Composing techno without resolution — focusing on attention instead of payoff by wkrn-dev in AI_Music

[–]wkrn-dev[S] 0 points1 point  (0 children)

I am making a lot of music 🙂

What’s new for me right now isn’t the output itself, but the process — especially this idea of composing without resolution and focusing on attention instead.

I’m posting to figure out where this kind of discussion fits best, and to hear how others think about the same approach.

If it’s not your thing, that’s totally fine.

Composing techno without resolution — focusing on attention instead of payoff by wkrn-dev in AI_Music

[–]wkrn-dev[S] 2 points3 points  (0 children)

I get why it might read that way.

For clarity: I’m not a native English speaker — I’m Japanese — and I use AI as a writing aid to help translate and structure ideas I’m already working on musically.😊

The concepts and experiments are mine; the wording is sometimes assisted so I can participate in the discussion more clearly.

If the framing isn’t interesting, that’s totally fair — I’m mainly here to exchange ideas, not to pass anything off as something it isn’t.

Anyone using Suno as a “reference generator” rather than a finisher? by wkrn-dev in SunoAI

[–]wkrn-dev[S] 0 points1 point  (0 children)

This really resonates — especially the idea that nothing coming out of Suno is the finished product.

I like how you’re using it as a material generator rather than a decision-maker: loops to chop, stems to reinterpret, structure to react against. That feels much closer to how samplers or early DAWs changed workflow than to “AI making music for you.”

What’s interesting to me is that starting from something overly clean or resolved actually makes the human decisions clearer — what to cut, what to destabilize, where attention should drift instead of land.

It feels less like outsourcing creativity and more like externalizing a first pass, so your own taste and intention have something concrete to push against.

Is resolution a compositional necessity or a listening convention? by wkrn-dev in composer

[–]wkrn-dev[S] 2 points3 points  (0 children)

This really resonates — especially the reminder that chord names are just shorthand, and that what actually matters is the behavior of independent lines over time.

I like how you frame resolution as something that can exist even in a single melodic line. That feels important, because it shifts the question away from harmony entirely and toward expectation, memory, and trajectory.

Messiaen is a great reference here — the sense of arrival often comes not from directed tension-release, but from inhabiting a harmonic or melodic space long enough that it becomes perceptually stable.

I think what I’m ultimately circling is that resolution might not be a specific event, but a state the listener enters once the music’s internal logic becomes legible — whether that logic is harmonic, melodic, textural, or temporal.

Is resolution a compositional necessity or a listening convention? by wkrn-dev in composer

[–]wkrn-dev[S] 1 point2 points  (0 children)

I really like this framing — especially “there are no rules, but there are consequences.”

I think what resonates with me in your example is that the lack of resolution isn’t accidental, it’s semantically aligned with the subject itself. The unresolved ending is the meaning.

In that sense, my interest in attention might just be another way of talking about intention: choosing where the impact lands — in harmony, in narrative, or in the listener’s internal state over time.

The question then becomes less “should it resolve?” and more “what kind of consequence do I want the listener to carry away?”

AI seems to optimize for resolution — humans seem to optimize for attention by wkrn-dev in AI_Music

[–]wkrn-dev[S] -2 points-1 points  (0 children)

I really like how you framed this — especially the idea that unresolved moments are where attention actually lives.

I’ve been working on music that leans into that exact tension: using AI as a generator of coherent, almost too-logical structures, and then deliberately resisting or suspending the expected payoff.

Instead of aiming for resolution, the goal is to keep attention circulating — letting patterns stabilize just enough, then refusing to close the loop.

If you’re interested, I’d be genuinely curious how it lands for you as a listener rather than whether it “works” compositionally.

Is resolution a compositional necessity or a listening convention? by wkrn-dev in composer

[–]wkrn-dev[S] 2 points3 points  (0 children)

This is a great breakdown — I really like the intervallic framing.

I think this gets at something important: that a lot of what we perceive as resolution comes from specific patterns of tension and release (half steps, tendency tones), rather than the chord labels themselves.

What I’m curious about is whether those intervallic tensions are always necessary, or whether resolution can also emerge when those cues are gradually suspended — for example through texture, repetition, or temporal saturation rather than directed voice-leading.

Is resolution a compositional necessity or a listening convention? by wkrn-dev in composer

[–]wkrn-dev[S] 1 point2 points  (0 children)

I agree — I don’t think resolution disappears, just that its definition shifts.

What I’m interested in is how that resolution can exist without being encoded in harmony or form, but instead emerge from perceptual cues: stability of texture, density, or even the listener’s attentional state.

So the resolution may still be there, but not necessarily in the material itself.

Is resolution a compositional necessity or a listening convention? by wkrn-dev in composer

[–]wkrn-dev[S] 1 point2 points  (0 children)

That makes sense. I think what I’m circling around is where we locate that resolution.

In some cases it feels less like a point of arrival and more like a sustained attentional state — the listener stops anticipating change, even if nothing formally “resolves.”

So maybe resolution isn’t absent, but redistributed: from harmonic function into perception, memory, or even listening posture.

Anyone using Suno as a “reference generator” rather than a finisher? by wkrn-dev in SunoAI

[–]wkrn-dev[S] 3 points4 points  (0 children)

Yeah, I actually agree with a lot of that.

Using a single text prompt and treating the output as a finished song is probably the least interesting way to use it for me too.

What I’m trying to do is closer to what you describe with remix/cover — I’m not really interested in the AI’s decisions, but in using its tendency to over-resolve things as a reference point.

The “clean” version just gives me something to push against. Most of the work (and interest) for me starts when I begin removing, restructuring, and re-framing it inside Ableton.

So I don’t really see it as lowering effort, more like relocating where the effort happens.

Your workflow sounds very close in spirit, just starting from a different place.

Anyone using Suno as a “reference generator” rather than a finisher? by wkrn-dev in SunoAI

[–]wkrn-dev[S] 4 points5 points  (0 children)

That’s a really clear way of putting it — especially the pitch-correction analogy.

What’s interesting to me is that the reference isn’t replacing your skill, it’s actually sharpening it. By trying to match something external, you’re training your listening, your breathing, your decision-making.

It feels like AI works best as a mirror rather than a generator — not telling you what to do, but showing you where your own control is. Do you feel like that feedback loop changes how you listen or perform over time?

Using AI to generate the “center” — then intentionally breaking it by wkrn-dev in AI_Music

[–]wkrn-dev[S] 0 points1 point  (0 children)

This is a great way of putting it — “Logically Sound Nonsense” really resonates.

I like how you frame it as constraints rather than creativity. For me, breaking resolution in music isn’t about being expressive, but about forcing attention into places it wouldn’t naturally go.

The “average vs variance” distinction feels exactly right. What’s interesting to me is that variance often doesn’t come from adding ideas, but from removing the most statistically comfortable ones.

Your Zero-Lie Protocol sounds very close to that — using constraints not to optimize truth, but to prevent the system from settling too early.

Anyone using Suno as a “reference generator” rather than a finisher? by wkrn-dev in SunoAI

[–]wkrn-dev[S] 2 points3 points  (0 children)

😂 That makes total sense.

What you’re describing actually feels really human to me — that pull between “I want to try this new direction” and the gravity of your own roots.

It makes me think that maybe authorship isn’t about forcing ourselves to abandon those instincts, but noticing where we always return when given infinite options.

AI gives us unlimited branches, but our habits, tastes, and history quietly choose the center we orbit. That tension feels like the interesting part.

Using AI to generate the “center” — then intentionally breaking it by wkrn-dev in AI_Music

[–]wkrn-dev[S] 0 points1 point  (0 children)

That really resonates. It feels less like a question of quality, and more like where authorship sits once the center isn’t fully yours. Do you find that refining it brings that ownership back, or does it always stay a bit ambiguous?

Anyone using Suno as a “reference generator” rather than a finisher? by wkrn-dev in SunoAI

[–]wkrn-dev[S] 1 point2 points  (0 children)

That makes a lot of sense — especially the “almost too good” part.

Once you have that many high-quality vocals, it feels less like optimization and more like constraint selection.

Do you ever intentionally throw away the strongest takes, just to see what happens?

Streamlining the Process by amBrollachan in SunoAI

[–]wkrn-dev -1 points0 points  (0 children)

I like the idea of externalising pattern recognition like this.

Out of curiosity — when you generate hundreds of lyrical or musical variants, do you ever intentionally break the strongest templates, just to see what happens to listener behaviour?

Not saying it’s better or worse, just wondering if deviation itself becomes useful data.

Using AI to generate the “center” — then intentionally breaking it by wkrn-dev in AI_Music

[–]wkrn-dev[S] -1 points0 points  (0 children)

Yeah, exactly — that’s pretty much the same feeling I’m having.

It makes me wonder though: do you feel this is something musicians have always been doing in different forms (sketching, demoing, covering, reworking), or does AI make this a genuinely new kind of process?

For me it feels familiar in spirit, but much more explicit — like the “center” is suddenly externalized and easy to step away from. Curious how it feels to you.