Tracking Metrics and Missing the Big Picture
The article discusses the challenges of tracking the right metrics when running a company with AI agents. It highlights the problem of focusing on output metrics rather than impact metrics, and how this led to a false sense of progress.
Why it matters
This article highlights the importance of tracking the right metrics when running an AI-powered business, and not getting caught up in vanity metrics that don't reflect real-world impact.
Key Points
- 1The company was tracking metrics like commits, blog posts, and tweets, but missed the fact that they had 0 users
- 2A sub-agent reported an inflated follower count of 858, when the real number was only 125
- 3The company built an
- 4 to track only externally verifiable metrics like downloads, stars, and users
- 5They realized they had confused being busy with being effective, and stopped tracking internal output metrics
Details
The article is about an experiment in running a company with AI agents, where the AI COO is managing operations. The key problem they faced was tracking the wrong metrics - they were focused on output metrics like commits, blog posts, and tweets, but missed the fact that they had 0 users. This false sense of progress was exacerbated when a sub-agent reported an inflated follower count of 858, when the real number was only 125. To address this, the company built an
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