Insights from recent episode analysis
Audience Interest
Podcast Focus
Publishing Consistency
Platform Reach
Insights are generated by CastFox AI using publicly available data, episode content, and proprietary models.
Total monthly reach
Estimated from 4 chart positions in 4 markets.
By chart position
- 🇦🇺AU · Music Commentary#5130K to 100K
- 🇪🇸ES · Music Commentary#3430K to 100K
- 🇸🇪SE · Music Commentary#1871K to 10K
- 🇿🇦ZA · Music Commentary#170500 to 3K
- Per-Episode Audience
Est. listeners per new episode within ~30 days
18K to 64K🎙 Daily cadence·17 episodes·Last published 3d ago - Monthly Reach
Unique listeners across all episodes (30 days)
62K to 213K🇦🇺47%🇪🇸47%🇸🇪5%+1 more - Active Followers
Loyal subscribers who consistently listen
34K to 117K
Market Insights
Platform Distribution
Reach across major podcast platforms, updated hourly
Total Followers
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* Data sourced directly from platform APIs and aggregated hourly across all major podcast directories.
On the show
Recent episodes
Why a 30-Year Electronic Music Veteran Went All-In on AI: Inge Nilsen, Red Lab Conversations
May 12, 2026
33m 03s
The Suno Stack: Why You're Reaching for the Prompt When the Problem is Three Layers Below
May 8, 2026
18m 40s
The Window Is Still Open. But It Won't Be Forever.
May 1, 2026
16m 39s
I've Been a Passenger My Whole Life. Six Weeks Ago, I Got in the Driver's Seat.
Apr 28, 2026
38m 56s
The Real AI Music Problem Has Nothing to Do With AI
Apr 24, 2026
15m 26s
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| Date | Episode | Description | Length | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 5/12/26 | Why a 30-Year Electronic Music Veteran Went All-In on AI: Inge Nilsen, Red Lab Conversations | Send us Fan Mail Inge Nilsen got his first DJ mixer at age 12. He organized his first techno party in Oslo in 1991, before electronic music had even splintered into the genres we know today. He grew his concepts to fill the biggest venues in Oslo with 10,000 people. He was the first promoter to book Armin van Buuren in Oslo. He toured with Tiesto. He has been releasing on labels like Armada Music since the mid-2000s. That is the resume. What makes this conversation matter is what Inge is doin... | 33m 03s | ||||||
| 5/8/26 | The Suno Stack: Why You're Reaching for the Prompt When the Problem is Three Layers Below | Send us Fan Mail Most creators using Suno are stuck in the same loop. The generation comes back wrong. They rewrite the prompt. They generate again. Six rerolls later, frustrated and out of credits, they have nothing usable. The instinct is always to fix the prompt. But the prompt is rarely the actual problem. This episode walks through the Suno Stack — the ten-layer mental model for understanding where Suno problems actually live. Once you have the Stack, you can never look at a failed gener... | 18m 40s | ||||||
| 5/1/26 | The Window Is Still Open. But It Won't Be Forever. | Send us Fan Mail Most people watching AI music from the sidelines are waiting for something — for the tools to be perfect, for the legal questions to settle, for some signal that says it's safe to start. The signal is not coming. And by the time it does, the window will already be closed. This week on the AI Music Revolution: why waiting is the most expensive decision you can make in 2026, why the technical-versus-artistic debate about mastering misses what actually matters, and a clip from m... | 16m 39s | ||||||
| 4/28/26 | I've Been a Passenger My Whole Life. Six Weeks Ago, I Got in the Driver's Seat. | Send us Fan Mail Doug Arrowood spent his career in law enforcement. He did scenic art for Disney and Universal. He builds furniture, he paints, he writes. For his entire life, his relationship with music was the same as most people's — he pressed play and he listened. Six weeks ago, that changed. "I've always been one of the passengers in the vehicle. Now I'm in the driver's seat, and I can choose which car I want and which direction I want to go." In this episode, Doug walks us through what ... | 38m 56s | ||||||
| 4/24/26 | The Real AI Music Problem Has Nothing to Do With AI | Send us Fan Mail The AI music panic doesn't match the math. The global music industry generated $105 billion in 2023. AI music accounts for about 1.5% of actual streams. For the median independent artist, the competitive pressure from AI works out to roughly $45 a year. The existential threat framing is wrong — and the creators who understand that have a significant advantage over the ones who don't. In this episode: The manifesto — what the actual numbers say about AI and the music industr... | 15m 26s | ||||||
| 4/21/26 | Poppycock: A Former Musician on AI, MCP, and Creative Joy | Send us Fan Mail Roy Brennan trained as a classical bass-baritone at the Royal Northern College of Music. He played keyboards in bands. He owned a DX7, a Jupiter, a Juno-06, an Akai S900 sampler. He's heard every version of "that's not a real instrument" that exists — and he's not impressed by any of it. Now he's doing some of the most sophisticated AI music production work we've seen in this space. In this episode, Roy walks us through the journey from his first Suno session (which he desc... | 29m 22s | ||||||
| 4/17/26 | Why I'm Not Impressed by Your Prompt | Send us Fan Mail Prompts matter. But somewhere along the way the AI music community turned them into the destination instead of the on-ramp. Threads with hundreds of upvotes sharing "the perfect Suno prompt" like it's the secret to the kingdom. Creators copying those prompts, generating something generic, and wondering why their music sounds like everyone else's. The truth is simple: a great prompt is the equivalent of knowing how to write words. It's necessary. It's not sufficient. In this e... | 20m 18s | ||||||
| 4/14/26 | Red Lab Conversations: William Harper — Commanding the Machine | Send us Fan Mail William Harper is a classically trained pianist from Guyana who has been playing since he was five years old. Cruise ships. Studio sessions. Worship music. Decades of real musical experience across multiple instruments. And now he's one of the most thoughtful voices in the AI music space on what it actually means to direct these tools rather than just use them. In this conversation, William breaks down how he discovered AI music through a mentor who was using it at a level th... | 36m 46s | ||||||
| 4/10/26 | Your Track Isn't Done When Suno Is Done With It | Send us Fan Mail Most AI music creators make the same mistake — they treat the raw export as the finished product. It isn't. What Suno hands you is raw material. What you do with it is where the real work begins. In this episode: The manifesto — why a raw export is not a finished track and what that gap is costing your catalog. The 60-second diagnostic — four numbers that tell you in under a minute whether your track is ready for the next step or needs more work. Run this on every export befo... | 23m 38s | ||||||
| 4/7/26 | Red Lab Conversations: Bob Sluys — From Roy Clark to the Suno Crack Pipe | Send us Fan Mail Bob Sluys has been in music for over 50 years. Trumpet player. Bass player. Tuba player at Magic Mountain — long story. He toured with Roy Clark, played funk up and down the West Coast in the late 70s, spent a decade in LA chasing a record deal, and ended up as a musical director on the Vegas Strip. He was also one of the people kicking and scratching against AI music. His words, not mine. Then someone showed him Suno. And within minutes, a JG BeatsLab ad hit his feed. In thi... | 26m 02s | ||||||
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| 4/3/26 | Get Better, Not Bitter — What Every AI Music Creator Needs to Hear Right Now | Send us Fan Mail 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... | 19m 36s | ||||||
| 3/28/26 | Suno v5.5 — What We Actually Found (Emergency Episode) | Send us Fan Mail Suno v5.5 dropped this week with three new features — Voices, Custom Models, and My Taste. We went straight into testing. This unscheduled episode covers what we actually found: the Voices sweet spot most people will miss, why Custom Models might be more important than Voices, and the My Taste feature nobody is talking about. Plus — the full v5.5 guide is available on the website right now. RLA members already have it. UPDATE: Suno V5.5 Guide is now available on our website. ... | 22m 29s | ||||||
| 3/27/26 | The Directors Are Playing Offense. Everyone Else Is Playing Defense. | Send us Fan Mail Two things are happening simultaneously in AI music right now. Most people are only paying attention to one of them. The first is the industry legal battle — lawsuits, injunctions, sledgehammers swinging at everything in sight. The second is the creators quietly building. The ones nobody's writing about. This episode is about both — and why the second group is going to win. In the first segment I push back hard on the lazy narrative about AI music creators. The caricature of ... | 16m 13s | ||||||
| 3/18/26 | Stop Gambling With Prompts. Start Directing the AI. | Send us Fan Mail Most AI music tracks sound amateur for one reason. Not lack of talent. Lack of specificity. In this episode I break down the craft of prompting — what the AI actually responds to, and why vague inputs produce average output every single time. We cover the 3-word fix that transforms your results immediately: sub-genre, mood, and texture. These aren't labels — they're commands. Sub-genres load specific instrument packages. Mood words are harmonic instructions, not feelings. Tex... | 17m 54s | ||||||
| 3/12/26 | The One-Platform Trap: What We Found Testing Mureka | Send us Fan Mail There's a trap that doesn't look like a trap. It looks like expertise. The creator who's spent six months mastering Suno — knows the syntax cold, built Personas, genuinely good at it — and has never opened another platform. The deeper your expertise in one tool, the more invisible its blind spots become. In this episode we break down the One-Platform Trap and what we actually found when we took Mureka V8 into the lab. In Red Lab Protocol #5, we ran 27 tracks across 9 tests on... | 23m 59s | ||||||
| 3/6/26 | The Notebook Problem — Why AI Music Matters More Than You Think | Send us Fan Mail Every week I get emails from people in their 50s, 60s, 70s who've been writing lyrics their whole life. The notebook sat in a drawer for decades. The industry debate is happening in boardrooms. The real story is happening in living rooms. This one's for everyone who's been waiting for permission to start. Links: jgbeatslab.com/ai-music-library jgbeatslab.com/music-books jgbeatslab.com/newsletter Red Lab Conversations is produced by JG BeatsLab LLC, an AI music education com... | 5m 17s | ||||||
| 2/27/26 | Nobody's Coming to Save You — A Message for Independent AI Musicians | Send us Fan Mail The music industry is building tools to protect incumbents. Not one of them is designed to help independent AI creators. I break down why you're not at the table, why that won't change, and why the only move is to build your own infrastructure. Links: jgbeatslab.com/ai-music-library jgbeatslab.com/music-books jgbeatslab.com/newsletter Red Lab Conversations is produced by JG BeatsLab LLC, an AI music education company building the methodology, research, and community for s... | 5m 58s | ||||||
| 2/20/26 | Lane 2 Is Getting Crowded — And That's a Good Thing | Send us Fan Mail More people are entering Lane 2 — human-authored, AI-assisted music. I break down why a crowded lane validates the market, what separates the floor from the ceiling, and why Lane 1 spammers are actually doing you a favor. Links: jgbeatslab.com/ai-music-library jgbeatslab.com/music-books jgbeatslab.com/newsletter Red Lab Conversations is produced by JG BeatsLab LLC, an AI music education company building the methodology, research, and community for serious creators working i... | 6m 33s | ||||||
| 2/13/26 | 200 Songs, 2 Lanes, and Zero Permission | Send us Fan Mail Quick housekeeping: the JG BeatsLab podcast is evolving. Starting now, each episode is the audio from our weekly YouTube videos. To kick things off, this episode combines our first three videos into one session — what I've learned from 200+ AI songs, the Lane 1/Lane 2 problem in AI music, and why nobody's coming to give you permission. Same content, same energy, new format. New episodes every week. Be sure to subscribe to our YouTube channel as well: https://www.youtube.com... | 21m 07s | ||||||
| 1/26/26 | NAMM 2026: What the Music Industry Got Wrong About AI | Send us Fan Mail I just spent three days at NAMM listening to the music industry argue about AI music. The education sessions felt defensive, anxious, and filled with one-way monologues about why AI is bad for music. But they're fighting a caricature — and conflating two very different things. In this episode, I break down: → The "junk food for the brain" argument (and why it falls apart) → The two lanes: spam vs. human-authored, AI-assisted production → Why the 97% stat actually pro... | 24m 24s | ||||||
| 1/16/26 | You Don't Own Your AI Music (Unless You Do This) | Send us Fan Mail Do you actually own your AI music? The answer might surprise you. In this episode, I break down the legal reality of AI-generated content — what the US Copyright Office has said, why your "hit song" might not be protectable, and the hybrid workflow that establishes real human authorship. You'll learn: Why prompts aren't copyrightableThe "Human Moat" conceptThe Studio-First Method for creating protectable workWhy sync deals and royalties depend on documented authorshipThis isn... | 8m 43s | ||||||
| 1/16/26 | The 5 Mistakes That Scream "AI Slop" | Send us Fan Mail These are the tells that make curators hit "decline" in 3 seconds. In this episode, I walk through the 5 most common mistakes I hear as a Submithub curator — and exactly how to fix each one. The mistakes: The Robotic VocalThe AABB Rhyme CurseSinging the TagsOne-Shot ObsessionChoosing Instrument Over VocalHomework: Go listen to your last release. Which of these five did you commit? Be honest. Books & resources: jgbeatslab.com/music-books Red Lab Conversations is produced ... | 10m 24s | ||||||
| 1/16/26 | Why 90% of AI Music Is Garbage (And How to Be the 10%) | Send us Fan Mail Most AI music isn't bad because of the AI. It's bad because the person using it doesn't know what they're doing. In this episode, I break down why the "slot machine" approach to AI music is killing your output — and what separates the 10% who sound professional from the 90% who sound like garbage. You'll learn: Why extending a "7 out of 10" track is a waste of creditsThe mindset shift from gambler to directorThe Golden Seed Method for finding tracks worth keepingIf you're tir... | 11m 45s | ||||||
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Chart Positions
4 placements across 4 markets.
Chart Positions
4 placements across 4 markets.