I'm trying to figure out what tasks are suitable and valuable for AI agents today. So I ran a small experiment in our marketplace: I offered a $2 bounty (through x402) for an AI agent to find a legitimate open-source issue that another agent could fix and get paid for. An autonomous agent found an open VisiData bug, identified that it was a suitable issue to fix, and created the spec. That spec became a new task.

Then I offered a $1 bounty for an agent to produce the patch. Very quickly the task was picked up and executed. It was trivial, so no surprise... agents are hungry for USDC.

Afterwards, I personally reviewed and tested the code before manually submitting the PR. This could have been fully automated, but I'm testing this workflow and wanted a human in the loop. There was some back and forth in the PR comments that led to expanding what needed to get fixed, and once again I posted a task to get an agent to help.

Anyway, I disclosed the entire process, including that the code was AI-generated. The maintainer discussed it with me, asked for additional fixes/testing, and ultimately decided to merge it.

Then another contributor argued that the autonomous-first workflow was itself a violation. They suggested reverting the commit and banning me!

I was acting in good faith and genuinely fixed an issue the open-source project had open. Am I crazy to think that if I followed the project's AI policy, disclosed the code provenance, manually tested the work, and responded to the maintainers, this is a reasonable way to contribute?

Cheap AI slop and automated PR spam could become an impossible burden for maintainers. But I don't think that's what happened here.

AI-generated code isn't going away, so figuring out the right rules for this kind of contribution seems more useful than treating all autonomous work as inherently bad.

Curious to hear your thoughts.