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 →The Wiggle Framework is an evaluation method introduced in Meta’s research paper, “Jagged Judges: Epistemic Stability Under Perturbation.” It is designed to test how easily large language model (LLM) judges abandon their original verdicts when challenged. Why this matters Traditional LLM evaluation often measures a judge’s accuracy once against a fixed gold-standard dataset. That tells us how […]
Read More →Would you let a brand-new employee wire $50,000 on their first day without anyone checking? Probably not. You’d train them, watch their work, and hand over more responsibility as they earned it. AI deserves the same treatment. That’s the idea behind Human-in-the-Loop (HITL). Table of Contents What Is Human-in-the-Loop? Human-in-the-Loop is a way of building […]
Read More →On June 9, 2026, Anthropic released Claude Fable 5, their most capable model available to the general public. Three days later, the US government ordered them to shut it off. No geographic carve-out. No targeted users. Everyone. What happened in those 72 hours is as revealing as anything we’ve seen in frontier AI deployment: a […]
Read More →Large language models are increasingly extensible. Whether they’re called “skills,” “plugins,” “tools,” or “MCP servers,” the core idea is the same: let an LLM invoke external code, read external data, and act on external instructions. It’s also one of the most serious attack surfaces in modern AI systems. Table Of Contents What’s the problem? Prompt […]
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