According to @AnthropicAI, Claude Code now supports direct connections to remote Managed Compute Platform (MCP) servers, allowing users to pull contextual data from their tools into Claude Code without any local setup required. This advancement streamlines AI workflow integration, enabling developers and enterprises to leverage cloud-based resources efficiently and securely. The update is expected to accelerate enterprise AI adoption by simplifying infrastructure requirements and reducing onboarding friction for teams looking to deploy AI-driven solutions at scale (source: @AnthropicAI, June 18, 2025).

According to Anthropic (@AnthropicAI) on Twitter, new features are now available for all Claude Code users as of June 18, 2025. These updates are designed to improve the AI-powered coding experience, offering advanced code generation, debugging, and integration capabilities. With these enhancements, businesses and developers gain more robust tools for automating software development tasks, increasing productivity, and streamlining workflows. This move positions Claude Code as a leading solution for enterprise AI coding platforms, highlighting opportunities for companies to leverage AI for faster and more reliable code deployment (source: AnthropicAI on Twitter, June 18, 2025).

According to Andrej Karpathy, the security risk is highest when running local LLM agents such as Cursor or Claude Code, as these models have direct access to local files and infrastructure, posing significant security and privacy challenges for AI-driven businesses (source: @karpathy, June 16, 2025). In contrast, interacting with LLMs via web platforms like ChatGPT generally presents lower risk unless advanced features such as Connectors are enabled, which can extend access or permissions. For AI industry leaders, this highlights the importance of implementing strict access controls, robust infrastructure monitoring, and secure connector management when deploying local AI agents for code generation, automation, or workflow integration. Addressing these risks is essential for organizations adopting generative AI tools in enterprise environments.

According to Anthropic's official communications on their developer blog, Anthropic teams utilize Claude Code to accelerate software development cycles, enhance code review processes, and streamline debugging tasks. Claude Code's large language model capabilities enable automated code generation, bug detection, and documentation summarization, which has led to measurable increases in developer productivity and cross-team collaboration. The integration of Claude Code has also allowed Anthropic to rapidly prototype AI solutions and maintain high code quality standards, demonstrating the practical business impact of advanced AI tools in enterprise software workflows (source: Anthropic Developer Blog, 2024-05-20).

According to @AnthropicAI, Claude Code has been officially integrated into the Pro plan, providing AI-powered coding assistance and automation tools for developers. This move expands access to advanced code generation, debugging, and code review capabilities powered by Claude's large language models. By bundling Claude Code within the Pro tier, Anthropic is positioning itself to compete more directly with other AI coding platforms like GitHub Copilot and Google Gemini Code Assist. This development is expected to enhance developer productivity and accelerate enterprise adoption of AI-driven software development workflows (source: @AnthropicAI, June 2024).