Description
At Anthropic, engineering centers on building AI systems that are reliable, interpretable, and steerable—especially through things like agents and tool integrations. Their team publishes about how they enable Claude (their AI model) to use tools well, optimize performance, and evaluate tools rigorously. They also talk about internal research efforts like scaling interpretability, making features behaving predictably, and improving developer workflows. Their engineering blog shows not just what they build, but how they think about safety, feedback loops, and tooling to support clean, robust, agent-based AI systems.
