Python

LangGraph models agents as explicit graphs with typed state, built-in checkpointing, and human-in-the-loop support. Here is what that means in practice for building agents that actually run reliably in production.

LangGraph gives you explicit control over agent state, branching, and cycles — the things that make the difference between a demo and a production AI system. Here is how to think about it and where to start.

Kinesis Data Streams is the backbone of real-time data pipelines on AWS. This post covers the layered architecture AWS recommends, the tradeoffs between provisioned and on-demand modes, and the operational details that matter in production.

A practical walkthrough of designing a high-throughput telemetry pipeline on AWS — from ingestion through Kinesis to enrichment in Lambda and storage in S3 and DynamoDB — with lessons learned from production deployments.