How much of BIRD is vibecoded#

Maria Matejka, BIRD | CZ.NIC

• Why: Not a talk the PM would search for, but one of the more honest datasets available on what LLMs can and cannot do in core network software — from the maintainers of a production routing daemon.
• What: The answer to "how much of BIRD is vibecoded" is essentially: none of the hard parts. LLM-generated lockless multithreaded C was "pathetic." Attempts to use AI for bug fixing failed ("most of our bugs need complex thinking"), as did texts about BIRD, release notes, slide generation, and RFC review.
• How: Beyond the failures, it catalogs the social pressures arriving via LLM: survivor bias (nobody posts their failures), confirmation bias ("the code should do what the commit declares"), "it works, just merge it" pressure, and the emerging phenomenon of LLM-fortified forks of real projects. The uncomfortable conclusion: BIRD's problem isn't AI — it's that their documentation "sucks or is outright wrong," their future intents aren't written anywhere, and background is scattered; that's bad for humans and LLMs alike.
• Where applicable: Anyone maintaining open-source network infrastructure, or thinking about where AI-assisted development can safely enter their toolchain. Read alongside "Brace for Upgrades" (same conference) for the flip side — LLM-equipped security researchers flooding projects with CVE reports (~5–8% validity rates).