Teaching Claude why
… Thus, after Claude 4, it was clear we needed to improve our safety training and, since then, we have made significant updates to our safety training. …
… Thus, after Claude 4, it was clear we needed to improve our safety training and, since then, we have made significant updates to our safety training. …
Announcements Australian government and Anthropic sign MOU for AI safety and research Mar 31, 2026 Today, Anthropic signed a Memorandum of Understanding with the Australian government to cooperate on AI safety research and support the goals of Australia’s National AI Plan. …
… A step forward on safety These intelligence gains do not come at the cost of safety. …
… We find that Opus 4.6 remains the strongest option for tasks that demand the deepest reasoning, such as codebase refactoring, coordinating multiple agents in a workflow, and problems where getting it just right is paramount. …
… A selection of our partners describe their experiences using Claude below: We were drawn to Anthropic's focus on AI safety and Claude's Constitutional AI approach to creating more helpful, harmless, and honest AI systems. …
… AI-native deal-making . PwC is reinventing how it executes deals end-to-end — diligence, value creation, integration — with agents working alongside deal teams. …
… Misaligned models sabotaging safety research is one of the risks we’re most concerned about—we predict that AI models will themselves perform a lot of AI safety research in the near future, and we want to be assured that the results are trustworthy. …
Policy Trustworthy agents in practice Apr 9, 2026 AI “agents” represent the latest major shift in how people and organizations are using AI. A couple of years ago, AI models were only broadly available as chatbots—simple question-and-answer machines. …
… Claude Opus 4.5 delivers measurable gains where it matters most : stronger results on our hardest evaluations and consistent performance through 30-minute autonomous coding sessions. Claude Opus 4.5 represents a breakthrough in self-improving AI agents . …
… Constantly iterating against a source of “ground truth” is usually crucial for scientific progress. In our AI safety research, empirical evidence about AI – though it mostly arises from computational experiments, i.e. AI training and evaluation – is the primary source of ground truth. …