We’re All F*cked: A case study on algorithmic scaling

The duo behind We’re All F*cked shows how the future of distribution works. You no longer need to chase contracts when the algorithms chase them for you.

Their intention was not to create an AI band. It began as an experiment for growth and became a masterclass in modern marketing.

Suddenly We’re All F*cked appeared in Spotify playlists, Reddit-threads, TikTok feeds and Instagram Reels. No press photos. No interviews. No explanation.

Listeners speculated: Was this AI? A label stunt? A real band with no face? 

The tracks now have listeners in 172 countries, which means their “small experiment” is being measured on a global dataset, not just a niche corner of the internet.

Investornytt has the first in-depth interview after their reveal. 

This is exactly the kind of model that quietly outperforms businesses that still think about traditional campaigns. The investors who understand how these systems create growth are the ones who will price risk and opportunity correctly in the years ahead. That is why we are telling this story as a lens on the future, not just on music.

Behind the project are Dutch creators Erwin Cuijpers, a long-time ghost producer with millions of followers on motivational Instagram pages. And Chayen Wittmer, from Cloud Chief and Wyatt Creed, who has produced music for years while working full-time as a chef.

At first, the duo tried to help emerging artists break into streaming by pushing their songs through Cuijpers’ social media network. The idea was solid. The execution was harder. 

— People just did not show up. They did not finish tracks. Without finished songs, you cannot test anything, Cuijpers explains to Investornytt.

AI as the catalyst, not the vision

The breakthrough came when Cuijpers reluctantly tested the AI music tool Suno. He expected little, but what he heard shocked him.

— My first thought was holy shit, this sounds so real. If this is only the beginning, we are all fucked, he explains. 

That reaction ended up becoming the name of the project.

The real catalyst was that they leaned into the tool people fear the most. By using AI, they removed friction in production and put all their energy into distribution and data.

Suddenly they could create 30 to 50 variations of a song within minutes, instead of months. Still, they distance themselves from the idea that AI replaces creators.

— We are not proud of it. It feels almost too easy. If you create something in two minutes, you cannot take credit for it, Cuijpers says.

People were angry all over the internet when they realised the music was AI-generated. Yet the outrage accelerated growth. Mystery drives engagement, and algorithms reward that.

At the same time, 7.2 million streams were a fairly strong argument for not overreacting to the comments.

And the reaction from listeners makes sense when you look at the broader landscape. The pressure from AI on human creators is real, and it is growing fast.

The AI music market is expected to hit $6.2 billion by 2025 and grow to $38.7 billion by 2033. Human creators risk an income loss of around 24–28% by 2028 due to increasing competition from AI-generated music.  

Distribution beats budget

They began posting short Reels with the songs embedded. People started picking up and posted moments from daily life. 

Half of Instagram’s users watch videos with sound. If a clip hits emotionally, the jump to Spotify is a single click. From there, Spotify’s data systems take over.

The platform tested their tracks in small dynamic playlists. When listeners saved, repeated or completed the song, the system pushed it higher. A track that began with 1,500 daily streams quickly climbed to 15,000, and then into the millions.

All of it happened organically. 

In the interview, they describe Suno itself as “a living organism”. People are not just generating tracks, they are reacting to comments, iterating and building on each other’s ideas. 

— It is basically a new social media platform, Cuijpers explains. You can create your own song, and other people can create their own versions of it. 

A broken industry confronted by its own economics

As numbers rose, labels began reaching out. Several six-figure offers.

— On paper it looks good. But when you read the fine print, you are signing away your soul, Wittmer says.

Their story reveals a structural tension inside the music industry. Artists often receive advances that function as loans against their own future royalties, while labels retain ownership, catalog rights and large portions of revenue.

The Dutch duo flipped the dynamic. Instead of waiting for validation, they arrived with 1.5 million monthly listeners across their projects and a proven distribution model. The industry was no longer the gatekeeper. It became the applicant.

Human expression meets algorithmic scaling

Despite the role AI played in their rise, this was never about building an AI band. It was a test of what becomes possible when new tools remove old bottlenecks and force a conversation about where the line between human and machine actually sits.

Their next album, Man vs Machine, will move that line again. The songs will be brought to life by real musicians on real stages.

— AI should be used to empower humans, not replace them, Cuijpers emphasizes.

AI will identify what works. Humans will shape the sound, country by country. And new artists will gain exposure through the platform they have built.

The threat is not to musicians. The threat is outdated business structures.

Cuijpers’ first reaction to the AI output still captures the tension perfectly.

— If this is only the beginning, we are all fucked.

But the irony is that their project shows the opposite. Those who understand the tools, the platforms and the economics shaping the next decade are not “f*cked” at all. They are the ones positioned to shape the opportunities ahead.

And fittingly, their reveal came through a song. Confesión, the track where they finally stated their real mission.