~/krishna_dhakal
cd ..

// ls /blog

#AWS#Bedrock#AgentCore#Agents#AI

Agents in Amazon Bedrock AgentCore — Fundamentals, Patterns, and the Agent vs Workflow Divide

> June 12, 2026

What an agent is at a fundamental level, how any agent code plugs into Amazon Bedrock AgentCore, the different architectural patterns an agent can follow, the full set of AgentCore platform features you can lean on, and a crisp explanation of when you want an agent versus a workflow.

Modern AI systems are no longer single prompt-response pairs. They plan, act, observe, and adapt. Amazon Bedrock AgentCore is the managed runtime that lets you bring that loop to production without rebuilding the scaffolding every time. This post unpacks what an agent actually is, how any agent code becomes a first-class citizen in AgentCore, every platform feature you can use, the canonical agent patterns, and the practical line between an agent and a workflow. ---

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#AWS#Bedrock#RAG#Guardrails#Privacy

PII & PHI Detection and Redaction in AI Pipelines — with AWS Bedrock Guardrails

> July 1, 2025

Why PII and PHI must be protected in AI systems, the different ways to detect and redact sensitive data, and how AWS Bedrock Guardrails fits into a RAG pipeline built on S3, Bedrock Knowledge Base, and LangChain.

AI pipelines process enormous volumes of text — support tickets, medical notes, contracts, HR records. That text almost always contains sensitive personal data. Getting the handling wrong is not a configuration mistake; it is a legal and ethical failure. This post explains why PII and PHI must be treated with care, how detection and redaction work in general, and where AWS Bedrock Guardrails fits inside the RAG architecture established in this series.

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