Agentic Context Engineering (ACE): Self-Bettering LLMs through Evolving Contexts, Not Tremendous-Tuning
TL;DR: A group of researchers from Stanford College, SambaNova Methods and UC Berkeley introduce ACE framework that improves LLM efficiency by modifying and rising the enter context as an alternative of updating mannequin weights. Context is handled as a residing “playbook” maintained by three roles—Generator, Reflector, Curator—with small delta objects merged incrementally to keep away … Read more