A Seek HiFi Guide to using AI to quickly turn a noisy multi-threaded music conversation into a Tidal, Spotify, or Apple Music playlist for free.

As far as I'm concerned, AI-generated music can get in the bin. But I do often use AI tools to help me discover (or rediscover) music. This is how. Here is an exact workflow I use to turn a sprawling Reddit comment thread into a finished playlist in Tidal, Spotify, or Apple Music.

Reddit is one of the best places in the world for music discovery: chaotic, passionate, unfiltered, and full of deep-cut obsessives. But taking a messy thread of song recommendations and turning it into a clean, curated playlist? That’s a lot of work.

But this will take about five minutes.

At the end we'll have turned a 100+ comment Reddit thread into an 96 track playlist, sorted by sentiment, on our chosen platform. Then we can kick back, dig through it at our leisure, and find some gems.

01: Start with a Reddit Thread Worth Listening To

For this example, I grabbed a post from r/MusicSuggestions: “Underrated songs that absolutely blew your mind.”

This is great, but it's a mess.

02: Feed the Thread to ChatGPT

Rather than manually parsing comments, I literally copy-pasted the entire web page into ChatGPT and then I prompted it:

“Make me a list of songs from this thread, in order of most positive sentiment to least.”

In about 10 seconds, ChatGPT:

• Extracted every track
• Separated songs from albums
• Removed conversations, tangents, and jokes
• Deduplicated repeats
• Fixed formatting
• Interpreted sentiment from all comments and replies
• Returned them in ranked order from “life-changing” to “solid pick” according to the hive mind

This is the part that feels like cheating. Before I had chaos, now I have a data set.

03: Clarify Album Handling

Redditors love to recommend entire albums. That's no good for my playlist. ChatGPT was smart enough to ask me how to handle albums and it gave me three options.

1. Include all tracks from the album.
2. Include only the first track from the album.
3. Include what is normally considered "the standout track" from the album.

I chose option 2 and ChatGPT built the list accordingly.

04: Get the Data Ready for Import

Prompt:

“Turn this into a playlist with only songs, no duplicates, no albums.”

ChatGPT output a pristine, import-ready list in this exact format:

Artist – Song
Artist – Song
Artist – Song

This is the universal format that most music import tools understand.

05: Generate a .TXT File

To finish the workflow, I simply asked:

“Give me this as a downloadable .txt file.”

ChatGPT created a file I could download. Now we're ready for TIDAL, Spotify, or Apple Music conversion.

I cannot overstate how useful this part is. In fact formatting data sets from one thing to another, particularly a messy data set, is a task for which I find AI tools very useful.

06: Importing Into a Streaming Service

Use TuneMyMusic. It works with Tidal, Apple Music, and Spotify and it's free unless you're importing over 500 tracks. Our Data set is 96 tracks, so this is perfect. (In fact, the "Tidal Import Tool" just redirects you to this service.)

Note: You'll have to be logged into your music service in the browser for this to work.

1. Upload or paste the .txt file
2. Select your destination
3. Confirm matches
4. Make any tweaks to the title or description of your soon-to-be playlist
5. Create playlist

Some tips:

• Tidal generally has excellent metadata matching, especially for deep cuts and long tracks.
• Apple is very good at finding “obscure but high-quality” versions of tracks.
  If something fails, it usually means it’s missing from the catalog entirely.
• Spotify sometimes defaults to compilation albums. Double-check the matches.

Boom! The End Result

A playlist of 89 underrated (not sure anything by Pink Floyd is underrated) tracks of (ostensibly) mind-blowing quality sorted by the sentiment of the Reddit jackals. We have everything from Sturgill Simpson and Pink Floyd epics to Japanese metal and folk heartbreakers.

This workflow turns:

• Reddit chaos > structure
• comments > tracks
• albums > single-song stand-ins
• random enthusiasm > ranked curation
• text > a playlist you can listen to now

My reservations about the quality of the selections will soon be proven right or wrong; most likely a little of both. But the point is humans made the music, the hive mind did the curation, AI handled the grunt work, and I can do the listening.