I write about the stuff that actually breaks at 2 AM: Kubernetes pods stuck in CrashLoopBackOff, Terraform state files that drifted into chaos, CI pipelines that pass locally and die in staging. If you run infrastructure for a living, you will recognize the problems.
You will also find posts about building AI products -- not the hype-cycle kind, but the practical side. Shipping features that use LLMs without burning through your API budget, choosing the right model for the job, and keeping latency under control when your users actually need real-time responses.
Every article comes from something I actually shipped or debugged. No theoretical hot takes, no ragebait. Just the problem, the context, and the fix. If you want tools to go with the reading, check out the free developer tools for AI workflows.
Claude Code & LLM tooling -- building developer tools on top of large language models, prompt engineering that works in production, and keeping AI costs under control.
DevOps & cloud infrastructure -- Kubernetes, Terraform, CI/CD pipelines, and the operational side of keeping services running at scale.
Developer productivity -- terminal workflows, editor setups, automation scripts, and small process changes that compound over time.
AI workflows -- practical patterns for integrating AI into real products, from retrieval-augmented generation to agent orchestration.