Suno Studio, a Generative AI DAW

Perceived Quality of Suno V5 & Studio

• Many find V5 a big leap: higher fidelity, less “AI shimmer,” genre pastiche good enough to replace some commercial playlists for casual listening.
• Others still hear obvious artifacts: thin/tinny synth-like vocals, over‑produced and “smoothed over,” flat song dynamics, predictable structures.
• Some consider V5 a regression in style control vs 4.5 (less “chopped/produced,” more generic), even if the raw audio quality is higher.
• Questions remain about noise level and stem quality; some say covers built from user uploads sound better than pure text‑to‑song.

Is Studio a Serious DAW or a Toy?

• Critics see Studio as a browser DAW with minimal editing: basic slicing, repitch, no fine control over dynamics/EQ, missing essentials like VST support.
• Being online/SaaS worries experienced producers: lock‑in to a proprietary format, risk of losing projects when subscription ends, latency concerns.
• Some argue no serious pro will adopt a DAW that can’t host plugins; others note incumbents could bolt AI onto their existing workflows instead.

Target Users: Musicians vs Casual Creators

• Working musicians say Studio is clearly not aimed at them; it’s closer to GarageBand for non‑producers seeking quick, impressive snippets.
• Others praise it as enabling: people with no rhythmic/pitch skill can finally realize lyrics or ideas and feel “superpowered.”
• A minority already integrate Suno into pro workflows: generate ideas/covers, export stems/MIDI, then fully rework in traditional DAWs.

Art, Authorship, and “Real” Music

• Strong debate over whether Suno users are “musicians” or “curators” pressing a sophisticated “Guitar Hero” button.
• Some say joy in creation is what matters; if prompting and iterating gives that, it counts as art. Others see it as akin to ordering food, not cooking.
• Many emphasize missing “intent” and lived experience: AI tracks sound like statistically average genre imitations, lacking genuine surprise or emotional depth.
• Counterpoint: most commercial pop is already committee‑built and highly formulaic; many listeners can’t or don’t care to distinguish.

Economic & Ethical Concerns

• Anxiety that ad music, trailers, jingles, stock tracks and even some pop will shift to cheap AI, squeezing working musicians and illustrators.
• Several call AI music “stolen work,” objecting to training on uncredited catalogs; others insist copyright never protected style and that competition is inevitable.
• Licensing language around “commercial rights while subscribed” initially alarmed some; clarification: rights persist for songs made during paid periods.

Culture, Discovery, and Content Flood

• Fears of “degenerative art”: AI slop saturating Spotify/YouTube, making discovery of human work harder (some already abandoned genres swamped by AI tracks).
• Others argue hyper‑personal, one‑listener creations (e.g., songs about one’s pet) will form tiny “micro‑bubbles,” not mass culture.
• Debate whether this accelerates homogenization (models regurgitating mainstream patterns) or empowers niche styles that were previously uneconomical.

Practical Workflows & Desired Features

• Desired AI features: stem extraction, melody/harmony analysis, timing/noise fixing, better stem export, voice‑to‑instrument, and “assistive” composition rather than full auto‑songs.
• Some already use Suno this way: upload rough ideas, let it re‑arrange, then re‑record or replace every part manually; treat AI as a sketch generator.
• Open questions raised about open‑source music models, AI detectors, long‑term sustainability of Suno’s VC‑funded model, and whether it can become the “DaVinci Resolve of DAWs” if a strong free tier emerges.