Rethinking Open Source Contribution in the Age of AI Agents

Open source projects are seeing a surge of AI-generated pull requests, and vLLM, the inference engine behind much of today's production LLM traffic, is no exception. The cost of producing a plausible-looking PR has collapsed, while the cost of reviewing one has not. This has changed what maintainers do every day, and it has changed what it takes for a new contributor to actually contribute something of value. This talk shares a core maintainer's view on what is happening to OSS contribution patterns, with concrete examples from vLLM: PRs that look correct but miss the design intent, and fixes that paper over deeper issues. It is not a talk against AI - agents are now part of how vLLM gets built. The argument is that a human contributor's leverage has shifted away from producing code and toward understanding systems, picking the right problems, and owning what ships to production. We will close with practical thoughts on how new contributors can stand out, and what maintainers of critical infrastructure should be doing differently.