Get Better, Not Bitter — What Every AI Music Creator Needs to Hear Right Now

Three things on my mind this week — and all three connect back to the same idea.

First: why Suno is engineered to steal your afternoon, and the three questions that fix it. Most people open Suno as a browser. The ones getting results walk in as directors. Sub-genre. Mood. Texture. Know what you're building before you hit generate.

Second: the view from inside the curator's chair. I'm a five-star SubmitHub curator and I reject most AI music submissions — not because they're AI, but because they make the same five fixable mistakes before the song ever gets a fair listen. Disclosure, visuals, genre targeting, instrumental packaging, and trust signals. Fix these five things and you're already ahead of most of what lands in a curator's queue.

Third — and this is the one that matters most to me — where I actually stand on all of this as a human artist who has released music, worked with real musicians on real projects, and invests in music royalties. Which means I almost certainly own rights to songs used to train the same AI models I now teach people to use. I have skin in this game on multiple sides. And I'm not bitter about any of it.

The rules aren't going to crystallize anytime soon. Build anyway.

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#AIMusicProduction #AIMusic2026 #JGBeatsLab #MusicProducer #Lane2 #Podcast

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New episodes of the AI Music Revolution drop every Friday, and most Tuesdays. Everything mentioned in today's episode is at jgbeatslab.com. Links in the show notes.

Transcript

SPEAKER_00 0:29

Welcome back to the AI Music Revolution. I'm Josh Gilliland, founder of JGB Slab. If you've been in any AI music community online lately, you know the conversation is loud right now. People defending AI, people attacking AI, people telling you it's the future, people telling you it's theft. Most of these people are not actually making music, they're making noise. Today I want to talk about three things that have been on my mind. Things that I think are actually useful to you as a creator. These aren't takes, they're not hot opinions, these are things you can actually use. We're going to start with something practical. Why Suno is designed to eat your afternoon, and three questions that fix that. Then we're going to go inside the curator's chair. I'm a five-star Submit Hub curator, and I'm going to tell you exactly why I reject AI tracks. Not because they're AI, because of five fixable mistakes that most producers don't even know they're making. And then I want to end with something a little more personal. Because I've been in bands, I've released music, I invest in music royalties, and I want to tell you where I actually stand on all of this. So let's get into it. Segment one, the Sunodopamine Loop. A few months ago, I sat down in Suno with no particular plan. I just wanted to make something. An hour and a half later, I had burned through dozens of generations and assembled what can only be described as a surprisingly complete catalog of songs about the fat squirrel that lives in my backyard and terrorizes my bird feeders. Listen, I had enough tempo number, I had a melancholy ballad. I'm pretty sure there was like a squirrel opera in there somewhere. Was it fun? Hell yeah, it was. Was any of it finished music? Man, not even close. Here's the thing I want you to understand with this. That afternoon was not a failure. Wasn't a failure of discipline. That was Suno working exactly as designed. Every generation is a small win. You you hit a button, something comes back, and your brain fires. It just lights up. The feedback loop is tight and rewarding. And that's a feature. It's generally part of what makes the platform absolutely great for creative exploration. But here's what nobody talks about. Exploration and production are two completely different modes. And Suno does not tell you which one you are in. When you're in exploration mode, you're browsing, you're discovering what's possible. That that has real value, especially when you're learning a platform or you know hunting for a sound. But when you sit down to make finished music, you need to be in production mode. And production mode requires one thing that exploration mode doesn't, a clear target before you start. Before you open Suno, I want you to answer three questions. First, what is the genre and feel? Not just rock or country. Be specific. Is it up tempo or slow? Is it dark or bright? What artists are in the same zip code as the track you're trying to make? What is their sound? What is the sound that you are going for? Second, what is this track for? Is it part of a project? Is it for a playlist? Do you know where it lives when it's done? What is the plan? What is the journey for the song? Third, how will you know when it's done? This one is the probably the most underrated. Done is a decision, not a feeling. Name it before you start. Otherwise, the session has no natural end. Three questions. Five minutes. They are the difference between a productive session and an afternoon that disappears. The squirrel will still be there. Let him wait. That idea going in with a plan, being a director instead of a browser, that's the entire foundation of the threesong sprint course I just released. Five sessions, nearly two hours of content, worksheets, cheat sheets for every step. You walk away with a Finnish mastered threesong EP. It's$29 as a standalone. It's free inside of Red Lab Access. Link is at jgbeatslab.com. Okay, segment two. These are some informative bits, is what I'm starting to call these. This one is about the Submit Hub curators' secrets. So let's talk about Submit Hub. I want to give you something here that most people in the AI music space do not have access to. The view from inside the curator's chair. I'm a five out of five rated Submit Hub curator, which means I receive AI music submissions regularly, and I reject most of them. Not because they're AI, but because they make the same five mistakes before the song ever gets a fair listen. And let me walk you through each one of those mistakes. Mistake number one, hiding the AI disclosure checkbox. Submit Hub has an internal tool that analyzes tracks for AI origin. I've tested it on my own music. My AI tracks get flagged as AI. My human tracks get flagged as human. There's a myth in this community that if you hide the AI checkbox, you'll sneak past curators who filter for it. You won't. And here's what actually happens. If you mark your tracks as 100% human and the tool flags it as AI, you've broken my trust permanently. I won't listen to your next submission ever. Here's the reframe for this. The AI disclosure filter is your friend. It routes your track only to curators who are open to AI music. Why would you pay credits to pitch someone who's going to reject you on principle? That's not strategy, that's a waste. Mistake number two, your visuals failed before I hit play. I judge the cover art before I judge the song. Hate to admit it, every curator does it. A generic AI image with you know floating notes and gradient text over a blurry sunset tells me something about the level of care that went into everything else. And that impression is usually accurate. So make your cover art look like a record cover, not a screensaver, not AI slop. Mistake number three: your genre targeting was too broad. More curators don't mean more chances. It means more wasted credits on people who sort of fit your track. A smaller curator who deeply identifies with your exact lane is more valuable than a big curator with broad reach and a weak fit. Find your lane, target it precisely. I'll give you an example of my own playlist. I'm a playlist curator for a hard-rocking modern country playlist with a party vibe. So that is a very tight niche of songs that I'm looking for. I end up getting submissions across the totality of the country music landscape, of which I decline most of them because I am looking for that one specific niche. When a song comes in to me inside of that specific niche, it gets a very high position on my playlist and it does extremely well. All right, mistake number four. Your instrumental had nothing else carrying it. So a lot of AI music is instrumental, cinematic, lo-fi, ambient, synthwave. That's not a problem. But when there are no lyrics, everything else has to work twice as hard. Genre precision, title, artwork, tempo, mood. For instrumental submissions, your submission is all of those things working together, not just the audio file. So for your instrumental only tracks, be sure to take very intense dedication and commitment to making those things world-class. Mistake number five, you felt risky to bet on. Curators are not just evaluating your music, they're evaluating whether adding your track to their playlist is a safe bet for their audience and their reputation. Generic branding, inconsistent metadata, no real artist's identity behind the submission. These things trigger instincts that are hard to override, no matter how good the track actually sounds. So build your artist's identity before you submit. Give curators a reason to trust you. Listen, none of these mistakes are about the music being AI. They're not. They're about presentation, trust, and fit. I go much deeper on all of this in the curator's code. It's a guide I wrote from the curator's chair, not the artist chair. It's exclusive to the Red Lab Access members. If you want to stop burning credits and start getting added, that's where you need to go. Okay, let's get into segment three, the last segment for this episode. I want to end today with something a little more personal. Because every week I see the same argument playing out in comment sections and forums and communities all over the internet. Human artist versus AI music, the ones who feel replaced and the ones embracing the tools. And most of the people making the loudest arguments on both sides are not actually making music. I want to tell you where I actually stand because I think my position is maybe a little different from most people in this space. I've been in bands. I've released music. I've worked on large-scale projects with real musicians, real studios, real stakes, including one that was ready to break right before COVID hit and took the whole thing down with it. I also invest in music royalties, which means I own the rights to songs that were almost certainly used to train the same AI models I now teach people how to use. So when someone tells me I can't possibly understand what human artists are going through right now, I push back on that pretty firmly. So here's where I stand. I don't label industry changes as good or bad. I label them as variables, the variables that have changed. And then I figure out what to do next. Do I think music I own the rights to was used to train AI models? Almost certainly yes. Would I want compensation for that? Hey, if someone wants to send a check, I'll take it. Am I holding my breath? Not even slightly. Am I feeling victimized? Not even for a second. And here's why. I've never once seen an industry stay static. Not music, not technology, not finance, not anything. Every industry evolves. And the people who survive these evolutions are the ones who treat change as a variable to adapt to, not an injustice to resent. The ones who don't make it are the ones who got dealt a bad hand. They're the ones who decided the hand that they had was the hand that they were supposed to keep forever. Buddha understood this. Impermanence isn't a tragedy. It's just the nature of things. If your mission in life is to hold the world constant, you've already committed to a life of disappointment and suffering. Nothing stays, not the music industry, not the tools, not the platforms, not the rules around who owns what. Now, does acknowledging change mean accepting every version of it without question? Absolutely not. The compensation question for human artists whose work trained these models is real and it's unresolved. I'm not dismissing that. I have personal skin in that game. But there's a difference between advocating for fair treatment in a changing landscape and refusing to engage with that landscape at all. One is a reasonable position, the other is a choice to become irrelevant. The musicians I respect most right now are the ones treating AI the same way previous generations treated the electric guitar, the synthesizer, the DAW, the digital distribution, and as new variable in the equation that requires them to get better, not bitter. That's what lane two is built on. Human-authored, AI-assisted, your story, your vision, your creative direction with the most powerful production tools in history available to execute it. Not replacing the human, amplifying it. The point is the music. The tools keep changing. Okay, that is it for episode 12 of the AI Music Revolution. If anything in today's episode hit home, share it with someone in your circle who's still maybe on the fence about AI music. Not to convince them, just to give them maybe a different angle to think from. Everything we talked about today, the three song sprint, the curator's code, red lab access, all of it is at jgbeatslab.com. The link is in the show notes. New episodes drop every Friday. I'll see you next time.