Modern WisdomHow AI and TikTok Are Breaking the Music Industry - Rick Beato
CHAPTERS
- 0:00 – 2:21
Stage spectacle, safety, and the insane stakes of live production
Chris and Rick open with a darkly funny hypothetical about Beyoncé’s on-stage stunt risks, which leads into a broader discussion of stage safety. Rick recounts pyro logistics at major shows and how modern touring has to manage liability and precision night after night.
- •Beyoncé car-top moment and the ‘insurance policy’ reality for megastars
- •Pyrotechnics as a major risk factor in live shows
- •Metallica example: in-ear cues and “safe zones” on stage
- •How heat, flames, and choreography create constant liability
- •Accidents used to be more common; modern tours are tighter controlled
- 2:21 – 6:17
How pop songs get made now: writers’ rooms, credits, and social-media-first careers
Rick explains that many pop stars contribute less to writing than audiences assume, often acting more as curators or editors of songs crafted by professional writers. He argues that today’s biggest shift is that artists must also be their own promotion department, with TikTok-era marketing driving hit potential.
- •Audience confusion: singer ≠ primary songwriter in many modern pop cases
- •Professional songwriters realize an artist’s ‘story idea’ or deliver finished songs
- •Historical contrast: rock bands typically wrote their own material
- •Success increasingly requires being fluent in social media and content creation
- •Virality (especially TikTok) is now central to breaking a single
- 6:17 – 10:24
Too many writers? Authenticity, audience ‘lore,’ and the Johnny Cash ‘Hurt’ counterexample
They unpack why listeners feel uneasy seeing huge songwriting credit lists and how audiences often project authenticity onto performers. Rick contrasts modern pop ‘lore’ with older norms of separating singer and writer, then illustrates how performance can authentically ‘own’ a song via Johnny Cash’s version of “Hurt.”
- •Why 10–15 writers on a simple track feels suspect to fans
- •Audience creates the authenticity narrative more than artists explicitly claim it
- •Nashville norm: performers often aren’t expected to explain lyrics they didn’t write
- •‘Hurt’ as an example of interpretive ownership overriding authorship
- •Rick Rubin’s role and Johnny Cash’s initial hesitation with the song’s harmony
- 10:24 – 13:48
Producer-driven vs artist-driven: Max Martin model and the Nashville writing factory
Rick defines producer-driven songs using Max Martin/Dr. Luke-style workflows where tracks and lyrics can be completed before the artist arrives. He then explains Nashville’s highly structured co-writing system, why sessions often have three writers, and how ‘track guys’ shifted country into producer-first creation.
- •Producer-driven definition: the track, hooks, and lyrics prebuilt by producers
- •Most songwriting starts with music/melody first; lyrics often follow
- •Nashville co-writes: three-person rooms and publishing-company incentives
- •Track guys/producers bring fully built beds; radio country becomes producer-led
- •Industrial pace: writers and producers creating multiple songs per week
- 13:48 – 23:39
Nashville’s elite session ecosystem: ‘Navy SEAL’ musicians and live-in-studio quality
Rick and Chris marvel at Nashville session players’ speed and precision, where demos can be cut almost immediately. Rick shares a story producing a track with top players, emphasizing the minimal ‘producer magic’ needed when musicians deliver near-perfect takes and performances.
- •Demo sessions: listen once, write parts, record immediately
- •Session players’ reputation for one- or two-take perfection
- •Rick’s video session with Tom Bukovac and high-end Nashville lineup
- •Live-style recording with studio-grade sound and real-time harmonies
- •Micro-level standards: punching a single note for a fingernail touch
- 23:39 – 28:14
What pop stars ‘add’ now: pre-fame platforms, athletic performance, and rare self-contained creators
They explore what differentiates modern pop stars when songwriting can be outsourced and production is standardized. Rick highlights outliers like Billie Eilish/Finneas, but argues fame, performance, dance, and platform often matter as much as musicianship for mainstream pop stardom.
- •Billie Eilish/Finneas as a rare self-contained writing/production unit
- •Modern pipeline: fame often precedes music success (Disney, TikTok influencers)
- •Dance/athleticism as a core part of pop’s value proposition
- •Some artists remain true songwriters/performers (Ed Sheeran, Chris Martin)
- •Speculation about ‘prefab DJs’ as the next platform-driven product
- 28:14 – 37:02
Algorithmic era trends: the end of shared listening and the collapse of subcultures
Rick argues there’s no single dominant musical trend because streaming platforms silo audiences into personalized recommendation loops. They contrast the old radio/MTV era—where moments like Nirvana reshaped culture—with today’s fragmented landscape and attention economy dynamics.
- •Algorithmic siloing reduces shared musical experiences
- •Radio/MTV once created mass cultural pivots (e.g., Nirvana)
- •Old promotion machine: regional radio teams, indies, payola-adjacent systems
- •Recommendation engines (Spotify/YouTube) intensify similarity and repetition
- •Homogenization pressures make subcultures harder to form and persist
- 37:02 – 48:46
Music is ‘too easy’ now: same tools, same presets, fewer pros, and a more uniform sound
Rick explains how modern digital workflows and modeling gear create a shared palette that encourages sameness. He links the decline in financial upside to fewer high-level producers and mixers in some genres, and contrasts older records’ punch and dynamics with sample-heavy modern production.
- •Digital modeling amps and shared algorithms reduce sonic uniqueness
- •DAWs and presets standardize production decisions across artists
- •Lower budgets reduce the role of elite producers/mixers (especially in rock)
- •Examples of ‘massive’ legacy mixing (Andy Wallace, Brendan O’Brien)
- •Differentiation shifts from soundcraft to the singer and marketing presence
- 48:46 – 1:00:29
TikTok’s bidirectional influence: designing for virality and the elusive ‘hit formula’
They discuss how TikTok doesn’t just amplify songs; it changes how songs are written to create a 15-second ‘moment.’ Rick shares how he studies data tools to track spikes and gives examples of older songs resurfacing via Shorts/TikTok, while conceding true virality remains hard to engineer.
- •TikTok impacts both discovery and creation: music built for short-form moments
- •Rick’s ‘figureoutable’ hit idea vs real unpredictability
- •Chartmetric-style analytics to trace social spikes and follower growth
- •Imogen Heap examples: specific bridge/section becomes the meme anchor
- •Fleetwood Mac ‘Dreams’ moment shows accidental virality and label behavior shifts
- 1:00:29 – 1:04:59
From formats to fad cycles: why genres rise and fall (nu metal to country-pop)
They zoom out to how the industry replicates what worked until it burns out, using nu metal and post-grunge as examples. Rick proposes that rock losing its blues DNA weakened broad appeal, while country expanded by adopting pop production aesthetics and radio-friendly loops.
- •Labels and creators chase replicable formats to reduce risk
- •Nu metal’s dominance and sudden decline as an example of trend exhaustion
- •Hypothesis: rock’s disconnection from blues reduced mainstream stickiness
- •Country’s rise aided by popification (loops, modern production, crossover)
- •Nashville producer ecosystem (e.g., Joey Moi) as a center of hit-making
- 1:04:59 – 1:14:07
Why country is booming: pop crossover, cultural moments, and scene-to-country migration
Chris shares a personal ‘conversion’ story from Nashville’s Broadway scene, while Rick outlines how bro-country and track-driven production paved the way for mass appeal. They note how rock listeners migrated to country for guitars and accessible songwriting, and how artists across genres pivoted into country.
- •Country’s mainstream surge tied to pop-like production and hooks
- •Chris’s Broadway ‘Tequila’ moment as an example of communal ritual
- •Bro-country era and the arrival of track guys transforming the sound
- •Rock fans moving to country as rock radio relevance declined
- •High-profile pivots (Post Malone, Beyoncé) and metal/scene musicians in country bands
- 1:14:07 – 1:18:26
AI artists arrive: Spotify playlists, ‘The Velvet Sundown,’ and the copyright incentive problem
Rick argues AI music is already being tested in the marketplace via playlists and suspiciously fast-growing ‘artists.’ He explains his policy view—fully generative AI shouldn’t be copyrightable—to remove incentives for platforms to flood catalogs with zero-cost content that displaces human payouts.
- •AI music already present in mood/jazz/ambient playlists with huge stream counts
- •Case study: ‘The Velvet Sundown’ as a possibly fake, AI-branded ‘band’
- •Rapid growth patterns (0 to 600k followers) raise bot/coordination concerns
- •Rick’s Senate hearing experience and the copyrightability argument
- •Platform incentive: fill playlists with AI to reduce royalty outflows
- 1:18:26 – 1:24:27
Ethics and detection: where the line is between AI assistance and AI replacement
They debate whether Spotify should ban AI music and how blurry authorship becomes when AI is used for parts of the workflow. The conversation shifts to listener expectations—story, meaning, and human intention—and the risk of being ‘catfished’ by music that performs emotion without lived experience.
- •Ban vs label: enforcement is hard because AI can be ‘covered’ by humans
- •‘15 writers is basically AI anyway’—team-made pop as a philosophical challenge
- •Why listeners care: narrative, intention, and emotional backstory
- •Need for disclosure/identification of AI-generated artists and tracks
- •AI as both competitor and amplifier tool for real creators
- 1:24:27 – 1:36:05
AI as a tool: prompting craft, voice cloning, and practical creative workflows
Rick describes using AI for titles, thumbnails, and idea iteration, arguing prompting requires refinement and taste even if it’s not equivalent to musicianship. They also discuss voice cloning via ElevenLabs, including verification, ethical ownership of voice likeness, and how indistinguishable inserts are already possible.
- •Prompt iteration as a creative workflow (titles via Gemini, visuals via image models)
- •AI’s strongest near-term music uses: mastering and potentially mixing variations
- •ElevenLabs voice training, verification, and multiple ‘mic profile’ versions
- •Chris discovers a default voice sounding like him—likeness and rights questions
- •AI audio inserts can be unnoticed by audiences, raising disclosure concerns
- 1:36:05 – 1:47:08
How musicians make money now: live revenue, streaming realities, and Spotify’s trade-offs
Rick outlines how live performance has become the most dependable income source across levels, while streaming meaningfully rewards only top-tier acts. They critique missing credits/metadata in streaming apps and weigh Spotify’s consumer convenience against artist frustration over compensation and platform power.
- •Live is the most reliable monetization path; ticket prices reflect this shift
- •Streaming pays well at the very top, poorly for the middle and bottom
- •Loss of liner notes: credits and performers often missing from Spotify UI
- •Spotify strengths: ease, playlists, discovery, and event alerts
- •Core artist complaints: compensation, playlist power, and AI flooding risks
- 1:47:08 – 2:01:34
Future monetization: diversification, entrepreneurship, and ‘human-only’ platforms
They close by discussing how modern musicians must stack income streams—touring, merch, lessons, VIP, products, and content—skills that used to be handled by teams. They speculate about blockchain verification and the potential emergence of ‘human-only’ music platforms as AI content proliferates.
- •Artists increasingly need a multi-stream business model (merch, VIP, lessons, products)
- •Spotify as a funnel: geo-targeted shows, merch shelves, and discovery features
- •Risk: business skills selection pressure may crowd out ‘pure’ musicians
- •Possible solutions: blockchain verification and clearer authenticity signals
- •Market opportunity for ‘organic’/human-only music platforms amid AI expansion
