The underground sounds reshaping pop: from hyperpop's collapse to AI's creative paradox
If you've been listening closely, you can hear the foundations of popular music cracking. Not with the dramatic crash of collapsing stadiums, but with the subtle, persistent creak of shifting tectonic plates deep beneath the mainstream surface. While the charts recycle familiar formulas, a parallel musical universe is undergoing its own quiet revolution—one that questions everything from genre boundaries to the very nature of artistic creation.
Over at Pitchfork, the conversation has moved beyond simply cataloging micro-genres to examining what happens when those genres implode. Hyperpop, that brief, glorious explosion of sugary distortion and emotional maximalism, has fragmented. Its pioneers have scattered, some retreating to more traditional pop structures, others diving deeper into abrasive, experimental electronic noise. The scene's center could not hold, but from its disintegration, something more interesting has emerged: a post-hyperpop landscape where the only rule is that there are no rules. Artists like underscores and Jane Remover aren't just making music; they're conducting salvage operations on the wreckage of a movement, building new forms from the shattered pieces of identity, nostalgia, and digital overload.
This fragmentation mirrors a broader cultural splintering discussed on Stereogum and The Fader. The monoculture is dead, buried under the algorithmic weight of infinite choice. There is no single "underground" anymore, but a thousand tiny, thriving ecosystems. In one corner, artists are reviving the raw, tape-hiss intimacy of early 2000s indie folk, a direct reaction to the sterile perfection of streaming-era production. In another, collectives are forging new strains of global club music, weaving together dembow rhythms, UK drill, and Afrobeats into dizzying, borderless hybrids. The audience isn't just listening; they're curating, participating in niche Discord servers, and championing sounds that will never touch the Hot 100. Success is no longer defined by platinum plaques, but by the intensity of a dedicated community.
Meanwhile, Consequence and NME are tracking the industry's awkward, billion-dollar tango with artificial intelligence. The headlines swing wildly between utopian promise and dystopian panic. One week, a startup promises AI tools that will help musicians overcome writer's block. The next, a viral "new" track by a long-dead artist sparks protests from estates and unions. The real story isn't in the hype or the fear, but in the messy middle where artists are actually using the technology. Producers are employing AI stems to brainstorm unusual textures. Songwriters are using large language models as high-tech parlor games, feeding them bizarre prompts to break out of creative ruts. The threat isn't that AI will replace artists, but that it will further inundate an already oversaturated market, making discovery even harder for human creators. The tool is here; the ethical and economic framework is not.
Beneath all this lies the engine of discovery itself, a topic Hypebot dissects with clinical precision. Playlists are no longer just mixtapes; they are the new radio, the new A&R, the new gatekeeper. But the gatekeeper is a black box. The algorithms that power Spotify's "Discover Weekly" or TikTok's sound trends are opaque, optimizing not for artistic merit, but for engagement and retention. This has created a new kind of sound: the "algorithmic native" track, engineered with crisp, immediate vocals, a drop before the 30-second mark, and a hook designed to survive being played on a phone speaker. It's a creative constraint that some chafe against and others have learned to master, writing songs that are as much data sets as they are emotional expressions.
What ties these threads together—the genre collapse, the niche communities, the AI anxiety, the algorithmic pressure—is a collective renegotiation of authenticity. In a world where a sound can be synthesized, a career can be built entirely online, and a genre can be born and die in a Twitter thread, what does it mean to be "real"? The answer is being written not in press releases, but in the work of artists who embrace the contradiction. They use AI to explore human loneliness. They craft music for algorithms while embedding deeply personal lyrics within it. They mourn the death of a scene while dancing on its grave.
The future of music isn't a single sound. It's the sound of a million contradictions playing at once. It's the glitch in the system, the human heart beating inside the machine, the raw, unquantifiable feeling that leaks out when the grid breaks down. To find it, you have to stop listening for the next big thing, and start listening to the quiet revolutions happening in the cracks.
Over at Pitchfork, the conversation has moved beyond simply cataloging micro-genres to examining what happens when those genres implode. Hyperpop, that brief, glorious explosion of sugary distortion and emotional maximalism, has fragmented. Its pioneers have scattered, some retreating to more traditional pop structures, others diving deeper into abrasive, experimental electronic noise. The scene's center could not hold, but from its disintegration, something more interesting has emerged: a post-hyperpop landscape where the only rule is that there are no rules. Artists like underscores and Jane Remover aren't just making music; they're conducting salvage operations on the wreckage of a movement, building new forms from the shattered pieces of identity, nostalgia, and digital overload.
This fragmentation mirrors a broader cultural splintering discussed on Stereogum and The Fader. The monoculture is dead, buried under the algorithmic weight of infinite choice. There is no single "underground" anymore, but a thousand tiny, thriving ecosystems. In one corner, artists are reviving the raw, tape-hiss intimacy of early 2000s indie folk, a direct reaction to the sterile perfection of streaming-era production. In another, collectives are forging new strains of global club music, weaving together dembow rhythms, UK drill, and Afrobeats into dizzying, borderless hybrids. The audience isn't just listening; they're curating, participating in niche Discord servers, and championing sounds that will never touch the Hot 100. Success is no longer defined by platinum plaques, but by the intensity of a dedicated community.
Meanwhile, Consequence and NME are tracking the industry's awkward, billion-dollar tango with artificial intelligence. The headlines swing wildly between utopian promise and dystopian panic. One week, a startup promises AI tools that will help musicians overcome writer's block. The next, a viral "new" track by a long-dead artist sparks protests from estates and unions. The real story isn't in the hype or the fear, but in the messy middle where artists are actually using the technology. Producers are employing AI stems to brainstorm unusual textures. Songwriters are using large language models as high-tech parlor games, feeding them bizarre prompts to break out of creative ruts. The threat isn't that AI will replace artists, but that it will further inundate an already oversaturated market, making discovery even harder for human creators. The tool is here; the ethical and economic framework is not.
Beneath all this lies the engine of discovery itself, a topic Hypebot dissects with clinical precision. Playlists are no longer just mixtapes; they are the new radio, the new A&R, the new gatekeeper. But the gatekeeper is a black box. The algorithms that power Spotify's "Discover Weekly" or TikTok's sound trends are opaque, optimizing not for artistic merit, but for engagement and retention. This has created a new kind of sound: the "algorithmic native" track, engineered with crisp, immediate vocals, a drop before the 30-second mark, and a hook designed to survive being played on a phone speaker. It's a creative constraint that some chafe against and others have learned to master, writing songs that are as much data sets as they are emotional expressions.
What ties these threads together—the genre collapse, the niche communities, the AI anxiety, the algorithmic pressure—is a collective renegotiation of authenticity. In a world where a sound can be synthesized, a career can be built entirely online, and a genre can be born and die in a Twitter thread, what does it mean to be "real"? The answer is being written not in press releases, but in the work of artists who embrace the contradiction. They use AI to explore human loneliness. They craft music for algorithms while embedding deeply personal lyrics within it. They mourn the death of a scene while dancing on its grave.
The future of music isn't a single sound. It's the sound of a million contradictions playing at once. It's the glitch in the system, the human heart beating inside the machine, the raw, unquantifiable feeling that leaks out when the grid breaks down. To find it, you have to stop listening for the next big thing, and start listening to the quiet revolutions happening in the cracks.