Your coding assistant reports that every test passed. The build is green, so you merge the pull request and move on. Three weeks later, an issue arrives, but the agent isn't available to help. Perhaps your API quota is exhausted, or you are stuck on a commuter train with no signal. The code is yours now, and something is broken. Can you actually fix it?
That question is the core problem behind the CodeOwnership project. In practice, ownership means more than having your name on a commit. You only truly own code if you can trace its logic and patch it fully unaided. Passing tests show that software works on a good day, but they do not prove you understand it. This concerns maintenance only, not licensing or copyright.
The author built CodeOwnership, a lightweight pilot, to test this blind spot. An AI agent writes a feature, and the developer records an honest rating of how well they understand it. A second agent then introduces a single pre-registered bug. The developer opens an incident report with all AI tools turned off and tries to locate the defect.
The harness, which includes locked specifications, visible and hidden tests, a blind bug verification check, a guided CLI, and a report tool that avoids a single combined score, is complete. In the first trial, the author rated their confidence 4 out of 5, then stopped the timer at 8 minutes and 12 seconds without finding the bug. About 30 minutes in a later session, the bug was located, though the script still logged NOT FIXED because no fix had been applied.
This is one developer on one run, not an industry benchmark. It shows how the harness works, where it breaks down, and what a realistic test of code comprehension looks like.
Source: Towards Data Science · Summarized by HeadlinesBriefing