Composing with a Machine: A 5-Step Guide to Creating Music with AI

Severin Sorensen
2 days ago
6 min read

For most executives, artificial intelligence has already proven its worth as an analyst, a drafter, and a sounding board. Fewer have discovered what happens when the same conversational fluency is pointed toward something far less utilitarian: music. The same discipline that produces a sharp board memo or a clear strategic brief also produces something unexpected when redirected toward melody, instrumentation, and lyric.

Leaders who engage seriously with AI music creation tend to arrive at a similar observation: the tool responds most generously to clarity of intention. It is, in that sense, the newest instrument in a lineage stretching from the first drum to the modern studio. Those who approach it as a creative collaborator find that it extends what they are able to express, without requiring them to become musicians to do so.

For business leaders and executive coaches, the most resonant use case is tribute. A song composed in remembrance of a colleague lost, a veteran honored, or a team marking a difficult anniversary can carry meaning that a card or a speech often cannot reach. AI-assisted music creation gives more leaders the practical means to create that kind of work.

Music as a reflection of the moment

Around the great turning points of the year, many leaders feel the pull to mark the occasion with something beyond routine acknowledgment. Reading history, writing a personal note to the team, gathering people in a room to name what the date represents: these are all worthy practices. In recent years, composing an original piece of music has become a practical addition to that list.

With tools like Suno and a disciplined prompting practice, it is now possible to produce a genuine musical reflection of a holiday, one grounded in the specific history being honored and shaped by the emotional register the moment calls for. The process only takes a few hours, requires no musical training, and produces something the audience will remember in a way that slides and speeches typically do not.

As the nation marks the 250th anniversary of its independence this week, I’m reminded of songs that I composed for prior American holidays, each one a reflection of a specific moment of remembrance or celebration. They are gathered here because the 250th anniversary of American independence is an appropriate occasion to revisit them. Created at the intersection of AI and human intention, with careful attention to lyric, structure, and emotional register, they honor the men and women in uniform whose service has made this country's history possible. Listen before reading further, and consider what you might create:

How to create your own song: A step-by-step guide

The process of creating a song is more accessible than most leaders expect. It requires no studio equipment and no technical background beyond the prompting skills you already use at work. Here is how it works from start to finish.

Step 1: Open Claude or ChatGPT and build your lyrical prompt

Begin in conversation with a reasoning model such as Claude or ChatGPT. Describe what you want to create: who the song honors, what quality or memory should anchor it, and the emotional tone you are reaching for. Solemn, resolved, quietly hopeful, and triumphant are all distinct registers that produce meaningfully different outputs. Specify a structure, how many verses, whether a bridge is needed, and what the final chorus should feel like. Include a target length, typically two and a half to three and a half minutes for a piece, and name a genre or reference artist if one comes to mind.

Ask the model to produce two outputs: a style description covering instrumentation, tempo, and vocal delivery, as well as a complete lyric sheet with bracketed section labels such as [Intro], [Verse 1], [Chorus], [Verse 2], [Bridge], and [Outro]. Those two elements are what is needed to generate music with precision.

Step 2: Copy the lyrics and style description into Suno

Navigate to suno.com, where you will need to create a free account to get started. Suno offers a free tier that allows you to generate a limited number of songs, which is enough to explore the tool and produce an initial draft. Once inside, create a new song in Custom Mode, which allows you to supply your own lyrics and style prompt rather than relying on Suno's automatic generation. Paste the style description into the style field, for example: slow acoustic ballad, piano and strings, warm baritone vocal, restrained and building. Paste the lyric sheet, section labels included, into the lyrics field. Suno will typically return two versions simultaneously, giving you an immediate basis for comparison.

Step 3: Return to Claude or ChatGPT to fine-tune the lyrics

If the lyrics need revision after hearing the initial generation, return to your reasoning model rather than editing inside Suno. Paste in the current lyric and describe what is not working: a chorus that feels too abstract, a bridge that loses momentum, a hook that does not land. Ask for a targeted revision, then bring the updated lyric back into Suno's Remix flow and regenerate. Working iteratively across both tools is where the piece acquires the specificity that generic prompts cannot produce.

Step 4: Use "Remix" to refine the version you want

When you find a version worth developing further, use Suno's Remix feature to refine it. Remix allows you to adjust specific elements, including instrumentation, tempo, vocal style, and track length, without discarding the version you started with. Two or three passes are usually sufficient to produce something that holds the room. Describe what you want changed in plain language; Suno responds well to specific direction. As always, working with Claude or ChatGPT to refine your Remix prompt before re-entering it into Suno tends to produce better results. Using one AI to prompt another is a reliable pattern across creative workflows, and music generation is no exception.

Step 5: Download or Publish the Final Version

Once the piece is ready, Suno allows you to download the audio file directly or publish it to the platform. For a tribute intended for a specific event, download the file and play it at the ceremony, embed it in a presentation, or share it with others in advance. For work intended for a wider audience, Suno's distribution options make it possible to publish to Apple Music and other streaming platforms.

What makes a strong song

The quality of the prompt built in Steps 1 and 4 determines the quality of the output. A few specific choices make a measurable difference.

Identify the hook before writing the verses: The hook is the line, typically placed inside the chorus, that the listener carries with them after the song ends. In lyrical work, the most durable hooks name the quality being honored with specificity. For example, courage, steadiness, sacrifice, or service. Starting with that line and building the rest of the lyric outward from it produces more cohesive results than writing linearly from verse to chorus.
Genre and instrumentation tags shape the emotional register as directly as the lyrics themselves: A remembrance piece generally calls for restrained acoustic instrumentation at a slow to moderate tempo, with vocal delivery described explicitly in the style field. Specificity in the style description produces noticeably better results than general terms like sad or emotional.
Include guidance about space and silence: Instrumental pauses, a sustained note before the final chorus, and a quiet outro rather than a hard stop are choices that give a generated track compositional intention. They can be requested in the prompt and make a significant difference in how the finished piece lands in a room.
Working iteratively across multiple tools is where the piece acquires the specificity that generic prompts cannot produce.

Leadership lesson beyond the music

The value of this practice for executives extends beyond the song. Producing a piece of music through AI requires translating an internal, often inarticulate feeling into language precise enough for a platform to act on. That is a skill with direct applications across every domain where leaders communicate: strategy, feedback, organizational change, and team alignment, and it becomes most apparent in moments where the feeling involved is difficult to name precisely. The leader who can describe grief or gratitude clearly enough to produce a coherent lyric has practiced the same capability required to describe a strategic ambiguity clearly enough for a team to execute against it.

Music has always developed alongside the tools available to those who made it. AI-assisted composition is the current chapter in that history. Leaders who engage with it seriously find that the platform rewards the same qualities that good leadership has always required: clarity of intention, precision of language, and a genuine understanding of what the moment calls for.