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 →Ask some reasoning models “What’s 2+3?” and they’ll chew through 900+ tokens before telling you “5.” That’s like hiring a consultant who writes a ten-page memo to confirm the sky is blue, then bills you by the page. This is the problem token-budget-aware reasoning solves. Here’s what it is, why it matters, and how to […]
Read More →A claim has been making the rounds in AI coding circles: stop prompting your coding agents and start designing loops that prompt them for you. Like most things, it gets repeated far more than it gets explained. This is the practical version — what an agent loop is, why it matters, and what one actually […]
Read More →Your agentic app just ran a search. The tool returned 500 results as JSON. Your agent appended all of it and fired off an API call — 45,000 tokens to answer a question that needed maybe 4,500. Tejas Manohar, a senior engineer at Netflix, hit this problem every day. He was running out of tokens […]
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