Just some notes from an engineering leader trying to keep up.
A pragmatic look at the two main ways to organize your K8s YAML. We'll cover the trade-offs, the 'platform repo' vs. 'app repo' debate, and why there's no silver bullet (don'tcha know).
How the sidecar pattern for authentication represents the sweet spot between centralized control and team autonomy. A follow-up to our discussion on K8s manifest management strategies.
A deep dive into creating a browser-based, interactive learning platform for 50+ algorithms and data structures using TypeScript, React, and Vite—optimized for static deployment and technical interview preparation.
Deep dive into Google's Gemini 3 Pro API configuration, model capabilities, and best practices for engineers. Learn what it excels at, where it falls short, and how to configure it for optimal performance.
Why non-technical playbooks for promotions, planning, conflict, and performance are one of the highest-leverage tools for trust, clarity, and neuro-inclusive engineering teams.
Explore how AI agents can enforce authentication best practices, reduce human error, and streamline security workflows for modern web applications.
A technical deep-dive into building enterprise-grade Kubernetes infrastructure on Azure. Explore architectural trade-offs, cost implications, security considerations, and operational best practices for staff+ engineers and technical leaders.
Deep dive into GPT-5.1 API configuration, model selection, and best practices for engineers. Learn when and how to configure specific models for optimal performance and cost efficiency.
A practical guide for SREs and platform teams on leveraging unified observability with AI to reduce MTTR, eliminate alert noise, and handle complex multi-cloud systems—with a 90-day implementation roadmap.
As LLMs treat code as just another sequence of tokens, the future of software engineering shifts from polyglot programming to specification-driven development. The compiler of tomorrow is a conversation between human intent and AI translation.
Learn how to architect goal-oriented, multi-agent AI systems capable of working together, reasoning, and aligning toward shared outcomes—with execution-ready engineering insights and operational considerations for technical leaders.
How GitHub Copilot Agents enable engineers to lead parallel AI workstreams like distributed teams, transforming the role from manager to technical conductor.
A ranked breakdown of the best AI coding agents for developers — from GitHub Copilot and Cursor to Cline, Roo, and beyond.
A deep dive into why today's AI coding tools excel at CRUD apps but fail at games, real-time audio, and complex UIs — and what the next generation must learn.
As AI becomes a first-class citizen in the development lifecycle, resilient CI/CD pipelines, safe deployments, and strong observability are essential to ensure reliability and trust.