This article discusses how to effectively utilize Large Language Models (LLMs) by acknowledging their superior processing capabilities and adapting prompting techniques. It emphasizes the importance of brevity, directness, and providing relevant context (through RAG and MCP servers) to maximize LLM performance. The article also highlights the need to treat LLM responses as drafts and use Socratic prompting for refinement, while acknowledging their potential for "hallucinations." It suggests formatting output expectations (JSON, Markdown) and utilizing role-playing to guide the LLM towards desired results. Ultimately, the author argues that LLMs, while not inherently "smarter" in a human sense, possess vast knowledge and can be incredibly powerful tools when approached strategically.
Comprehensive guide to prompt engineering techniques for Claude's
latest models, including Claude Opus 4.6, Claude Sonnet 4.6, and
Claude Haiku 4.5. It covers foundational techniques, output
control, tool use, thinking, and agentic systems.
latest models, including Claude Opus 4.6, Claude Sonnet 4.6, and
Claude Haiku 4.5. It covers foundational techniques, output
control, tool use, thinking, and agentic systems.
This article explains the concept of 'skills' in the context of language models, detailing how to create and use them to enhance model capabilities. It covers the file structure, YAML configuration, and integration of scripts for task automation, providing a practical guide for developers.
Anthropic is clashing with the Pentagon over the military's use of its AI systems, particularly regarding autonomous weaponry and mass surveillance. A key point of contention arose when the Pentagon asked if Claude could be used to help intercept a nuclear missile, a request Anthropic resisted, raising concerns about unrestricted AI use and potential risks. OpenAI is also signaling it would take a similar stance.
Examples for common OpenSandbox use cases. Each subdirectory contains runnable code and documentation. Integrations and sandboxes are available for various tools and services like AI models, desktop environments, and web scraping.
The use of AI tools in the attacks on Iran is collapsing the time required for military decision-making, raising fears that human oversight is being sidelined. The US military reportedly used Anthropic’s Claude AI model to shorten the 'kill chain' during almost 900 strikes on Iranian targets, including one that killed Ayatollah Ali Khamenei.
Anthropic has released a guide detailing “Skills,” a new method for customizing Claude by teaching it specific tasks through dedicated folders containing structured metadata in a single SKILL.md file. Skills enable consistent automation of workflows, enhancement of existing tools via accumulated expertise, and standardized document creation, functioning alongside MCP (which grants Claude tool access). The guide highlights five effective patterns – sequential orchestration, multi-tool coordination, iterative refinement, context-aware tool selection, and domain-specific intelligence – while cautioning against vague descriptions, overly complex skills, and lack of error handling. Ultimately, Skills aim to transform Claude from a general chatbot into a focused, integral part of daily work processes.
A "Clawdbot" in every row with 400 lines of Postgres SQL. An open-source Postgres extension that introduces a claw data type to instantiate an AI agent - either a simple LLM or an "OpenClaw" agent - as a Postgres column.
An article discussing Moltbook, a social network for AI agents built on top of OpenClaw, and the potential risks and benefits of this emerging technology.
LLM-powered Rust development assistant with meta-cognition framework.
