Artificial Intelligence #llms#autonomous agents
Your Agent Has a Genome: New Framework Analyzes LLM Agent Behavior to Enable Runtime Governance
Researchers propose Base Sequence Analysis, a framework that encodes runtime behavior of LLM-powered autonomous agents into symbolic sequences (X, E, P, V). Analyzing 347 execution traces revealed key patterns: the trigram P-X-P lowered success rate by 10.4%, and verification transition E->V occurred only 2.1% of the time. They designed Governor, a three-layer runtime intervention system that increased task success by 6.2% and reduced token consumption by 44% in a production ReAct agent system.
Jun 16, 2026 1 source