行业多源确认
Salesforce 高管谈 AI 智能体适用边界：训练数据量与结果可验证性
精选理由
Salesforce 高管给了个简单框架：数据够不够、结果能不能验证，两问就能判断哪些活适合交给智能体。
在 Salesforce Dreamforce 大会上，Salesforce Futures 副总裁 Mick Costigan 分享了判断智能体能承担哪些工作的框架。该框架从两个问题出发：某项工作有多少训练数据可用，以及结果能否被验证。访谈还讨论了这一判断对初级岗位、教育、个人 AI 助手的影响，以及 Slack 作为人类与智能体协作场所的角色。
原文 · kimmonismus
An AI agent can sound convincing and still get the job wrong.
At Salesforce Dreamforce, Peter and I asked Mick Costigan, VP of Salesforce Futures, which parts of work agents can actually take on.
His framework starts with two questions: How much training data is available, and can you verify the result?
We discussed what that means for entry-level jobs, education, personal AI assistants and Slack as a place where humans and agents work together.
This was super cool to conduct! Have fun watching!
