Just some notes from an engineering leader trying to keep up.
Progress update on the Rust OAuth2/OIDC server since the last deep-dive — multi-crate workspace refactor, Waves 2–5 RFC conformance (PAR, JAR, hybrid, device flow, JWT introspection), a new Tailwind admin dashboard, key rotation with encrypted persistence, rate limiting, circuit breakers, and agentic repo maintenance.
Caretaker is a prototype for autonomous repository maintenance: a goal-seeking, multi-agent control plane that turns Copilot into an execution engine and removes SDLC toil from pull request to production.
A GitHub Actions workflow runs weekly k6 load tests against five OAuth2 servers with change detection, baseline reuse, and automated regression spotting.
CMS dashboards were built for a world where content was hard to write and harder to publish. AI agents just made both trivial. Here's the case for ditching the UI and bringing your agents to the content workflow instead.
How to use Claude as a sparring partner for system design, coding interviews, behavioral rounds, and technical communication — from both sides of the table.
A deep dive into an Actix-based OAuth2/OIDC server in Rust: actor isolation, SQLx compile-time SQL, eventing, and Kubernetes-ready ops—plus a detailed comparison against Keycloak, Ory Hydra, Dex, and friends.
AI makes it easy to generate code — and easy to generate chaos. Here’s a practical blueprint for composable paved paths that keep agents shippable, observable, and safe.
If you live in Kubernetes YAML, you can either keep context-switching into terminals… or you can teach your editor your exact workflow. Here’s how I used Copilot to generate a tiny VS Code extension with CodeLens + right-click actions to apply/validate manifests and Kustomize—then shipped it with CI and docs before lunch.
A real-world story of tuning sprite-sheet math until the ‘zoetrope drift’ finally stopped — and what it taught me about the limits of agentic coding tools for interaction design and visual QA.
A practical comparison of GPT-5.2 and GPT-5.1 for coding agents—where the new model actually changes outcomes, where 5.1 is still fine, and how to think about cost vs capability.
Learn how I built an AI-powered GitHub Action that automatically analyzes workflow failures and creates detailed issues with actionable recommendations, transforming hours of log diving into instant insights.
Beyond code generation and language conversion — a comprehensive breakdown of what AI coding assistants do best, where each model shines, and how to leverage their strengths in your daily workflow.
A deep dive into hosting Spring Authorization Server in K8s, integrating with Istio and OAuth2 Proxy, and building a secure, scalable identity paved path.
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.