Persistent AI Agents in Academic Research: A Single-Investigator Implementation Case Study

ArXi:2605.26870v1 Announce Type: cross Background: Large language models are typically evaluated as models, benchmarks, or short conversational episodes. Less is known about what happens when an agent is embedded persistently in a real academic research environment with durable memory, local files, external tools, scheduled routines, delegated roles, and explicit safety protocols. Methods: A structured self-observed implementation was conducted from January 31 to May 25, 2026.