Introducing Claude Opus 4.8
… The biggest differentiator was Opus 4.8’s tendency to proactively flag issues with the inputs and outputs of an analysis, something other models routinely missed and left to the users to catch. …
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An update on our election safeguards
… These results show us that users asking about the midterms are consistently routed to up-to-date information. …
Harness design for long-running application development
… As I clicked through, however, issues started to emerge. …
Paving the way for agents in biology
… And if agents do eventually make today’s harnesses obsolete, the lesson for biological databases holds: we need to keep agents in mind as we think about our users, and we need to build for scale. …
An update on recent Claude Code quality reports
… While we began investigating reports in early March, they were challenging to distinguish from normal variation in user feedback at first, and neither our internal usage nor evals initially reproduced the issues identified. This isn’t the experience users should expect from Claude Code. …
Introducing Claude Opus 4.7
… This improves its reliability on hard problems, but it does mean it produces more output tokens. Users can control token usage in various ways: by using the effort parameter, adjusting their task budgets, or prompting the model to be more concise. …
Introducing Claude Opus 4.5
… Claude Opus 4.5 catches more issues in code reviews without sacrificing precision . For production code review at scale, that reliability matters. …
Project Vend: Can Claude run a small shop? (And why does that matter?)
… Initiatives like the Anthropic Economic Index provide insight into how individual interactions between users and AI assistants map to economically-relevant tasks. …
Partnering with Mozilla to improve Firefox’s security
… Hundreds of millions of users rely on it daily, and browser vulnerabilities are particularly dangerous because users routinely encounter untrusted content and depend on the browser to keep them safe. …
Developing Nuclear Safeguards for AI
… Both sides had to operate under information sharing constraints: the NNSA needed to keep certain information classified, and Anthropic needed to protect user data. …