mdwelsh

Hey HN, I’m excited to show off a project I have been building the last few months called Podverse — it automatically generates transcripts, summaries, and a chatbot from a podcast’s RSS feed, and makes it easy to embed AI features onto any website.

You can check it out at https://podverse.ai.

See it in action on an example podcast here: https://www.podverse.ai/podcast/omnibus

I’m a former engineer at Google and Apple, former CS prof at Harvard, and was a co-founder at Fixie.ai. I truly feel that LLMs are a revolution in our field, and I wanted to bring something to life that bridged between two deep interests of mine — AI and podcasts.

I’ve been listening a ton of podcasts lately, but it's frustrating to find relevant episodes, or even content that I had listened to previously. I also know that podcasters want to take advantage of the latest AI tech to connect with and expand their audience, but they're not usually equipped to bring all the pieces together. I wanted to build a complete, end-to-end solution for podcasters that is easy to use.

All you have to do is provide your RSS feed URL, and Podverse does the rest — automatically ingesting new episodes as you release them, generating transcripts and summaries, identifying speakers, and populating a custom chatbot that knows about all of the content of your podcast.

I built the site from scratch over the last few months (in my copious spare time!). It’s built entirely using Next.js deployed on Vercel — no backend servers beyond Vercel’s server components and API handlers. For running background tasks, like podcast ingestion and transcription, I used Inngest, which fills a big gap in the Next.js stack. Deepgram is used for ASR, which is fast, affordable, and very high quality. Supabase handles the storage, including the vector database (using pgvector). Auth is done with Clerk, which was super easy to integrate. Happy to answer any questions about the stack.

I’d love to get your feedback, and especially hear from podcasters to learn more about what features you’d like to see. Thanks!

The last couple of weeks, when using Google to search for technical content, I've often stumbled upon AI-generated blog posts from Restack.io, a startup building AI developer tools. These all seem to be AI generated, and, critically, often seem to be either technically incorrect or at least highly misleading.

The blog posts in question have nothing to do with Restack's own products. They seem to have generated thousands of blog posts on all kinds of technical topics. For example, searching for "Streamlit icons", I found this page:

https://www.restack.io/docs/streamlit-knowledge-streamlit-icon-list-guide

which confidently tells one to use the "st.icon()" function to add icons to your Streamlit app. Streamlit has no such API, and never has; this is completely hallucinated information that was clearly generated by an LLM.

Last week I sunk about an hour into getting a "solution" proposed by a Restack blog post working, only to discover that the approach it was describing simply does not work.

Here's a page that tells you how to deploy Streamlit on AWS Amplify:

https://www.restack.io/docs/streamlit-knowledge-streamlit-aws-amplify-integration

This page is totally bogus. Streamlit is a Python package, and Amplify requires a Node.js program. What it is describing is impossible. But the article is very confident in its tone and wording, making it look like an easy matter of running a few commands. Someone who did not understand this fundamental limitation of Amplify and Streamlit working together could sink a _lot_ of time into trying to debug why it was not working.

Shockingly, they seem to have thousands of these AI-generated blog posts on their site. Here is just the list of the first 100 (out of more than 500) articles about Streamlit that they have generated:

https://www.restack.io/docs/streamlit/kb-index/0

I find this appalling in large part because Restack is an AI company. They are clearly doing this to boost their SEO, but in so doing they are wasting the time of good people who have jobs to do and are used to relying on Google searches to surface useful, relevant content. Even worse, I fear this Restack garbage will end up in the next web crawl used to train future AI models, which will now, themselves, hallucinate back the garbage that Restack has fed them.

Restack, you can do better. Please take down your broken and misleading AI-generated blog posts.

Ironically, once Google catches on that the entire Restack.io site is spam, they will probably stop showing up in any Google searches. I hope the SEO was worth it while it's still live.