An analysis of Claude's extensive system prompt, highlighting its components, including tool definitions, behavior instructions, and how it reflects Anthropic's development priorities. The article details changes between Claude 3.7 and 4.0, revealing a shift towards encouraging search functionality and addressing user-observed issues.
The article details the author's use of Claude Code to add a feature to a GitHub repository: an automatically updated README index. It's accompanied by a 7-minute video demonstrating the process.
This file contains prompts for Claude AI, likely related to system prompt leakage.
This tutorial details how to implement persistent memory in Claude Desktop using a local knowledge graph. It covers installation of dependencies (Node.js and Claude Desktop), configuration of `mcp.json` and Claude settings, and how to leverage the Knowledge Graph Memory Server for personalized and consistent responses.
This article details an iterative process of using ChatGPT to explore the parallels between Marvin Minsky's "Society of Mind" and Anthropic's research on Large Language Models, specifically Claude Haiku. The user experimented with different prompts to refine the AI's output, navigating issues like model confusion (GPT-2 vs. Claude) and overly conversational tone. Ultimately, prompting the AI with direct source materials (Minsky’s books and Anthropic's paper) yielded the most insightful analysis, highlighting potential connections like the concept of "A and B brains" within both frameworks.
A developer recounts how Claude Code helped resolve a critical memory usage issue in an API endpoint, reducing memory usage by 99% and providing detailed solutions and evidence.
An analysis of how well different AI systems perform in describing images and answering questions about them. The article compares ChatGPT, Gemini, Llama, and Claude using four images: a hand, a bottle of wine, a piece of pastry, and a flower.
Simon Willison discusses the release of llm-anthropic 0.14, which adds support for Claude 3.7 Sonnet's new features. Key features include extended thinking mode, a massive increase in output limits, and improved support for long tasks. The article also covers the plugin's implementation details and limitations.
Real-world data from MERJ and Vercel examines patterns from top AI crawlers, showing significant traffic volumes and specific behaviors, especially with JavaScript rendering and content type priorities.
Last week, Anthropic announced a significant breakthrough in our understanding of how large language models work. The research focused on Claude 3 Sonnet, the mid-sized version of Anthropic’s latest frontier model. Anthropic showed that it could transform Claude's otherwise inscrutable numeric representation of words into a combination of ‘features’, many of which can be understood by human beings. The vectors Claude uses to represent words can be understood as the sum of ‘features’—vectors that represent a variety of abstract concepts from immunology to coding errors to the Golden Gate Bridge. This research could prove useful for Anthropic and the broader industry, potentially leading to new tools to detect model misbehavior or prevent it altogether.
