The ecosystem of “AI skills” — modular instruction packs that extend an LLM with task-specific know-how, whether they’re called Skills, plugins, agents, MCP servers, system-prompt templates, or tool bundles — has exploded fast enough that “which one should I use?” has become the dominant question. The answer is rarely obvious from a README, and almost […]
Read More →“Keep It Simple” is old advice. It got interesting again the moment anyone could generate 500 lines of code in 30 seconds. KISS says systems and tasks should be as straightforward as possible. No unnecessary complexity. Fewer moving parts, fewer things to break, fewer things to hold in your head. It was good advice when […]
Read More →AI coding agents are fast, but they cut corners. Agent Skills is an open-source project by Addy Osmani that gives agents the same structured workflows senior engineers follow, from spec to ship. This post breaks down how it works, explains the Google engineering principles it builds on (Hyrum’s Law, Chesterton’s Fence, the Beyonce Rule, Shift […]
Read More →A viral Claude Code skill claims to cut 65% of output tokens by making LLMs talk like cavemen. Two research papers suggest forced brevity can actually improve accuracy in large models. But tokens are also compute — and nobody has benchmarked whether caveman-speak helps or hurts code quality. A look at the arguments on both […]
Read More →Most people blame Claude for strict limits. The blame is justified to an extent. Until Anthropic eases its usage limits, users are better off optimizing token usage. All you need to do is use tokens wisely, but not everyone knows how to do that and ends up losing a lot of tokens and money as […]
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