Creating Augmented Reality (AR) applications requires expertise in both design and implementation, posing significant barriers to entry for non-expert users. While existing methods reduce some of this burden, they often fall short in flexibility or usability for complex or varied use cases. To address this, we introduce agentAR, an AR authoring system that leverages a tool-augmented large language model (LLM)–based autonomous agent to support end-to-end, in-situ AR application creation from natural language input. Built on an application structure and tool library derived from state-of-the-art AR research, the agent autonomously creates AR applications from natural language dialogue. We demonstrate the effectiveness of agentAR through a case study of six AR applications and a user study with twelve participants, showing that it significantly reduces user effort while supporting the creation of diverse and functional AR experiences.
