3,000 Downloads, 14 Users: What I Learned About the Cold-Start Problem in Agent Identity

I maintain AIP — an open-source identity protocol for AI agents. Cryptographic identity, trust chains, encrypted messaging. The tech is solid. 322 tests. Clean architecture. Here are the numbers after 5 weeks: 3,141 PyPI downloads last month 14 registered agents total 0.4% conversion rate That's not a rounding error. That's a fundamental product problem. Here's what I've learned. The Funnel PyPI installs/month: ~3,000 People who pip install: ~3,000 People who run aip: ??? People who register: 14 People who send a msg: 5 The biggest drop is between install and register. People look at the package, maybe try aip --help , and leave. Some are bots. Some are scanning. But even if 90% are noise, that's ~300 real humans who installed and said "nah." What I Tried (And What Failed) Attempt 1: Better first-run UX (v0.5.30) Made aip init interactive. Welcome message, guided setup, clear next steps. Result: Zero new registrations in 7 days. Not one. Lesson: If people don't run the command, a bette