Anthropic expands Mythos access to 150 new organizations; security experts warn of structural changes driven by frontier AI models and the risk of vulnerability chaining.
Long-horizon iterative improvement, not single high-quality responses, is the critical capability for autonomous AI agents tackling real-world engineering tasks.
Context Engineering is the discipline of systematically and at runtime filling the context window of language models with the right information in optimal form—far more comprehensive than prompt engineering.
Anthropic introduces a performance classification system for Claude integrators that measures demonstrated productive customers, certified personnel, and published case studies rather than abstracting on company size.
Uber caps AI-coding tool usage per employee and tool at $1,500 monthly, equivalent to approximately 11 percent of the average annual compensation for a software engineer.
Anthropic is opening its cyber-capable Mythos model to approximately 150 new organizations across more than 15 countries, including EU member states for the first time, with strict security requirements.
PaW trains environment models during policy training using the same RL rollouts, consistently improving agent performance without requiring additional simulators or inference costs.
