In the five years since our comprehensive review of computational methods in legal analysis (Frankenreiter & Livermore 2020), the field has undergone a revolutionary transformation driven by the emergence of large language models (LLMs). What began as a promising but limited set of natural language processing tools has evolved into sophisticated systems capable of analyzing and generating legal texts with remarkable fluency and accuracy. GPT-3.5, which was released in 2022, demonstrated that neural language models could perform legal tasks ranging from contract analysis to bar exam questions. Subsequent models like GPT-4, Claude, and specialized legal LLMs have pushed these capabilities even further, achieving performance levels that often rival trained legal professionals.