Auxefeed
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Follow taste. Not algorithms.

Auxefeed is where music taste becomes a track record. Blast tracks you believe in. Build your receipts. Get followed for being right.

What the feed looks like

N

noisefloor

@noisefloor

BLASTJan 14

Mirror

Mk.gee

This is what guitar music sounds like when it stops trying to be guitar music. Everything here is displaced just enough to feel genuinely alien.

V

velvetatlas

@velvetatlas

BLASTJan 12

Good Luck, Babe!

Chappell Roan

There are maybe five songs this decade that land like this. She called it and the rest of the world is just catching up.

D

deepcurrent

@deepcurrent

BLASTJan 10

Prom / Therapy

Olivia Rodrigo

She sounds like she means it more on this record than anything before. The production finally gets out of the way and lets the voice carry.

The gap

Real music. Real people. Direct connections.

AI-generated tracks are flooding Spotify playlists. The human behind the music is disappearing. The curators who spent years building taste are invisible. The artists who made something real are buried beneath algorithm-optimized content made by no one.

Auxefeed gives the power back. No agenda. No AI filler. Just a social network for music taste built around real curators, real artists, and direct connections between the people who make music worth hearing and the listeners who care.

How it works

Three things. That's it.

BLAST

The co-sign.

A curator or artist backs a track publicly. No algorithm. Just taste on the line.

RADAR

The early call.

Flag a release before it lands. When it delivers, the record shows you called it.

ISSUE

The direct line.

Subscribe to a curator or artist and their Issues arrive straight in your inbox. No feed, no filter.

Why now

The timing has never been better

The algorithm is winning. Listeners are losing. Human taste is the fix.

Discovery is broken

The average listener consumed 2,728 songs from 1,488 artists in 2025 — and spent just 4.2% of their time on their top artist.

Algorithms optimize for volume. Nothing sticks. Human co-signs create the stickiness that playlists can't.

"The average listener consumed 2,728 songs from 1,488 different artists over the course of 2025" — Reprtoir Industry Insights 2025-2026

Reprtoir 2025

More music than ever. Less of it means anything.

The algorithm is not your friend

Personalised algorithms risk trapping listeners in a bubble — narrowing taste over time instead of expanding it.

The more you listen, the more you get the same thing. Auxefeed breaks the loop — curators take risks, surface the unexpected, and post things before the data confirms they are safe.

"Personalised algorithms risk trapping listeners in an algorithmic bubble, making it harder to find community with fans." — MIDiA Research 2025

MIDiA Research 2025

An algorithm learns what you like and gives you more of it. A curator shows you what you didn't know you needed.

Human curation is having a moment

Listeners are actively shifting away from algorithmic discovery toward human-led recommendations — and the platforms winning are the ones that balance scale with taste.

The backlash is real and the data confirms it. Auxefeed is built for exactly this moment.

"There's been an increasing shift away from algorithmic discovery towards more traditional discovery methods." — Identity Music 2026

Identity Music 2026

The co-sign doesn't just reflect taste. It creates it.

AI flooded the supply. Trust became the product.

AI-generated music is projected to make up the majority of new uploads on streaming platforms by 2026.

When anyone can generate a song in seconds, the question stops being where do I find new music and starts being who do I trust to find it for me.

"As AI-generated content scales, authentic human-led discovery is the only filter listeners still trust." — Auxefeed Thesis

Auxefeed 2026

Auxefeed isn't competing with AI. It's the reason human curation still matters in a world where AI exists.

Discovery needs a home

Music discovery now happens across TikTok, group chats, YouTube, Substack, and live events — fragmented across dozens of platforms with no central home.

Auxefeed is that home. The place where discovery lives permanently, with a human voice behind it, separate from the platforms that produce it and the DSPs that play it.

"There is no longer one central place to find new music." — MIDiA Research 2025

MIDiA Research 2025

Every platform produces culture. None of them house it. Auxefeed does.

Streaming is infrastructure. Auxefeed is culture.

The algorithm

Not an algorithm. A network.

Spotify's algorithm looks at what you've played and predicts what you'll play next. It's a mirror — your taste in, your taste out, slightly optimized. It can't show you something genuinely new because it's built around what you already know you like.

Auxefeed works differently. When you open the feed, what you see is shaped by the people you follow — not a machine learning model. If three curators you trust all co-signed the same track this week, it rises. If someone you follow Reblasted something from a curator you've never heard of, it surfaces. The signal is human. The network moves the music.

The further a track travels through real taste connections — Blasted, Reblasted, co-signed by curators whose followers trust them — the stronger its signal. Being early in a chain that goes wide means something here. Your feed reflects the taste of people you chose to trust, not an engagement metric optimized for time on screen.

Who it's for

Built for three people.

The listener.

Tired of AI-generated tracks clogging your playlists? Discover music through real people with real taste. Follow the ones worth following and hear from them directly.

The curator.

You've always driven discovery. Now you get the credit. Build a following on Auxefeed — your taste is public, your record is permanent, your fans are yours directly.

The artist.

Your fans hear from you when you drop something. Not because an algorithm decided to surface it. Because they followed you and your message arrives directly.

Your taste.
On the record.

Join the network.

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