AI Agent Artifacts Should Be Written Atomically, Even If the Run Is Not
中文摘要
为提升金融机器学习研究的可信度，AI智能体应采用原子化写入，通过临时文件、哈希及日志确保产物可靠。
English Summary
To enhance trust in financial ML research, AI agents should write artifacts atomically using temporary files, hashes, and event logs.
Original Excerpt
Why temporary files, atomic replacement, hashes, and event logs make financial ML research runs easier to trust. Continue reading on Medium »