I gave the AI arms and legs then it rejected me

Automated Hiring and Missed Signals

• Many readers think the rejection was likely automated or came from an overwhelmed HR funnel, not the engineering team.
• Some see it as a “non‑story”: the role was probably already near closing and late applicants got bulk‑rejected.
• Others argue that, for a role explicitly using the applicant’s library, auto‑rejecting without human review is a clear hiring failure and bad signaling for an AI company.

Open Source, Exploitation, and Licensing

• Strong frustration that a multibillion‑dollar AI company can use a hobbyist’s MIT‑licensed library in a flagship product, yet not even grant an interview or token compensation.
• This is used as evidence that permissive licenses (MIT/BSD) mainly benefit large corporations; several commenters advocate GPL/AGPL or dual licensing (“GPL + commercial”) instead.
• Counterpoint: some developers genuinely want maximal freedom and adoption, even by corporations, and view MIT as “more free”; they accept that it may not bring money or jobs.
• Concern that even copyleft may be weakened by LLM‑assisted rewrites that “launder” code, though others note this is still legally murky.

Value of OSS Portfolios in Hiring

• Multiple anecdotes: maintainers of widely used tools (package managers, testing libs, infra services) still failing interviews or being filtered out.
• Several people argue that open source used to be a strong hiring signal, but post‑2019 it matters less than navigating HR funnels and internal referrals.
• Some hiring managers say high‑profile OSS, blogs, or founder experience can even hurt: teams may prefer “low‑profile” hires they can “shape” and who are less likely to leave or challenge norms.

HR, ATS, and Structural Problems

• Heavy criticism of HR/ATS practices: AI or keyword filters, junior screeners, and risk‑averse processes routinely discard strong candidates.
• Some HR professionals in the thread acknowledge that mis‑screening is common and that overloaded HR is often the least‑resourced function, even at AI firms.
• Others highlight legal and volume constraints: tens of thousands of applicants, fear of discrimination suits, and incentives to default to automated rejection.

Referrals and Coping Strategies

• Many insist the real mistake was not using the “friend of a friend” for a warm intro to the hiring manager; cold applications to hot AI companies are seen as near‑futile.
• Broader takeaway from commenters: don’t assume “I built what you use” will bypass the system; rely on networks, understand interview games, and don’t expect reciprocity for unpaid OSS work.