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There is a popular assumption baked into many agentic AI systems: if an agent doesn't succeed on the first attempt, just let it try again. Give it more turns. Sample more trajectories. Add a reflection step. More compute at inference time should mean...

Last spring, a research team gave a large language model agent a list of real, unpatched web application vulnerabilities and a sandboxed environment in which to work. The model did not merely identify the flaws. It exploited them — autonomously, end-...

When working with coding agents — and I noticed something familiar (and frustrating). Whenever I started a new project and wrote a feature or design document, it quickly turned into a technical specification. I’d dive into class structures, APIs, and...

Large Language Models (LLMs) have already transformed how we interact with text—answering questions, generating content, translating languages, and simulating human dialogue. But human intelligence is not limited to language. We think in images, list...
