The Complete AI Agent Architecture: From Perception to Action
A field guide to designing production AI agents — from perception and reasoning loops to memory, tool routing, and the orchestration patterns that keep them reliable at scale.
RAG vs CAG: What the Difference Actually Means in Production
A practical, architecture-first comparison of Retrieval-Augmented Generation and Cache-Augmented Generation, with patterns for combining both in production LLM systems.
What If Your Coding Agent's Context Was Infinite?
Infinite context windows are the next frontier for coding agents. We unpack what truly changes in architecture, debugging, and developer workflow when agents stop forgetting — and why context size alone is not the same as context quality.
Learning AI Engineering from Scratch in 2026: A Production-First Roadmap
Skip the tutorials and learn AI engineering the way it actually ships in production: pick a stack, build small, evaluate honestly, and deploy behind an API. Here’s the roadmap.
Inside Linux Namespaces: A Deep Dive into the Kernel Primitives Behind Modern Containers
Namespaces are the unsung kernel feature behind every container runtime. This post walks through the eight namespace types, how they appear in the kernel, and how Docker, Kubernetes, and runc compose them into the isolation boundary you trust in production.