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Anthropic rss
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| <rss version="2.0"> | |
| <channel> | |
| <title>Claude 相关文章</title> | |
| <link>https://www.anthropic.com/engineering</link> | |
| <description>RSS Feed generated by AI</description> | |
| <item> | |
| <title>Claude for Engineering</title> | |
| <link>https://support.anthropic.com/en/articles/9945689-claude-for-engineering</link> | |
| <description>In this video guide, we'll explore several examples of how Claude can be used by engineering teams. Before you get started, review the availability of the features demonstrated in this video: Artifacts are available on all Claude.ai plans.</description> | |
| <pubDate>Thu, 28 Nov 2025 00:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>Introducing Claude 4</title> | |
| <link>https://www.anthropic.com/news/claude-4</link> | |
| <description>These models advance our customers' AI strategies across the board: Opus 4 pushes boundaries in coding, research, writing, and scientific discovery, while Sonnet 4 brings frontier performance to everyday use cases as an instant upgrade from Sonnet 3.7. Claude 4 models lead on SWE-bench Verified, a benchmark for performance on real software engineering tasks.</description> | |
| <pubDate>Tue, 22 May 2025 00:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>How enterprises are driving AI transformation with Claude</title> | |
| <link>https://www.anthropic.com/news/driving-ai-transformation-with-claude</link> | |
| <description>The company is now pioneering an AI post-processing system in CI/CD that automatically improves variable names, adds comments, and generates unit tests. "Anthropic prioritized safety and security a lot more than other LLMs," said Gunjan Patel, ...</description> | |
| <pubDate>Thu, 30 Oct 2025 17:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>Claude Code on the web</title> | |
| <link>https://www.anthropic.com/news/claude-code-on-the-web</link> | |
| <description>Today, we're introducing Claude Code on the web, a new way to delegate coding tasks directly from your browser. Now in beta as a research preview, you can assign multiple coding tasks to Claude that run on Anthropic-managed cloud infrastructure, ...</description> | |
| <pubDate>Tue, 11 Nov 2025 16:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>Effective context engineering for AI agents</title> | |
| <link>https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents</link> | |
| <description>Get started with context engineering in the Claude Developer Platform today, and access helpful tips and best practices via our memory and context management cookbook. Written by Anthropic's Applied AI team: Prithvi Rajasekaran, Ethan Dixon, Carly Ryan, and Jeremy Hadfield, with contributions from team members Rafi Ayub, Hannah Moran, Cal Rueb, and Connor Jennings.</description> | |
| <pubDate>Thu, 04 Dec 2025 00:00:00 GMT</pubDate> | |
| <author>Prithvi Rajasekaran, Ethan Dixon, Carly Ryan, Jeremy Hadfield</author> | |
| </item> | |
| <item> | |
| <title>Claude Skills: Customize AI for your workflows</title> | |
| <link>https://www.anthropic.com/news/skills</link> | |
| <description>Claude can now use Skills to improve how it performs specific tasks. Skills are folders that include instructions, scripts, and resources that Claude can load when needed. Claude will only access a skill when it's relevant to the task at hand.</description> | |
| <pubDate>Mon, 10 Nov 2025 16:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>How AI Is Transforming Work at Anthropic</title> | |
| <link>https://www.anthropic.com/research/how-ai-is-transforming-work-at-anthropic</link> | |
| <description>Despite this, we felt it was on balance useful to research and publish these findings, because what’s happening inside Anthropic for engineers may still be an instructive harbinger of broader societal transformation. Our findings imply some challenges and considerations that may warrant early attention across sectors (though see the Limitations section in the Appendix for caveats). At the time this data was collected, Claude Sonnet 4 and Claude Opus 4 were the most capable models available, and capabilities have continued to advance.</description> | |
| <pubDate>Thu, 04 Dec 2025 00:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| <item> | |
| <title>Estimating AI productivity gains from Claude conversations</title> | |
| <link>https://www.anthropic.com/research/estimating-productivity-gains</link> | |
| <description>For example, software engineers see large estimated time savings in developing and debugging software, but not in supervising programmers. Weekly time fractions are estimated by Claude (see previous section). Our approach has several limitations that we think warrant further research on this topic: Claude’s predictions are imperfect and we lack real-world validation of Claude’s time estimates: AI systems are imperfect predictors, and can’t see activity that happens after the user finishes their interaction with the model.</description> | |
| <pubDate>Mon, 25 Nov 2025 00:00:00 GMT</pubDate> | |
| <author>Anthropic</author> | |
| </item> | |
| </channel> | |
| </rss> |
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