The Speed of Human Oversight
Why AI-Generated Development Remains Limited by Human Understanding
This post follows my standard early access schedule: paid subscribers today, free for everyone on March 10.
A few weeks ago, I published a post here about Moltbook, a social networking platform designed for AI agents to post, read, and coordinate tasks, and the security disaster that followed from building it without meaningful human oversight. Moltbook is a cautionary tale about what happens when AI generates faster than humans can verify.
In January 2026, something similar played out from the opposite direction: the team behind the open-source project curl, a ubiquitous data transfer tool that runs on billions of devices, permanently ended their bug bounty program. It was shut down because AI agents were submitting security reports faster than the curl maintainers could evaluate them. And, crucially, most of these security reports suffered from inherent flaws because the people overseeing the generating AI agents failed to provide adequate human oversight themselves.
One incident shows the cost of skipping human review during development; the other shows the cost of overwhelming it afterward. Together, these examples expose a clearer picture of where AI-assisted software development actually stands in 2026 and consequently offer a useful lens for thinking about the skills educators need to cultivate.
These two events did not occur in isolation. They are symptoms of a greater structural constraint that is coming into focus and that I think we have been slow to name clearly. I want to call it “The speed of human oversight.”
When human developers ignore security constraints
As I detailed in my earlier post, OpenClaw (previously Clawdbot, then Moltbot) was released in late 2025 as an open-source framework for giving AI agents expansive access to a user’s terminal, file systems, email, and execution environment. The project went viral. By January 2026, over 30,000 instances had been exposed to the open internet.
