
TL;DR 30 sec12 min coredeep dive optional Temporal policies are stateful AgentCore Gateway rules that allow or deny an agent’s next action based on what the agent has already done in the session, closing the gap that per-request, stateless authorization leaves open. Stateless authorization checks each call in isolation; agents break in the sequence, so… Continue reading
AgentCore Gateway is the managed front door that turns scattered AI agent tool access into one governed endpoint. In this tutorial you will create a gateway, register a Lambda function as an MCP tool, write Cedar allow and deny rules, and read the audit record every call leaves behind. No gateway infrastructure to run, no… Continue reading
Agentic AI transforms how cloud architects build intelligent systems on AWS. Instead of writing rigid procedural code for every workflow, you delegate goals to software agents that perceive context, reason about trade-offs, and act on your behalf. This guide covers the foundations and shows how Amazon Bedrock, AWS Lambda, and AWS Step Functions bring autonomous… Continue reading
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, know when… Continue reading
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 AWS agentic AI frameworks encode the critical plumbing (prompt assembly, tool calling, retry loops, memory, tracing)… Continue reading
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
RAG optimization begins before a user submits a query, at the source documents that feed retrieval-augmented generation. Document and context engineering is the discipline of writing for two readers: the human who skims the page and the embedding model that chunks it. RAG Optimization: What You’ll Learn RAG optimization is the practice of writing and… Continue reading
Vector database selection on AWS for RAG: compare OpenSearch, pgvector, MemoryDB, Neptune Analytics, DocumentDB, S3 Vectors, Bedrock Knowledge Bases, and Kendra in 2026.
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Healthcare RAG on AWS using Amazon Bedrock, OpenSearch, and Neptune. Patient data augmentation, re-admission prediction, and talent management solutions grounded in HIPAA-eligible infrastructure.
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AgentOps on AWS — operationalize agentic AI at enterprise scale with CI/CD pipelines, guardrails, observability, multi-tenancy, and business alignment strategies across the six AWS focus areas.
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Agentic AI economics compares total human costs against agent costs, introduces pay-per-outcome pricing, and gives you the ROI models to scale automation sustainably on AWS, answering when replacing human labor with agentic AI actually pays off, and where agentic AI economics tips in favor of automating. Agentic AI Economics: What You’ll Learn Agentic AI economics… Continue reading