DOP 346: Fighting AI in Your Project Is a Terrible Mistake

#346: Drive-by PRs, AI slop, maintainers burning out – the open source world is having a meltdown and everyone wants to blame the robots. Viktor isn’t buying it.

The real problem started long before AI. Contributing to most open source projects has always depended on tribal knowledge and obscure docs nobody reads. AI didn’t break that. It exposed it. When contributions were trickling in, you could get away with onboarding people via vibes. Now that contributions are a firehose, you can’t.

Viktor’s take cuts in a direction that will annoy a lot of maintainers: your primary job is empowering contributors, not gatekeeping. And if a 20,000-line PR is drowning you, the answer isn’t to block everybody. The answer is to change the whole review cycle – because yesterday you were complaining about not enough contributions and today you’re complaining about too many. That’s a great problem to have. Solve it.

Here’s the part that will upset people. Viktor reframes what a developer’s job actually is. If you think your role is typing on a keyboard, you’re going to be disappointed. Your role is becoming a product manager. Asking the agent did you look at this, are you sure, what about that. Your job is no more. You just didn’t receive the memo.

There’s also a thread running through the episode about auditing. Can you actually assess the health of an open source dependency you depend on? Viktor dares Darin to audit Kubernetes. Or curl. Or anything. Humans can’t do it at all. AI can – imperfectly, but better than nothing. Which means the old enterprise model (pay Red Hat, they’ll handle it) starts to wobble when the value of someone else handling it drops because the tools can handle it for you.

And there’s a prediction. Right now when you ask AI to build something, it picks libraries based on training data. But what happens when the agent actually goes shopping – analyzing projects, reading docs, deciding which dependencies to pull in? That changes the open source landscape in a way nobody is ready for.

The episode ends somewhere quieter. Contributors, human or AI, should be cherished and trained over time. The hostility toward AI contributions is coming from maintainers who forgot that investing in new contributors is the job. The tools will make a mess. Then they will make less of a mess. Eventually we will be arguing about whether the feature should exist at all – not whether the code compiles.