What if the next leap in AI agents is not a smarter worker, but a better organisation?

This paper introduces OneManCompany, a framework that turns scattered agents, tools, skills, and runtime configurations into managed “Talents” that can be hired, reviewed, replaced, and improved over time. Its Explore-Execute-Review loop decomposes work, assigns accountability, checks outputs, and learns from failures.

The result is striking: 84.67% success on PRDBench, beating reported baselines by 15.48 percentage points. But the catch is equally important: this organisational intelligence costs more and is still mostly validated on software tasks.

Inspired by the work of Zhengxu Yu, Yu Fu, Zhiyuan He, Yuxuan Huang, Lee Ka Yiu, Meng Fang, Weilin Luo, and Jun Wang, this episode was created using Google’s NotebookLM. Read the original paper here: https://arxiv.org/abs/2604.22446v1