I Used Suno AI to Produce an Album in One Month, Here’s What I Learned.....
- Justin Robinette
- Aug 9
- 5 min read
As a music producer with years of experience, I’m constantly exploring tools that can push creativity forward. Recently, I spent a full month using Suno AI, a text-to-music generator, to create my latest project, The Heartbreak EP. I wanted to see if AI could streamline the creative process, inspire new ideas, and maybe even produce release-ready tracks.
After 30 days, 2,500 credits, and countless generated songs, here’s what I found.
About Suno AI
Suno AI is an emerging generative AI music platform that creates original songs from text prompts, primarily lyrics, using machine learning models trained on large music datasets. Instead of composing notes manually, producers can upload lyrics or style descriptions, and Suno generates full song versions in seconds.
It works via a credit-based subscription model, where each generation costs 10 credits and produces two song options. Monthly plans typically provide thousands of credits to experiment with.
The platform aims to empower creators by speeding up songwriting, sketching ideas quickly, and blending AI creativity with human input. Unlike many AI tools that focus on loops or samples, Suno tries to build complete tracks with vocals and instrumentation.
How Suno AI Compares to Other AI Music Tools
Compared to alternatives like Amper Music, AIVA, or Soundraw, Suno stands out by focusing on lyric-driven song generation with AI vocals, a cutting-edge approach.
Unlike OpenAI’s Jukebox, which is research-focused and less accessible, Suno offers a commercial-grade platform with user-friendly interfaces.
However, like many AI music generators, it faces challenges in audio quality, stem separation, and fine control over arrangements, which are common hurdles in the industry today.
My Experience with the User Interface
Suno’s UI is straightforward. You enter your lyrics or text prompts, select a style or mood if desired, and generate tracks. The platform is easy to use, but can feel a bit limited because:
There is no deep editing of arrangements or stems.
Lyrics can sometimes be mispronounced or repeated oddly.
Navigation between saved generations and exports could be smoother.
Still, the quick turnaround makes it a useful tool for rapid ideation.
Prompting: What I Tried
For The Heartbreak EP, I uploaded full lyric sets for each track and let Suno generate multiple versions.
Often, I had to run multiple generations to find usable takes, sometimes tweaking the wording slightly to influence the results. This iterative approach is necessary because AI creativity can be unpredictable.
Copyright and Usage Notes
One important consideration is that Suno’s terms allow users to commercially release music generated on the platform, with royalty-free usage granted. This is a significant advantage for creators seeking to monetize AI-assisted compositions without legal hurdles.
My Workflow: From Lyrics to Final Tracks
For each song, my process was straightforward:
Upload the lyrics to Suno’s prompt window.
Generate song versions (each generation costs 10 credits and produces 2 song versions).
Listen through the outputs until I find one worth saving.
With 2,500 credits, I ended up with 6 tracks I was proud of. That might sound efficient, but in reality, it meant sifting through hundreds of discarded outputs. For every track I kept, there were around 80+ versions I didn’t, a hit rate of only about 1 percent.
The Pros: What Suno Does Well
Despite the low keep rate, Suno AI offered some clear benefits:
🎨 Rapid idea sketching. It is incredibly fast to get a starting point for a song.
🚀 Creative sparks. Sometimes, the AI surprised me with melodies or arrangements I wouldn’t have thought of myself.
🛠️ Simple workflow. Upload lyrics, hit generate, and you’re off.
The Cons: Where It Falls Short
However, when it comes to production quality, Suno has some major limitations:
Stem Bleed. When exporting single stems, there is noticeable bleed, for example, vocals bleeding into instrumental tracks, making them difficult to mix professionally.
Muddy Mixes. The overall sound quality can be compressed and muddy, lacking the polish needed for release-ready material.
Limited Control. Beyond prompts, you don’t have granular control over arrangement or sound design.
How the Songs Turned Out
All six tracks came out musically strong, good enough to make the final EP, but I still had to rely on my own mixing and mastering skills to bring them up to a professional level. Without heavy post-production, the AI’s output wouldn’t stand on its own.
For mastering, I used my typical chain:
Mid/Side Processing to balance stereo width and tighten the low end.
Subtractive EQ to carve out unwanted frequencies.
Additive EQ to enhance clarity and add brightness where needed.
Glue Compressor to bring cohesion to the mix.
Limiter to control peaks and raise overall loudness.
Ozone 9 for final polish and commercial loudness standards.
Even with these steps, the raw Suno outputs required significant work to meet the quality I expect in a release.
Future Outlook: Where Suno AI and AI Music Tech Are Headed
Suno AI recently introduced stem separation, which is a promising but still very early-stage feature. Currently, the stems suffer from significant bleeding, where vocals and instruments overlap across tracks, making professional mixing a challenge. This highlights that while progress is happening, the technology remains in its infancy and has a long way to go before achieving clean, usable stems.
Looking at the evolution of Suno, from early versions that generated whole songs with minimal control to now offering stem separation, it is clear the developers are actively working to improve usability and quality.
Moving forward, I expect:
Major improvements in stem isolation to reduce bleed and give producers real mixing flexibility.
Enhanced vocal synthesis with more natural phrasing and emotional expression.
Greater user control over arrangements, instrumentation, and mix elements.
Deeper DAW integration for seamless collaboration between AI-generated tracks and human producers.
AI tools are designed to augment creativity, providing smart suggestions while leaving the artistic decisions to humans.
Though AI music technology is rapidly advancing, fully replacing the nuance and depth of human production is still a ways off. For now, Suno and similar tools offer valuable ideation and sketching platforms that will only get more powerful and polished in the near future.
As a producer, it is exciting to witness this evolution and to experiment with AI as a creative partner in the music-making process.
Final Verdict: A Useful Tool, But Not a Replacement
After using Suno AI extensively, my conclusion is this:
It is great for brainstorming and inspiration.
It is not ready for professional production.
The technology is evolving quickly, but at this stage, it is best seen as a collaborator for early ideas, not a complete replacement for human producers and DAWs.
🎶 Listen to the Final Album
Want to hear how it turned out?👉
💬 What Do You Think About AI in Music?
AI is changing the creative landscape, but should it? I’d love to hear your thoughts. Please drop a comment below and let me know where you stand on the future of AI-generated music.
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