Blog

Lighthouse now scores sites for AI agents reading them, not just human visitors. Here is what the Agentic Browsing checks actually measure and how to pass them.

AI coding assistants stopped being autocomplete once they could read a codebase and plan multi-file changes. Here is what actually changed in how I work.

Local LLMs via Ollama trade raw capability for privacy, cost, and offline access. Here is how I actually decide between local and API-based models.

A practical filter for deciding what belongs in an n8n + Groq workflow versus what stays manual, based on the automations I have actually kept running.

AI writes implementations faster, but that raises the value of tests instead of lowering it. Here is the testing discipline I apply to AI-generated changes.

Vibe coding gets code running fast, but running and correct are different claims. Here's the gap I actually check before shipping AI-generated code.

What cubic-bezier() actually controls, why the built-in easing keywords look different from each other, and how to read or build your own custom curve.

How I decide between simple and scalable architecture early in a project — file-based content, CMS-ready layers, and when to actually add complexity.

Reusable n8n + Groq automation patterns — prompt chaining, structured output, and rate-limit handling — from workflows I actually run.