Articles on building things — cloud platforms, AI agents, data pipelines, mobile apps, and the occasional robotic arm.
A visual guide to understanding artificial intelligence in 2026. 51 key concepts organized into 9 clusters, from machine learning basics to generative AI and agentic systems — explained for non-technical readers.
Most developers treat Claude Code as a chat box with tools. The ones who get 10x results treat the context window as a product they design. A practitioner's guide to 11 chapters on mastering Claude Code, from first agentic interaction through multi-agent orchestration.
10 hands-on Jupyter notebooks for Exploratory Data Analysis using real NIST datasets. Download notebooks with bundled data files, or run them instantly in Google Colab.
Why prompting an AI agent to build a FastAPI app gets you functional code but not production infrastructure. How hand-crafting 13 production concerns into a chassis lets the agent focus on what it's good at: business logic.
Production-tested guide to writing secure GitHub Actions workflows. 48 rules across security, semantic correctness, best practices, and style with fix examples.
A comprehensive interactive reference for Exploratory Data Analysis based on the NIST/SEMATECH Engineering Statistics Handbook. 90+ pages covering graphical techniques, quantitative methods, probability distributions, and case studies.
Production-tested guide to writing secure Kubernetes manifests. 67 rules across security, reliability, RBAC, and cross-resource validation with fix examples.
A production-tested guide to writing secure, efficient Docker Compose files. 52 rules explained with real-world consequences and fix examples. Try the free browser-based validator.
A practical framework for choosing the right database model. 12 categories scored across 8 dimensions, from scalability and performance to reliability and beyond.
