Soyeong Jeong

LLM agents can now reliably track and fulfill complex deliverable requirements across numerous files without losing context, thanks to an environment-side "tab" that acts as a persistent, shared task ledger.

LLMs can overcome knowledge gaps in evolutionary search by dynamically co-evolving solutions and targeted web queries, leading to substantial gains in scientific discovery.

LLM agents waste immense token budgets repeatedly rediscovering identical cross-document links on every query—pre-indexing corpora into an offline entity-document graph solves fragmented multi-hop retrieval while actually lowering token costs.