I listen to a lot of audiobooks, and there's no good way to know when an author you like has something new coming out. RecentAudiobook.com is the sister site to RecentMusic.com, built to scratch the same itch.
Follow the authors and narrators you listen to and you get an email when a new book comes out, another when a release date gets announced, and a weekly digest. No ads, no data selling, no algorithm deciding what you hear about.
The catalog is over 776,000 audiobooks across 140,000+ authors, 103,000+ narrators and 76,000+ series. Keeping that current takes a fleet of about 29 worker machines scanning around the clock... they peak at around 2,300 books an hour, so a full rescan takes about two weeks.
The public side is AstroJS again, just bigger. Every author, narrator, book, series, publisher and category gets its own page, about 1.2 million pages in all, rebuilt every 4 hours and swapped in atomically so nobody ever lands on a half-deployed site. The member side is a React app that picks up where the public site leaves off ( click Follow on any public page and it's completed after you sign up ). Members can bring their library in from Goodreads, a CSV or Excel file, or a pasted list instead of following authors one at a time.
It's also where I've been doing most of my AI work. Book categories are assigned by Jev from TypeSafe, a model that returns a probability for each question instead of generated text, so it can't invent a category that doesn't exist. Re-categorizing 4,030 books took 48 minutes and cost $0.90. The fallback is a self-hosted LLM ( Qwen3 on a Mac Mini ) with its output locked to a schema of valid categories. Every model choice was made from measured runs on real catalog data, not gut feel.