Agentic Capability Advances and Limitations Agentic capability is the idea that an AI system can do more than respond. It can pursue a goal through steps, use tools, recover from partial failure, and make choices about what to do next. The excitement is understandable. When a system can plan, browse internal knowledge, call APIs, write […]

Frontier Benchmarks and What They Truly Test Benchmarks are the public language of progress. They compress complex behavior into a score that can be compared, charted, and repeated. That compression is useful, but it is also dangerous. The moment a benchmark becomes a scoreboard, it attracts optimization pressure that can drift away from the capability […]

Uncertainty Estimation and Calibration in Modern AI Systems Modern AI systems can generate answers that read as confident even when they are wrong, incomplete, or out of distribution. That mismatch between apparent confidence and actual reliability is not a cosmetic issue. It determines whether a system can be trusted in production, whether humans will over-delegate […]