Notes from production

Blog

Practical articles on AWS Bedrock cost optimization, knowledge graphs, AI infrastructure, and cloud architecture — from the ThinkXL team.

AgentCore vs Bedrock Agents vs Roll-Your-Own on Fargate

There are three realistic ways to run an AI agent on AWS, and they sit on a spectrum from "AWS does almost everything" to "you do almost everything." Bedrock Agents has AWS define and orchestrate the

What Is Amazon Bedrock AgentCore? (And When to Use It)

Amazon Bedrock AgentCore is a managed platform for deploying and operating AI agents you've already built — in any framework, with any model — without managing the runtime, memory, identity, or observ

Model Evals: How to Know If You Can Use a Cheaper Model

An eval, in the AI FinOps context, is a structured comparison: run a representative sample of real production inputs through your current model and a cheaper candidate, score both against a defined qu

What Is AI FinOps?

AI FinOps is the practice of making AI workload costs visible, attributable, and optimizable — applied to the specific economics of model inference, where the unit of cost is the token, not the instan

RAG, GraphRAG, and Knowledge Graphs: What's Actually Different

LLMs are stateless. They don't know your documents, your internal data, or what changed last week. They're only as good as what you put in front of them. This gave rise to what's now called context en

Deploying Engineering Resource Management Knowledge Graph on AWS

Resource planning in engineering orgs is a multi-hop problem. The data is there — skills, project history, availability — it's just stored in flat tables that you need to join on demand. This post wal