I did not release the code but it's incredibly basic, and I believe OP's one is just the same.

You collect N links from HN api with any heuristic you want, then scrape those urls - preferably using pupeteer-based tooling or online equivalent (think Jina).

I then ran each url's content in an LLM to get a summary, then from all the results ask a LLM to create the conversation (and give it a tone). Then decide on the voices and characters and feed each turn into 11labs (or any tts). And finally, concatenate all audio parts, add music and effects.

If I remember correctly, mine could perform all that from a single Cloudflare worker. The catch is it can become a bit pricey because of the TTS. I remember toying with making it a product (podcast everything) and quickly discovered there's a couple of company already offering this.

NotebookLM is slightly different on the TTS front, I think they are using the amazing model google showed off a year or so ago (without giving it public access) that can generate actual multi speakers conversations with "hums" and cutting, and talking at the same time.

Added : someone just made a python lib for the usecase (also found on HN 5 days ago) https://github.com/souzatharsis/podcastfy