

CLAUDE.md is the instruction manual located in the project's root directory, which reduces redundant explanations and enables more stable and controllable AI programming.


This article compares two AI projects, OpenClaw and Hermes Agent. The former emphasizes user control and adaptability, while the latter focuses on automation and efficiency. At their core, the competition between the two reflects a fundamental question: will AI agents evolve into programmable personal operating systems, or become self-evolving work agents?


What truly determines content quality are the other three factors.


The XChat, touted as the "Western WeChat," has finally made its debut. Marketed as "encrypted communication," how does XChat truly perform?


This article is a hands-on guide to GPT Images 2.0, introducing its core functionalities, summarizing universal prompt structures and workflows, including role anchoring, editing protocols, and quality tiering techniques, enabling users to systematically produce high-quality images.


An API intermediary hub exploits the global price disparities and access barriers of AI services, operating a arbitrage model by acquiring overseas AI Tokens at low cost and reselling them to domestic users, yet it carries risks such as data breaches and model misalignment.


AI Agents can serve as an independent and secure layer for DeFi investors, assessing protocol risks through publicly available data.


For ordinary users, the most direct changes are increased compliance with instructions, better image understanding, and outputs that are closer to final products—while also noting that tokens will be consumed more rapidly.


The value of this content lies not in a barrage of flashy prompt keywords, but in sharing a set of high-frequency, production-grade Prompts refined over six months. Covering scenarios such as writing, distribution, meetings, decision-making, pricing, collaboration, and post-mortems, these Prompts precisely address the most time-consuming daily tasks for knowledge workers, minimizing repetitive effort and reducing trial-and-error costs, transforming ambiguous tasks into structured, actionable outputs.


AI-powered financial markets enable retail investors to leverage AI-driven automated trading strategies, achieving technological parity and lowering investment barriers.

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