Why Open Source Doesn't Embrace AI
A week ago I would have told you the open source community rejected AI for four obvious reasons. Then I tried defending each one properly. Most of them collapse under scrutiny — and what’s left is a much more tractable conversation. The conventional answer Every maintainer I know has roughly the same three or four complaints about AI tooling. First, nobody can tell where the training data came from, which sits badly with a culture obsessed with provenance. Second, maintainers are drowning in AI-generated PRs and CVE reports — Daniel Stenberg’s posts on the curl side of this are now the canonical example. Third, AI shortcuts the old apprenticeship loop where contributors learned a codebase by earning review trust over months. And fourth, the power asymmetry: frontier models need hyperscaler capital, which sits uneasily inside a movement built on “you can read, modify, and redistribute the thing.” ...