Generating a due-diligence-ready song with Suno v6

Newbies shouldn't treat Suno v6 as a tool where you click once and make money. A safer approach is to use it as an auditable Demo: first learn to generate, export, and log versions, then decide if it's suitable for commercial use. I've been making some music samples with it recently and broke down the workflow.

I ran two approaches twice each. Approach 1 is direct descriptive generation: just tell the AI what kind of song you want, letting it fill in lyrics and arrangement. Good for quick testing. My tests showed about 2 out of 3 songs were listenable; one had muddy vocals, and the chorus felt unfinished. Approach 2 is writing lyrics first, then choosing a style. Suitable for investment due diligence because there are fewer variables and issues are easier to attribute. I prepared three sets of lyrics, each with a dozen lines, and saw significantly fewer discarded drafts. The cost is spending a few extra minutes upfront. Newbies should start with Approach 2. AI music models essentially let computers generate songs based on text. The clearer your input, the less likely it is to sing randomly; the vaguer your input, the result feels like pulling a gacha.

Specifically, open the Suno website, register, and enter Create. You'll see Simple Mode and Custom Mode; choose Custom so you can fill in lyrics yourself. Paste lyrics into Lyrics. Don't write too long at first; under 16 lines is more stable. Keep two verses and one chorus. Keep sentences short, especially for Chinese songs—don't cram too much into one line. Write plain language in the style box. You can input light electronic, female vocals, slower tempo, repeating chorus, suitable for night. Newbies shouldn't pile on jargon, or the model won't know what's important. Confirm the model version. News says v6 is released, and older models will be phased out. Before clicking Generate, check the model selection box to ensure v6 is selected. If it defaults to an old model, switch back. Click Create. Wait tens of seconds to a minute or two; usually two results appear. Don't rush to download; listen from start to finish, focusing on vocal articulation, whether the chorus is memorable, and if the ending cuts off weirdly. For listenable versions, click Extend or Remix. Extend continues the song; Remix changes the arrangement. Newbies should try each once. I suggest max two rounds of revision per song; beyond that, the direction probably wasn't clear. Click Download to export. Before exporting, definitely read the licensing terms. Products like Suno record generated content and may include watermarks. Watermarks are invisible markers embedded by the platform to identify content sources. Don't try to remove them; doing so might affect platform identification and distribution. Finally, keep a log. I recently used a spreadsheet to create a small ledger with fields: date, model version, lyric summary, style keywords, listenability, and suitability for commercial use. This step looks basic but is crucial.

Pitfalls and investor judgment—I list three. First pitfall: assuming platform copyright partnerships mean users can freely commercialize. News says Suno has partnered with Warner Music, BMG, etc., but this doesn't mean every user can take generated results to run ads or sell songs. Commercial licensing depends on account type, export file status, and platform policies. Second pitfall: ignoring changes in download policies. Materials mention a change related to download policy on September 3. Just because you downloaded before doesn't mean it works today. Re-check page prompts before every export. Third pitfall: Chinese lyrics being too long. The model swallows words to keep the beat. Solution: keep each sentence to around ten-plus characters, and repeat a core phrase in the chorus.

I review over 500 AI and robotics projects a year. Seeing Suno v6, my first reaction is still to ask: what's the valuation logic? Where's the ceiling for this track? Early on, these products are often hyped as 'everyone is a composer.' But valuation logic depends on whether it can connect generation, licensing, distribution, and settlement. How good the listening experience is is just surface-level. Suno's old story was model capability. The new story is more about the copyright and distribution system: label partnerships, community, identification, downloads, APIs—all part of the system. For developers, retiring old models means re-adapting. For investors, look at paid retention, licensing boundaries, and developer API call volumes; play counts are just outcomes. My judgment: the next round of competition in AI music will depend on who can turn a song from a Demo into a traceable, licensable, distributable asset. Generation speed is just the entry ticket. Models will get cheaper; licensing and distribution processes are what cost money.

After learning this, try three things next. Use a spreadsheet to organize twenty style Demos, pick one to post on short-video platforms for a small-scale retention test, and use an Agent to help batch-edit lyrics—but don't let it judge copyright for you.