Unlike symbolic AI agents that rely on explicitly defined world models and search-based planning, LLM-based coding agents operate in a probabilistic, language-driven manner. Despite this difference, they increasingly exhibit behaviors aligned with classical definitions of agency, especially when augmented with memory, tool-use modules, and planning routines. At its core, an agent is an entity capable...