Every chat with Claude starts with a hidden briefing. Anthropic publishes it. Here’s what’s in it, why it exists, and how it grew roughly 40x in just over two years. Table of Contents TL;DR What is a system prompt? Picture Claude as a brilliant new hire who has read most of the internet, then got […]
Read More →Imagine hiring a brilliant assistant, handing them a 200-page manual, and asking a question. They read all 200 pages, answer, and then promptly forget everything. Next question? They read all 200 pages again. And you pay them by the page. That’s roughly how large language models (LLMs) work by default. Prompt caching is the fix. […]
Read More →This post draws on research across blogs, videos, and company profiles in the AI native space. What follows is my commentary on the patterns I kept seeing — the framework, the workflows, and the thinking that separates organizations genuinely operating this way from those just using AI tools. Being “AI native” isn’t just about using […]
Read More →You installed a skill. The README looks fine. The demo in the docs worked on the first try. Should you keep it? You can’t tell from the README. You have to run the skill on your own work and look at what comes out. This post walks through doing that. We start with the simplest […]
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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