Anthropic is rolling out Claude Cowork to mobile and web, letting agentic tasks run in the background across devices while decisions still route back to you. Here’s what changes and why it matters.
Deploy the Claude apps gateway on Google Cloud for centralized identity, policy enforcement, cost attribution, and spend limits across your Claude Code deployments.
Explore Claude Tag, Anthropic’s revolutionary Slack integration that brings AI directly into team collaboration. Learn how @Claude can handle code, data analysis, and async workflows—with real-world examples.
Stop guessing which LLMs will run on your machine. llmfit is an open-source terminal tool that detects your hardware and ranks hundreds of AI models by how well they’ll actually perform on your system — with scores for quality, speed, memory fit, and context length.
A coding assistant is an AI tool that helps developers write, understand, review, test, and maintain code. Far more than simple autocomplete, modern coding assistants can reason about entire codebases, explain complex logic, catch subtle bugs, and even autonomously execute multi-step engineering tasks. They are rapidly becoming an indispensable part of the modern developer’s workflow.
If you’ve been exploring Anthropic’s AI ecosystem, you may have come across both “Claude” and “Claude Code” — and wondered whether they’re the same thing. They’re not. Here’s a clear breakdown of what each one is, how they differ, and when to use which.
AI agents — software entities that can perceive environments, plan actions, and autonomously execute tasks — are a rising frontier in artificial intelligence. DeepLearning.AI has apparently launched (or announced) a series of 16 AI-agent courses, likely aiming to train practitioners in building, deploying, and scaling agents that can learn, reason, and interact.
Blog post highlighting all the cool but powerful new features that came along with the latest release of Gemini CLI.
Learn how to connect Kaggle with Vertex AI Workbench using Google Cloud Console. The blog post guides you through enabling the Vertex AI API and setting up the environment using a Jupyter Notebook. Follow along to set up your own connection for data science projects.