I just found about them on twitter and tested, its so crazy that it work so smooth and fast. It's probably powered by Claude Agent SDK in behind, I created a fully functional telegram bot under 3 minutes. It seems perfect for non-technical users.
Working on WordPecker, trying to create something like a personalized Duolingo but for vocabulary you actually encounter.
Started when I was struggling to read books in English. Pushed an open source version back then (https://github.com/baturyilmaz/wordpecker-app), later added more features, and now working on a mobile app.
My end goal is to build: an AI language learning companion that knows what you read, listen, and watch, knows you as a friend (real life, who you are), then helps you improve using that context. If you're B1 at language, it creates a personalized path to get you to B2, then C1, and so forth using your context.
The idea is simple, but I think it could be really cool: an autonomous agent that actually manages an entire radio station. It creates its own shows, play copyright-free tracks, shares the daily program schedule on social media and the website, and later I want to add guest appearances too and live 7/24.
I'm actually building this exact thing right now. Using Gemini TTS with its multi-speaker capabilities. Soundtrack comes from a Suno Playlist which the tool will download the entire playlist at the start.
Plays 3-5 songs prior to a "break", where the logic will call out channel donators vs pick a random topic to discuss, then use an LLM to generate the script before sending to gemini.
In the end; its really just a wrapper around FFMPEG broadcasting to an SRT or RTMP stream. I can upload the latest branch when I get home to share
that’s great to hear. I’d love to check out your project and have a chat if you’re up for it. maybe i can contribute to it instead of working on a separate project.
As bearish as I am on AI, outside of the agent deciding it only wants to play "Semi Charmed Life" and nothing else, I fail to see how this is a nightmarish hellscape in and of itself.
I feel standard commercial radio is already that hellscape. I mostly listen to rock (classic or alternative radio stations) and it's the same ~20 things being rinsed and repeated every hour and every day. Has been this way for decades.
I am pretty sure 90% of playlists you hear when out and about are generated by spotify algorithms at this point. I would more be concerned because it seems like a weird use for LLM when recommendation engines are probably better than it? I suppose it has a ton of training data around music forums and people recommending songs, but it is hard to believe that would beat out billions of hours of tracked listening spotify has access too.
Models are making capability leaps every few weeks but AI-native product innovation hasn’t kept up.
Most products are forcing AI into existing UX patterns rather than rethinking an AI-native experience from first principles. Parallels to early mobile (2007-2010) - for years, mobile meant shrinking your website into your phone until Uber reimagined transportation.
To be clear, there are lots of amazing AI-first products. See NotebookLM, Lovable, Stitch, Flow. But the pace of innovation on models has been faster, for a lot of reasons which I will explore in future posts."
