Agentic AI moves generative AI applications toward systems that coordinate reasoning, enterprise context, model inference, and external actions. Integrating these capabilities into enterprise software introduces diverse architectural concerns, from orchestration, knowledge and memory, and model access to tools and acti...
Ming-Qin Yu, F. Rabhi, Li-Ming Zhu et al.· 0 citations
Constraint-Driven Context Engineering (CDCE), a design approach for engineering domain interfaces for AI systems that identifies and characterises constraints, determines the required context assets, and designs representations through which these assets are made available to AI systems, is proposed.
Xi-Wei Xu, Chen Wang, Meng-Meng Yang et al.· 0 citations
A taxonomy focused on the architectures of foundation-model-based agents is introduced, addressing critical aspects such as functional capabilities and non-functional qualities and unifying and detailing these classifications to improve the design of foundation-model-based agents.
TRACE is presented, to the authors' knowledge the first agent watermark that is distortion-free in its action choices, self-synchronizing under deletion, and unconditionally invariant under rewriting, and it is proved this behavioral watermark's signal is bought with decision entropy.
