Using ChatGPT As A Composer
I’ve experimented with AI quite a bit over the last year. I’ve used it to try to train a model to adopt my specific document review approaches. I’ve used it to build a portal on the fly to manage document uploads. I’ve used it when allowed during coding interviews. I even used it to a degree when building the scaffolding I used for those coding interviews, including a basic code, API, and test project.
Where I was most resistant to using it, though, was in my composing. I want what I produce to reflect me, not a machine. That said, I’ve found a specific and effective use for ChatGPT, in spite of all the ads telling me to stop using it “like Google”, because that’s exactly what I do with it.
When composing, I used ChatGPT to unblock by having it hopefully coalesce Google searches I would have executed myself and had to sift through to arrive at an answer.
I am currently writing a symphony. My first question to ChatGPT was to outline a typical approach to a Baroque style symphony and how I should think about structure. That’s pretty basic.
But recently I was writing the second piece in the orchestral suite. It requires the second part of the piece to transition from D major to A major, and then close in D major at the end. I was really struggling based on my melodies and progressions to get from D to A without it feeling like it was absolutely dying to resolve back to the D major chord.
So I sent over a prompt:
Sadly my A section ends naturally on an A for a measure to an A7 for an extra measure before returning to D major. At the end of my second A section, how do I now get to A? I feel like just staying there won’t work. Can I shift to F# minor instead? Or is there a turnaround since this is supposed to transition keys to the major 5?
ChatGPT suggested two responses, which I tried.
Option A – Classic ii–V–I into A
Near the end of the section, let D go, and instead:Treat B minor as ii of A
E7 as V of A
Then A as I (new key)
Example last 3 chords of the section:B minor → E7 → A
Coming out of D‑world you can arrive on Bm very naturally (vi in D, ii in A),
Then Bm–E7–A is a textbook ii–V–I in A major.
You can still touch D before that (so it feels like you’re still in D), but your final phrase should clearly choose Bm–E7–A instead of A7–D.Option B – Use F♯ minor as a pivot (your idea)
Yes, you can go via F♯ minor: it’s vi in A and iii in D, so it’s a legit pivot.Something like:
… D → F♯m → Bm → E7 → A
In D: F♯m = iii, Bm = vi. Still sounds like D.
In A: F♯m = vi, Bm = ii, then E7 = V, A = I.
Both sounded pretty harsh, so I let ChatGPT know I wasn’t fond of either choice after giving each a listen. After doing the usual “Oh You Are Right” false praise that AIs love to do, ChatGPT offered a few suggestions, and in going through them I figured out why they weren’t working: the D natural in the suggested E7 chord was still pulling back to D major. Once I came up with my conclusion I let ChatGPT know.
Ok so this is what ended up working. The original turnaround at the end was 1 bar D, 1/2 bar Bm, 1/2 bar C#dim, leading into an F# minor, which is how this progression starts. I replaced that with 1 bar Bm, then 2 bars E without the 7; the D in the E7 was wreaking havoc with my ear.
And ChatGPT gave me positive feedback on why it worked.
That’s a very sensible fix, and it explains why your ear finally relaxed.
What you had before:
Old turnaround:
D (1 bar) → Bm (½) → C♯dim (½) → F♯m …
That strongly re‑stated D as “home” right before moving on, so anything after felt like it still wanted to resolve back there.What you changed to:
New turnaround:
Bm (1 bar) → E (2 bars, no 7) → F♯m …
Why this works:No strong D at the end
By removing that full bar of D, you stop telling the listener “we’re safely back at tonic.”
Bm → E already steers the harmony toward A/F♯‑world instead of D‑world.
Plain E instead of E7E7 (E–G♯–B–D) introduces a dominant‑of‑A feeling plus that D natural, which:
still evokes the original tonic D major in the background,
and makes the ear half‑expect A (and then D after that).
Using E major (E–G♯–B) without the D:
keeps the pull toward F♯m/A,
but doesn’t slam a dominant function in the listener’s face.
The result is more ambiguous / modal and less “I must cadence.”
Bm → E → F♯m is a smooth directional lineIn D terms: Bm feels like vi, E like a chromatic “brightening” step, and F♯m like iii/vi.
In A terms: Bm is ii, E is V, F♯m is vi; that’s all compatible with A/F♯ as a new region.
But because you don’t resolve E7 to A, the progression flows forward rather than closing.
So the new version:Stops reaffirming D right at the end,
Points gently into the new harmonic area via Bm → E → F♯m,
Avoids the D that made everything sound like “prep for a cadence.”
This is exactly the kind of local surgery you want in a modulation: same broad shape, but you trim out the one chord tone (D in E7, and the big D bar) that kept yanking your ear backward.
This is actually the critical bit that’s super helpful. While I don’t always adopt the suggestions, I have a concrete list of reasons why something worked or maybe didn’t, and a concrete list of options when I’m stuck that would have taken a while to pull together from searches if I couldn’t dig myself out on my own.
So, in this case, ChatGPT has become what AIs should be. A useful tool. But definitely not a replacement for the creative magic.

The piece captures a real moment of friction between principle and pragmatism: resisting AI as a co-creator to keep the work unmistakably yours, yet quietly turning to it when the harmonic door refuses to open. That specific modulation problem—ending on A yet needing to arrive at A without sounding static or forced—feels like the kind of knot many orchestral writers have stared at for hours. The iterative back-and-forth you describe (prompt, test, diagnose the rogue D natural, refine by stripping the seventh and extending the pivot) shows a disciplined ear at work; the final Bm → E → F♯m line reads as elegant precisely because it avoids the obvious cadence while still pointing forward.
It’s refreshing to see someone treat the tool as an accelerated thesaurus for theory rather than a magic button. The insistence that the output must still reflect personal reflection rather than algorithmic averaging lands convincingly here, especially since the breakthrough came from your own diagnosis of why the earlier suggestions felt harsh. Makes me curious whether this method will stay confined to problem-solving or gradually creep into larger structural decisions as the symphony progresses. Solid, grounded reflection on a tool most composers are still deciding how (or whether) to touch.
Thanks so much for your perspective. I’ve continued to use this as a tool, and likely won’t go much beyond that. There’s been a couple of times where AI has caught me about to break some “rules” about the period of music I am trying to participate in, such as the use of some off meter like 11/8, that I’ve given some serious consideration and finally found reasonable compromises. But for the most part the AI has been something to bounce off when I am unsure and earlier would have done searches. Beyond that I haven’t gone to it much.