Tag: 开发流程 (3 articles)

AI evaluation costs are skyrocketing, with single agent benchmark runs costing tens of thousands of dollars, and their inherent complexity makes them hard to compress, creating a new compute bottleneck for AI development.

LangChain argues that building reliable AI agents requires systematically integrating domain experts' tacit knowledge and judgment throughout the development lifecycle, rather than relying solely on the model's own capabilities.

LangChain proposes a 6-point checklist before building agent evaluations, emphasizing manual analysis of 20-50 real failure traces before automating tests.