Feed economy: How Each Platform Manufactures Dependency Loops
Why creators feel burned out, and what platforms don’t want you to understand about their invisible incentive systems
feed-economy-how-each-platform-manufactures-dependency-loops
Platform Economics
Creator Growth
How social media platforms manipulate creators
Have you ever felt that being a creator today means slowly giving up what you’re best at, what you love most?
Like your voice is being reshaped, quietly and algorithmically, into something else.
Something that fits. Performs. Converts.
It is not just content anymore.
You are producing what the platform wants you to become. And the strangest part?
Most people do not even notice it is happening.
Melanie Murphy, an Irish creator with over 800,000 followers, described the hidden cost of this evolution: “There’s no off button in this job. The algorithms never stop. You can’t pause the internet because you get sick”
This is not metaphor. It is the lived reality of half of creators. A survey by advertising agency Billion Dollar Boy found that fifty percent have experienced burnout and thirty‑seven percent have thought about quitting entirely . by The Guardian
The default advice to creators today sounds like this:
“Just make great content.”
But “great” is platform-specific.
It’s defined by what the platform wants to optimize, not what your audience actually needs.
The Platform Trap
Platforms aren't neutral distribution tools. They're incentive engines with built-in behavioral defaults.
Platforms no longer simply distribute content. They now encode behavior.
Every swipe, like, scroll, and pause trains a system, and in return, that system reshapes the user. What began as tools for creativity have evolved into closed systems for behavioral engineering. The implications are asymmetric. Platforms accrue compounding data and capital. Creators accumulate temporary attention and creative fatigue.
This essay unpacks how four platforms, TikTok, Substack, YouTube, and Podcasts structure dependency loops. Not through obvious rules, but through invisible defaults that steer content behavior, format design, and monetization strategy.
1. TikTok: When Viral Means Disposable
Growth feels exponential, but your leverage rounds to zero. Welcome to attention without ownership.
• TikTok mid-tier creators after the May 20 algorithm change
Many reported extreme impact after TikTok reordered its rewards:
“Revenues plunge by up to 90 percent” within hours of the update
A stark illustration of how hidden algorithmic shifts can immediately redefine who or what is rewarded.
A Closed System Masquerading as a Discovery Engine
TikTok optimizes for velocity. It’s built on repetition, not relationships.
From the outside, it looks like a meritocracy of short-form storytelling. In practice, it is a frictionless loop of disempowerment.
The most critical point is this: TikTok rewards behavior that aligns with its own retention goals, not the creator’s goals. That’s why outbound links are punished. That’s why engagement tools are limited. That’s why content must re-perform with each upload. There is no archive effect. No subscriber base you own. Only constant reinvention, scored by a machine.
In a bold move that’s poised to reshape the e-commerce landscape within its ecosystem, TikTok has announced plans to ban links to external e-commerce sites, notably giants like Amazon.
Creators may go viral. But they never escape the gravity.
Incentives do not reward independence. They punish it.
Strategic Implication:
Creators must assume they are temporary nodes in TikTok’s system, not participants in a long-term audience relationship. Brand equity built here is extractive by default. The long-term game must happen elsewhere.
Signals to Watch:
TikTok Shop integrations that favor in-app conversion
No preview or indexing for outbound content
Growth ceilings after initial virality unless paid
[Simulated scenario]
First Diagram: Platform Control Dashboard
This diagram simulates a "server room monitoring system" - like an internal TikTok control panel for tracking creator behavior. The chart is divided into three sections:
Left Side:
Platform Control Systems
No Outlink Preview: Shows how TikTok blocks external links, with outbound CTR penalized by 67%, status showing "BLOCKING AUDIENCE EXPORT"
Growth Spike → Flatline: Demonstrates the inevitable decay pattern after virality, with viral windows lasting only 12-48 hours, followed by 89% viewership decline with "NO ARCHIVE EFFECT"
Virality Window: Peak content performance lasts just 12-24 hours, maximum lifespan 72 hours, forcing "CONSTANT REINVENTION REQUIRED"
Center:
Algorithm Behavior Modification Matrix This is the chart's core, showing the contrast between creator behaviors and platform responses:
When creators attempt independence (posting outbound links, cross-platform content) → Platform punishment (reduced reach, shadow throttling)
When creators align with platform ecosystem (TikTok Shop, platform-native content) → Platform rewards (algorithm boost, priority distribution)
Right Side:
In-Platform Monetization Control
TikTok Shop conversion rate 23% vs external links only 3%
Bar chart shows in-platform purchases far exceed external traffic
Creator independence score only 12%, platform revenue share 67%
This diagram reveals how TikTok uses technical mechanisms to systematically punish creator independence while rewarding platform dependency behaviors.
[Simulated scenario]
Second Diagram: Attention Loop Chart
This chart tracks one creator's performance data across 40 consecutive videos, with upload number on the X-axis and view count on the Y-axis.
Line Pattern:
The black line shows extremely irregular peaks and valleys with no "cumulative growth" trend. Even after a video gets 9 million views, the next one might only get 500K, proving there's "no archive effect."
Algorithm Intervention Markers:
Black triangle flags (B): Boosted - content pushed by the algorithm to viral status
White triangle flags (T): Throttled - content restricted by the algorithm
Dashed triangle flags (M): Muted - content shadow-banned
Key Findings:
The right-side annotation shows the viral peak (9.2M views) lasted only 18 hours before returning to baseline. No matter how hard creators work, they cannot "control" or "predict" their next viral moment.
Bottom Insight:
"Peak performance occurs unpredictably regardless of content quality, creator effort, or posting consistency. Algorithm decides viral windows independent of creator strategy, ensuring constant platform dependency for revenue maintenance."
This chart proves TikTok is an "endless content treadmill" - creators must constantly produce but can never build predictable growth trajectories or audience assets.
Virality is completely unpredictable. It has nothing to do with content quality, creator effort, or launch strategy. The algorithm alone decides when a “viral window” opens, forcing creators to stay dependent on the platform just to sustain their income.
The core idea:
On TikTok, virality equals disposability. A creator might blow up, but they never escape the platform’s gravitational control. Every product decision is optimized for platform dependency, not long-term creator success.
2. Substack: Writing as Funnel Architecture
Every post becomes a proxy for trust velocity, not just creative output.
From Newsletter to Intent Engine
Substack sells the dream of creative independence. And structurally, it delivers more than most platforms: email ownership, subscription tiers, and migration freedom. But independence and control are not the same.
Substack’s design creates ambient dependency through nudges.
Notes, the platform’s micro-content layer, isn’t a social tool. It’s a funnel disguised as chatter. Creators are incentivized to simulate conversation not to build community, but to heat up cold readers for a future conversion event.
Dan Shipper’s method, open-ended questions, visibility threads, and staggered calls-to-action, is less about writing and more about temperature modulation. The emotional slope between “familiar stranger” and “paying subscriber” is the core product.
Substack does not sell reach. It sells trust velocity.
And the architecture rewards those who manufacture that slope carefully.
[Simulated scenario]
Visual: The Substack Funnel Overlay Map
From Cold Reader to Paid Subscriber: Substack’s Engineered Conversion System
This visual tracks the full journey from passive reader to paid subscriber, showing how Substack transforms writing into a behaviorally engineered funnel. Writing is not simply expression. It is structured progression.
Primary Conversion Stages (Top Flow):
Email Inbox → Entry point for cold readers
Notes → Lightweight temperature-warming layer
Reader Click → Signals intent and increases engagement temperature
Subscription CTA → Paid Conversion → From attention capture to revenue event
Retention Loops (Lower Layer):
Each loop reinforces the reader’s progression through micro-incentives and behavior shaping.
Open Rate Loop: Subject line → Preview text → Future open probability
2 Notes Loop: Open-ended question → Response → Follow-up → Visibility → Trust signal
CTA Exposure Loop: Perceived value → Soft ask → Benefit framing → Hard CTA → Social proof
$ Conversion Loop: Premium preview → FOMO → Tiered value → Payment → Retention → Upsell
Heat Calibration Meter (Bottom Bar):
Visualized as a temperature scale from “Familiar Stranger” to “Conversion-Ready,” the thermometer maps reader warming tactics. Each stage includes conversion probability ranges and trigger mechanics.
Core Insight:
Beneath the visual:
“Each post = a funnel step, not an act of creativity.”
Substack writing is not about publishing. It is about orchestrating behavioral progression toward monetization.
[Simulated scenario]
Visual: Substack Notes Interaction Heatmap
What Actually Works in Notes: A Psychological Map of Reader Activation
This matrix visualizes how different types of content perform inside Substack Notes, using border styles and fills to indicate interaction intensity.
Content Type Performance Matrix:
Open-ended Questions (Top Left):
“What’s the biggest mistake you’ve made in [topic]?” → 87% interaction (bold black border)
“How do you deal with [common pain point]?” → 73% interaction (bold black border)
“Tell me your experience using [tool]” → 42% interaction (dashed border)
Provocative Statements (Top Right):
“Most [industry] advice is completely wrong.” → 94% interaction (black fill, highest tier)
“I used to believe [myth], now I know better.” → 68%
“Unpopular opinion: [statement]” → 35%
Value-driven statements and vulnerability posts follow similar logic.
Interaction Psychology Breakdown (Center Layer):
Explains high-performing triggers and their psychological foundations:
Controversy / Anti-mainstream takes → Activates tribal defense reflex
Open questions → Zeigarnik effect: unfinished thoughts drive engagement
Personal failure stories → Reciprocity through shared vulnerability
Specific frameworks → Immediate utility signals trustworthiness
Strategic Pattern Sequence (Bottom Bar):
The high-conversion Notes cadence:
“Controversial take → Follow-up question → Value delivery → Soft CTA”
This flow converts 67% more newsletter subscribers than random posting.
Right Panel: Trust Velocity Analysis
Compares interaction intensity with time-to-subscribe:
High-interaction Notes: average conversion in 2.3 days
Low-interaction Notes: 15.2 days
Reveals Notes as a behavioral temperature sensor, not a casual social feed.
Strategic Implication:
Creators on Substack are not just writers. They are funnel architects. Every post, note, and CTA is either accelerating or stalling the conversion sequence.
Signals to Watch:
Algorithmic boosts for Notes-based engagement
Newsletter CTA redesigns that reward funnel depth
Future integrations that mimic CRM logic (not just CMS)
3. YouTube: Editing Is the Real Product
Success favors those who engineer retention, not those who chase ideas.
The Platform Where Structure Becomes Strategy
YouTube is the only major platform where content depth and architectural clarity are still rewarded at scale. But even this reward system is not neutral. It favors a particular form of thinking: narrative engineering.
Ali Abdaal’s pivot to hour-long videos in 2024 was not artistic. It was mathematical. Longer view durations feed into channel-level performance metrics. That, in turn, fuels recommendation loops and playlist clustering.
The system isn’t built for bursts of genius. It’s built for predictable retention curves. The most successful creators treat editing as behavioral modeling. They experiment not with ideas, but with fatigue timing, emotional arcs, and micro-hooks.
YouTube looks like a video platform. It is actually a time allocation market.
[Simulated scenario]
Strategic Implication:
Winning on YouTube requires understanding its behavioral gradients. Editing becomes an economic function. Scriptwriting becomes a funnel mechanic. The creator is no longer the star, the structure is.
Signals to Watch:
First-30-second retention benchmarks dictating growth
Rise of chaptered videos as modular attention units
Channel clustering strategies that treat libraries as ecosystems
[Simulated scenario]
4. Podcasts: Intimacy Is Eroding
What began as permissioned listening is collapsing into feed-driven skimming.
Losing the Moat of Attention Depth
Podcasts historically offered refuge from platform manipulation. They ran on RSS. They respected attention. There were no feeds, only relationships. That era is ending.
Spotify and YouTube are pulling podcasting into the feed economy. The rise of video-first formats, timestamp UX, and clip sharing reshapes consumption into scanning, not listening. Completion rates are dropping. Skimmed consumption is rising.
In trying to expand discovery, platforms are killing depth.
Listeners no longer sit with you. They bounce between you and a thumbnail stack.
The intimacy that once made podcasts powerful is now diluted by format creep.
[Simulated scenario]
This diagram analyzes the trend of podcasts losing their deep listening experience.
Podcast UX Evolution Timeline (Upper Section)
This timeline shows four critical stages in podcast consumption patterns:
RSS Era: Originally, podcasts were directly subscribed through RSS feeds, where users would listen to complete episodes, building deep listening relationships.
Platform Integration: When platforms like Spotify began intervening, we saw a "Drop-off Spike" with algorithms starting to influence content recommendations.
Visual Optimization: Platforms began emphasizing thumbnail optimization, making visual elements more important than audio content itself.
Chapter Skip Era: Users became trained for fragmented consumption, no longer listening linearly through complete content.
The dotted arrow below marks "Intimacy Decay," showing how this evolution gradually destroys podcasting's original deep connection.
Completion Rate vs Discovery Rate Chart (Middle Section)
This dual-axis chart is the most critical, revealing a negative correlation:
Left axis (solid line): Podcast completion rates declining from nearly 100% in 2020 to about 40% in 2024
Right axis (dashed line): Platform-driven discovery rates rising from 100% to nearly 500%
Key Insight:
Algorithm-driven content discovery increases exposure but simultaneously destroys deep listening relationships. The easier it becomes for users to discover new content, the less willing they are to focus on complete listening.
Signals to Watch (Right Section)
Three warning indicators show this trend is accelerating:
Spotify's visual-first interface: Thumbnails matter more than audio controls
Chapter skip becoming default behavior: Users habituated to fragmented consumption
YouTube Podcasts favoring thumbnail scanning: Browse behavior replaces intentional listening
Strategic Implication
The black box at the bottom emphasizes: Creators who built business models on "attention loyalty" must now redesign for "modular consumption." Visual UX, snippet logic, and timestamp design are no longer "nice-to-haves" but "core infrastructure."
The diagram's core argument is: Podcasts are degrading from deep "permissioned listening" to shallow "feed-driven skimming," and creators must adapt to this reality.
Conclusion: Escape Isn’t Exit, It’s Leverage
Platforms won’t change. But creators can shift the game by reclaiming control across distribution, identity, and monetization.
Burnout isn’t a personal failure. It’s a systemic feature of incentive structures that prioritize platform growth over creator well-being.
Each platform engineers its own version of creator success. But that success is conditional, temporary, and contingent on reinforcing the platform’s growth logic.
To escape the loop is not to exit the platform. That’s a false binary.
It’s to build systems that reclaim leverage: direct distribution, durable identity, audience portability, and financial upside aligned with time investment.
The smartest creators and product teams in 2025 are doing one thing in common.
They’re building off-platform insurance inside on-platform strategy.
Anchor Articles and Updates
Crisis Is Not the End. It’s a Catalyst for Product Growth. — Reframing the Narrative of Windsurf, Astronomer, and Cluely
Building Products in the AI Era: The Deep Logic of Speed, Content, and Data Ownership — If you’re building a new product in 2025, you’re not competing on functionality.
You’re competing on attention loops, learning velocity, and data leverage.
How AI Platforms Reshape Innovation: Subordination, Risk, and Workflow Strategy — Rethinking Product Strategy Under Model Governance
How AI Understands User Intent Before They Search: Commercial Decision Loops and the Invisible Funnel — Why pre-intent behavior is becoming more legible and monetizable
Inspired by Lenny’s Growth Inflections: AI and Personal Brands Rewiring Startup Growth — AI automation and personal brands are redefining startup growth inspired by Lenny Rachitsky’s Growth Inflections.
Why Growth Marketing Is Not Digital Marketing and Why This Distinction Matters — It’s not that your marketing strategy is flawed. You might just be addressing the wrong problem.
When AI Products Can’t Find PMF, Build a Landing Client Instead — PMF isn’t always found in the product, Sometimes, it starts with one strategic client
Content as a Revenue Tool: Shortening Time-to-Close in Startup Sales — Content that shortens sales cycles, Not just builds traffic
Building Revenue Systems When Scale Isn’t an Option — Profitability First: How Startup Teams Can Drive Revenue in Constrained Markets
Case Studies
Mountain Gentleman — They knew they needed to go digital but had no idea how to start.So we saw things through the rider’s eyes.It wasn’t just about buying gear because it felt like building out your dream GTR.Every part of the journey was designed to match that thrill.
CoinRank — CoinRank needed a fresh way to stand out in crypto. We created a short video strategy that turns complex info into quick, engaging clips that grab attention fast.
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Feed economy: How Each Platform Manufactures Dependency Loops
Why creators feel burned out, and what platforms don’t want you to understand about their invisible incentive systems
feed-economy-how-each-platform-manufactures-dependency-loops
Platform Economics
Creator Growth
How social media platforms manipulate creators
Have you ever felt that being a creator today means slowly giving up what you’re best at, what you love most?
Like your voice is being reshaped, quietly and algorithmically, into something else.
Something that fits. Performs. Converts.
It is not just content anymore.
You are producing what the platform wants you to become. And the strangest part?
Most people do not even notice it is happening.
Melanie Murphy, an Irish creator with over 800,000 followers, described the hidden cost of this evolution: “There’s no off button in this job. The algorithms never stop. You can’t pause the internet because you get sick”
This is not metaphor. It is the lived reality of half of creators. A survey by advertising agency Billion Dollar Boy found that fifty percent have experienced burnout and thirty‑seven percent have thought about quitting entirely . by The Guardian
The default advice to creators today sounds like this:
“Just make great content.”
But “great” is platform-specific.
It’s defined by what the platform wants to optimize, not what your audience actually needs.
The Platform Trap
Platforms aren't neutral distribution tools. They're incentive engines with built-in behavioral defaults.
Platforms no longer simply distribute content. They now encode behavior.
Every swipe, like, scroll, and pause trains a system, and in return, that system reshapes the user. What began as tools for creativity have evolved into closed systems for behavioral engineering. The implications are asymmetric. Platforms accrue compounding data and capital. Creators accumulate temporary attention and creative fatigue.
This essay unpacks how four platforms, TikTok, Substack, YouTube, and Podcasts structure dependency loops. Not through obvious rules, but through invisible defaults that steer content behavior, format design, and monetization strategy.
1. TikTok: When Viral Means Disposable
Growth feels exponential, but your leverage rounds to zero. Welcome to attention without ownership.
• TikTok mid-tier creators after the May 20 algorithm change
Many reported extreme impact after TikTok reordered its rewards:
“Revenues plunge by up to 90 percent” within hours of the update
A stark illustration of how hidden algorithmic shifts can immediately redefine who or what is rewarded.
A Closed System Masquerading as a Discovery Engine
TikTok optimizes for velocity. It’s built on repetition, not relationships.
From the outside, it looks like a meritocracy of short-form storytelling. In practice, it is a frictionless loop of disempowerment.
The most critical point is this: TikTok rewards behavior that aligns with its own retention goals, not the creator’s goals. That’s why outbound links are punished. That’s why engagement tools are limited. That’s why content must re-perform with each upload. There is no archive effect. No subscriber base you own. Only constant reinvention, scored by a machine.
In a bold move that’s poised to reshape the e-commerce landscape within its ecosystem, TikTok has announced plans to ban links to external e-commerce sites, notably giants like Amazon.
Creators may go viral. But they never escape the gravity.
Incentives do not reward independence. They punish it.
Strategic Implication:
Creators must assume they are temporary nodes in TikTok’s system, not participants in a long-term audience relationship. Brand equity built here is extractive by default. The long-term game must happen elsewhere.
Signals to Watch:
TikTok Shop integrations that favor in-app conversion
No preview or indexing for outbound content
Growth ceilings after initial virality unless paid
[Simulated scenario]
First Diagram: Platform Control Dashboard
This diagram simulates a "server room monitoring system" - like an internal TikTok control panel for tracking creator behavior. The chart is divided into three sections:
Left Side:
Platform Control Systems
No Outlink Preview: Shows how TikTok blocks external links, with outbound CTR penalized by 67%, status showing "BLOCKING AUDIENCE EXPORT"
Growth Spike → Flatline: Demonstrates the inevitable decay pattern after virality, with viral windows lasting only 12-48 hours, followed by 89% viewership decline with "NO ARCHIVE EFFECT"
Virality Window: Peak content performance lasts just 12-24 hours, maximum lifespan 72 hours, forcing "CONSTANT REINVENTION REQUIRED"
Center:
Algorithm Behavior Modification Matrix This is the chart's core, showing the contrast between creator behaviors and platform responses:
When creators attempt independence (posting outbound links, cross-platform content) → Platform punishment (reduced reach, shadow throttling)
When creators align with platform ecosystem (TikTok Shop, platform-native content) → Platform rewards (algorithm boost, priority distribution)
Right Side:
In-Platform Monetization Control
TikTok Shop conversion rate 23% vs external links only 3%
Bar chart shows in-platform purchases far exceed external traffic
Creator independence score only 12%, platform revenue share 67%
This diagram reveals how TikTok uses technical mechanisms to systematically punish creator independence while rewarding platform dependency behaviors.
[Simulated scenario]
Second Diagram: Attention Loop Chart
This chart tracks one creator's performance data across 40 consecutive videos, with upload number on the X-axis and view count on the Y-axis.
Line Pattern:
The black line shows extremely irregular peaks and valleys with no "cumulative growth" trend. Even after a video gets 9 million views, the next one might only get 500K, proving there's "no archive effect."
Algorithm Intervention Markers:
Black triangle flags (B): Boosted - content pushed by the algorithm to viral status
White triangle flags (T): Throttled - content restricted by the algorithm
Dashed triangle flags (M): Muted - content shadow-banned
Key Findings:
The right-side annotation shows the viral peak (9.2M views) lasted only 18 hours before returning to baseline. No matter how hard creators work, they cannot "control" or "predict" their next viral moment.
Bottom Insight:
"Peak performance occurs unpredictably regardless of content quality, creator effort, or posting consistency. Algorithm decides viral windows independent of creator strategy, ensuring constant platform dependency for revenue maintenance."
This chart proves TikTok is an "endless content treadmill" - creators must constantly produce but can never build predictable growth trajectories or audience assets.
Virality is completely unpredictable. It has nothing to do with content quality, creator effort, or launch strategy. The algorithm alone decides when a “viral window” opens, forcing creators to stay dependent on the platform just to sustain their income.
The core idea:
On TikTok, virality equals disposability. A creator might blow up, but they never escape the platform’s gravitational control. Every product decision is optimized for platform dependency, not long-term creator success.
2. Substack: Writing as Funnel Architecture
Every post becomes a proxy for trust velocity, not just creative output.
From Newsletter to Intent Engine
Substack sells the dream of creative independence. And structurally, it delivers more than most platforms: email ownership, subscription tiers, and migration freedom. But independence and control are not the same.
Substack’s design creates ambient dependency through nudges.
Notes, the platform’s micro-content layer, isn’t a social tool. It’s a funnel disguised as chatter. Creators are incentivized to simulate conversation not to build community, but to heat up cold readers for a future conversion event.
Dan Shipper’s method, open-ended questions, visibility threads, and staggered calls-to-action, is less about writing and more about temperature modulation. The emotional slope between “familiar stranger” and “paying subscriber” is the core product.
Substack does not sell reach. It sells trust velocity.
And the architecture rewards those who manufacture that slope carefully.
[Simulated scenario]
Visual: The Substack Funnel Overlay Map
From Cold Reader to Paid Subscriber: Substack’s Engineered Conversion System
This visual tracks the full journey from passive reader to paid subscriber, showing how Substack transforms writing into a behaviorally engineered funnel. Writing is not simply expression. It is structured progression.
Primary Conversion Stages (Top Flow):
Email Inbox → Entry point for cold readers
Notes → Lightweight temperature-warming layer
Reader Click → Signals intent and increases engagement temperature
Subscription CTA → Paid Conversion → From attention capture to revenue event
Retention Loops (Lower Layer):
Each loop reinforces the reader’s progression through micro-incentives and behavior shaping.
Open Rate Loop: Subject line → Preview text → Future open probability
2 Notes Loop: Open-ended question → Response → Follow-up → Visibility → Trust signal
CTA Exposure Loop: Perceived value → Soft ask → Benefit framing → Hard CTA → Social proof
$ Conversion Loop: Premium preview → FOMO → Tiered value → Payment → Retention → Upsell
Heat Calibration Meter (Bottom Bar):
Visualized as a temperature scale from “Familiar Stranger” to “Conversion-Ready,” the thermometer maps reader warming tactics. Each stage includes conversion probability ranges and trigger mechanics.
Core Insight:
Beneath the visual:
“Each post = a funnel step, not an act of creativity.”
Substack writing is not about publishing. It is about orchestrating behavioral progression toward monetization.
[Simulated scenario]
Visual: Substack Notes Interaction Heatmap
What Actually Works in Notes: A Psychological Map of Reader Activation
This matrix visualizes how different types of content perform inside Substack Notes, using border styles and fills to indicate interaction intensity.
Content Type Performance Matrix:
Open-ended Questions (Top Left):
“What’s the biggest mistake you’ve made in [topic]?” → 87% interaction (bold black border)
“How do you deal with [common pain point]?” → 73% interaction (bold black border)
“Tell me your experience using [tool]” → 42% interaction (dashed border)
Provocative Statements (Top Right):
“Most [industry] advice is completely wrong.” → 94% interaction (black fill, highest tier)
“I used to believe [myth], now I know better.” → 68%
“Unpopular opinion: [statement]” → 35%
Value-driven statements and vulnerability posts follow similar logic.
Interaction Psychology Breakdown (Center Layer):
Explains high-performing triggers and their psychological foundations:
Controversy / Anti-mainstream takes → Activates tribal defense reflex
Open questions → Zeigarnik effect: unfinished thoughts drive engagement
Personal failure stories → Reciprocity through shared vulnerability
Specific frameworks → Immediate utility signals trustworthiness
Strategic Pattern Sequence (Bottom Bar):
The high-conversion Notes cadence:
“Controversial take → Follow-up question → Value delivery → Soft CTA”
This flow converts 67% more newsletter subscribers than random posting.
Right Panel: Trust Velocity Analysis
Compares interaction intensity with time-to-subscribe:
High-interaction Notes: average conversion in 2.3 days
Low-interaction Notes: 15.2 days
Reveals Notes as a behavioral temperature sensor, not a casual social feed.
Strategic Implication:
Creators on Substack are not just writers. They are funnel architects. Every post, note, and CTA is either accelerating or stalling the conversion sequence.
Signals to Watch:
Algorithmic boosts for Notes-based engagement
Newsletter CTA redesigns that reward funnel depth
Future integrations that mimic CRM logic (not just CMS)
3. YouTube: Editing Is the Real Product
Success favors those who engineer retention, not those who chase ideas.
The Platform Where Structure Becomes Strategy
YouTube is the only major platform where content depth and architectural clarity are still rewarded at scale. But even this reward system is not neutral. It favors a particular form of thinking: narrative engineering.
Ali Abdaal’s pivot to hour-long videos in 2024 was not artistic. It was mathematical. Longer view durations feed into channel-level performance metrics. That, in turn, fuels recommendation loops and playlist clustering.
The system isn’t built for bursts of genius. It’s built for predictable retention curves. The most successful creators treat editing as behavioral modeling. They experiment not with ideas, but with fatigue timing, emotional arcs, and micro-hooks.
YouTube looks like a video platform. It is actually a time allocation market.
[Simulated scenario]
Strategic Implication:
Winning on YouTube requires understanding its behavioral gradients. Editing becomes an economic function. Scriptwriting becomes a funnel mechanic. The creator is no longer the star, the structure is.
Signals to Watch:
First-30-second retention benchmarks dictating growth
Rise of chaptered videos as modular attention units
Channel clustering strategies that treat libraries as ecosystems
[Simulated scenario]
4. Podcasts: Intimacy Is Eroding
What began as permissioned listening is collapsing into feed-driven skimming.
Losing the Moat of Attention Depth
Podcasts historically offered refuge from platform manipulation. They ran on RSS. They respected attention. There were no feeds, only relationships. That era is ending.
Spotify and YouTube are pulling podcasting into the feed economy. The rise of video-first formats, timestamp UX, and clip sharing reshapes consumption into scanning, not listening. Completion rates are dropping. Skimmed consumption is rising.
In trying to expand discovery, platforms are killing depth.
Listeners no longer sit with you. They bounce between you and a thumbnail stack.
The intimacy that once made podcasts powerful is now diluted by format creep.
[Simulated scenario]
This diagram analyzes the trend of podcasts losing their deep listening experience.
Podcast UX Evolution Timeline (Upper Section)
This timeline shows four critical stages in podcast consumption patterns:
RSS Era: Originally, podcasts were directly subscribed through RSS feeds, where users would listen to complete episodes, building deep listening relationships.
Platform Integration: When platforms like Spotify began intervening, we saw a "Drop-off Spike" with algorithms starting to influence content recommendations.
Visual Optimization: Platforms began emphasizing thumbnail optimization, making visual elements more important than audio content itself.
Chapter Skip Era: Users became trained for fragmented consumption, no longer listening linearly through complete content.
The dotted arrow below marks "Intimacy Decay," showing how this evolution gradually destroys podcasting's original deep connection.
Completion Rate vs Discovery Rate Chart (Middle Section)
This dual-axis chart is the most critical, revealing a negative correlation:
Left axis (solid line): Podcast completion rates declining from nearly 100% in 2020 to about 40% in 2024
Right axis (dashed line): Platform-driven discovery rates rising from 100% to nearly 500%
Key Insight:
Algorithm-driven content discovery increases exposure but simultaneously destroys deep listening relationships. The easier it becomes for users to discover new content, the less willing they are to focus on complete listening.
Signals to Watch (Right Section)
Three warning indicators show this trend is accelerating:
Spotify's visual-first interface: Thumbnails matter more than audio controls
Chapter skip becoming default behavior: Users habituated to fragmented consumption
YouTube Podcasts favoring thumbnail scanning: Browse behavior replaces intentional listening
Strategic Implication
The black box at the bottom emphasizes: Creators who built business models on "attention loyalty" must now redesign for "modular consumption." Visual UX, snippet logic, and timestamp design are no longer "nice-to-haves" but "core infrastructure."
The diagram's core argument is: Podcasts are degrading from deep "permissioned listening" to shallow "feed-driven skimming," and creators must adapt to this reality.
Conclusion: Escape Isn’t Exit, It’s Leverage
Platforms won’t change. But creators can shift the game by reclaiming control across distribution, identity, and monetization.
Burnout isn’t a personal failure. It’s a systemic feature of incentive structures that prioritize platform growth over creator well-being.
Each platform engineers its own version of creator success. But that success is conditional, temporary, and contingent on reinforcing the platform’s growth logic.
To escape the loop is not to exit the platform. That’s a false binary.
It’s to build systems that reclaim leverage: direct distribution, durable identity, audience portability, and financial upside aligned with time investment.
The smartest creators and product teams in 2025 are doing one thing in common.
They’re building off-platform insurance inside on-platform strategy.
Anchor Articles and Updates
Crisis Is Not the End. It’s a Catalyst for Product Growth. — Reframing the Narrative of Windsurf, Astronomer, and Cluely
Building Products in the AI Era: The Deep Logic of Speed, Content, and Data Ownership — If you’re building a new product in 2025, you’re not competing on functionality.
You’re competing on attention loops, learning velocity, and data leverage.
How AI Platforms Reshape Innovation: Subordination, Risk, and Workflow Strategy — Rethinking Product Strategy Under Model Governance
How AI Understands User Intent Before They Search: Commercial Decision Loops and the Invisible Funnel — Why pre-intent behavior is becoming more legible and monetizable
Inspired by Lenny’s Growth Inflections: AI and Personal Brands Rewiring Startup Growth — AI automation and personal brands are redefining startup growth inspired by Lenny Rachitsky’s Growth Inflections.
Why Growth Marketing Is Not Digital Marketing and Why This Distinction Matters — It’s not that your marketing strategy is flawed. You might just be addressing the wrong problem.
When AI Products Can’t Find PMF, Build a Landing Client Instead — PMF isn’t always found in the product, Sometimes, it starts with one strategic client
Content as a Revenue Tool: Shortening Time-to-Close in Startup Sales — Content that shortens sales cycles, Not just builds traffic
Building Revenue Systems When Scale Isn’t an Option — Profitability First: How Startup Teams Can Drive Revenue in Constrained Markets
Case Studies
Mountain Gentleman — They knew they needed to go digital but had no idea how to start.So we saw things through the rider’s eyes.It wasn’t just about buying gear because it felt like building out your dream GTR.Every part of the journey was designed to match that thrill.
CoinRank — CoinRank needed a fresh way to stand out in crypto. We created a short video strategy that turns complex info into quick, engaging clips that grab attention fast.
FAQ
01
What does a project look like?
02
How is the pricing structure?
03
Are all projects fixed scope?
04
Can I adjust the project scope after we start?
05
How do we measure success?
06
Do you offer ongoing support after project completion?
07
How long does a typical project last?
08
Is there a minimum commitment?
Feed economy: How Each Platform Manufactures Dependency Loops
Why creators feel burned out, and what platforms don’t want you to understand about their invisible incentive systems
feed-economy-how-each-platform-manufactures-dependency-loops
Platform Economics
Creator Growth
How social media platforms manipulate creators
Have you ever felt that being a creator today means slowly giving up what you’re best at, what you love most?
Like your voice is being reshaped, quietly and algorithmically, into something else.
Something that fits. Performs. Converts.
It is not just content anymore.
You are producing what the platform wants you to become. And the strangest part?
Most people do not even notice it is happening.
Melanie Murphy, an Irish creator with over 800,000 followers, described the hidden cost of this evolution: “There’s no off button in this job. The algorithms never stop. You can’t pause the internet because you get sick”
This is not metaphor. It is the lived reality of half of creators. A survey by advertising agency Billion Dollar Boy found that fifty percent have experienced burnout and thirty‑seven percent have thought about quitting entirely . by The Guardian
The default advice to creators today sounds like this:
“Just make great content.”
But “great” is platform-specific.
It’s defined by what the platform wants to optimize, not what your audience actually needs.
The Platform Trap
Platforms aren't neutral distribution tools. They're incentive engines with built-in behavioral defaults.
Platforms no longer simply distribute content. They now encode behavior.
Every swipe, like, scroll, and pause trains a system, and in return, that system reshapes the user. What began as tools for creativity have evolved into closed systems for behavioral engineering. The implications are asymmetric. Platforms accrue compounding data and capital. Creators accumulate temporary attention and creative fatigue.
This essay unpacks how four platforms, TikTok, Substack, YouTube, and Podcasts structure dependency loops. Not through obvious rules, but through invisible defaults that steer content behavior, format design, and monetization strategy.
1. TikTok: When Viral Means Disposable
Growth feels exponential, but your leverage rounds to zero. Welcome to attention without ownership.
• TikTok mid-tier creators after the May 20 algorithm change
Many reported extreme impact after TikTok reordered its rewards:
“Revenues plunge by up to 90 percent” within hours of the update
A stark illustration of how hidden algorithmic shifts can immediately redefine who or what is rewarded.
A Closed System Masquerading as a Discovery Engine
TikTok optimizes for velocity. It’s built on repetition, not relationships.
From the outside, it looks like a meritocracy of short-form storytelling. In practice, it is a frictionless loop of disempowerment.
The most critical point is this: TikTok rewards behavior that aligns with its own retention goals, not the creator’s goals. That’s why outbound links are punished. That’s why engagement tools are limited. That’s why content must re-perform with each upload. There is no archive effect. No subscriber base you own. Only constant reinvention, scored by a machine.
In a bold move that’s poised to reshape the e-commerce landscape within its ecosystem, TikTok has announced plans to ban links to external e-commerce sites, notably giants like Amazon.
Creators may go viral. But they never escape the gravity.
Incentives do not reward independence. They punish it.
Strategic Implication:
Creators must assume they are temporary nodes in TikTok’s system, not participants in a long-term audience relationship. Brand equity built here is extractive by default. The long-term game must happen elsewhere.
Signals to Watch:
TikTok Shop integrations that favor in-app conversion
No preview or indexing for outbound content
Growth ceilings after initial virality unless paid
[Simulated scenario]
First Diagram: Platform Control Dashboard
This diagram simulates a "server room monitoring system" - like an internal TikTok control panel for tracking creator behavior. The chart is divided into three sections:
Left Side:
Platform Control Systems
No Outlink Preview: Shows how TikTok blocks external links, with outbound CTR penalized by 67%, status showing "BLOCKING AUDIENCE EXPORT"
Growth Spike → Flatline: Demonstrates the inevitable decay pattern after virality, with viral windows lasting only 12-48 hours, followed by 89% viewership decline with "NO ARCHIVE EFFECT"
Virality Window: Peak content performance lasts just 12-24 hours, maximum lifespan 72 hours, forcing "CONSTANT REINVENTION REQUIRED"
Center:
Algorithm Behavior Modification Matrix This is the chart's core, showing the contrast between creator behaviors and platform responses:
When creators attempt independence (posting outbound links, cross-platform content) → Platform punishment (reduced reach, shadow throttling)
When creators align with platform ecosystem (TikTok Shop, platform-native content) → Platform rewards (algorithm boost, priority distribution)
Right Side:
In-Platform Monetization Control
TikTok Shop conversion rate 23% vs external links only 3%
Bar chart shows in-platform purchases far exceed external traffic
Creator independence score only 12%, platform revenue share 67%
This diagram reveals how TikTok uses technical mechanisms to systematically punish creator independence while rewarding platform dependency behaviors.
[Simulated scenario]
Second Diagram: Attention Loop Chart
This chart tracks one creator's performance data across 40 consecutive videos, with upload number on the X-axis and view count on the Y-axis.
Line Pattern:
The black line shows extremely irregular peaks and valleys with no "cumulative growth" trend. Even after a video gets 9 million views, the next one might only get 500K, proving there's "no archive effect."
Algorithm Intervention Markers:
Black triangle flags (B): Boosted - content pushed by the algorithm to viral status
White triangle flags (T): Throttled - content restricted by the algorithm
Dashed triangle flags (M): Muted - content shadow-banned
Key Findings:
The right-side annotation shows the viral peak (9.2M views) lasted only 18 hours before returning to baseline. No matter how hard creators work, they cannot "control" or "predict" their next viral moment.
Bottom Insight:
"Peak performance occurs unpredictably regardless of content quality, creator effort, or posting consistency. Algorithm decides viral windows independent of creator strategy, ensuring constant platform dependency for revenue maintenance."
This chart proves TikTok is an "endless content treadmill" - creators must constantly produce but can never build predictable growth trajectories or audience assets.
Virality is completely unpredictable. It has nothing to do with content quality, creator effort, or launch strategy. The algorithm alone decides when a “viral window” opens, forcing creators to stay dependent on the platform just to sustain their income.
The core idea:
On TikTok, virality equals disposability. A creator might blow up, but they never escape the platform’s gravitational control. Every product decision is optimized for platform dependency, not long-term creator success.
2. Substack: Writing as Funnel Architecture
Every post becomes a proxy for trust velocity, not just creative output.
From Newsletter to Intent Engine
Substack sells the dream of creative independence. And structurally, it delivers more than most platforms: email ownership, subscription tiers, and migration freedom. But independence and control are not the same.
Substack’s design creates ambient dependency through nudges.
Notes, the platform’s micro-content layer, isn’t a social tool. It’s a funnel disguised as chatter. Creators are incentivized to simulate conversation not to build community, but to heat up cold readers for a future conversion event.
Dan Shipper’s method, open-ended questions, visibility threads, and staggered calls-to-action, is less about writing and more about temperature modulation. The emotional slope between “familiar stranger” and “paying subscriber” is the core product.
Substack does not sell reach. It sells trust velocity.
And the architecture rewards those who manufacture that slope carefully.
[Simulated scenario]
Visual: The Substack Funnel Overlay Map
From Cold Reader to Paid Subscriber: Substack’s Engineered Conversion System
This visual tracks the full journey from passive reader to paid subscriber, showing how Substack transforms writing into a behaviorally engineered funnel. Writing is not simply expression. It is structured progression.
Primary Conversion Stages (Top Flow):
Email Inbox → Entry point for cold readers
Notes → Lightweight temperature-warming layer
Reader Click → Signals intent and increases engagement temperature
Subscription CTA → Paid Conversion → From attention capture to revenue event
Retention Loops (Lower Layer):
Each loop reinforces the reader’s progression through micro-incentives and behavior shaping.
Open Rate Loop: Subject line → Preview text → Future open probability
2 Notes Loop: Open-ended question → Response → Follow-up → Visibility → Trust signal
CTA Exposure Loop: Perceived value → Soft ask → Benefit framing → Hard CTA → Social proof
$ Conversion Loop: Premium preview → FOMO → Tiered value → Payment → Retention → Upsell
Heat Calibration Meter (Bottom Bar):
Visualized as a temperature scale from “Familiar Stranger” to “Conversion-Ready,” the thermometer maps reader warming tactics. Each stage includes conversion probability ranges and trigger mechanics.
Core Insight:
Beneath the visual:
“Each post = a funnel step, not an act of creativity.”
Substack writing is not about publishing. It is about orchestrating behavioral progression toward monetization.
[Simulated scenario]
Visual: Substack Notes Interaction Heatmap
What Actually Works in Notes: A Psychological Map of Reader Activation
This matrix visualizes how different types of content perform inside Substack Notes, using border styles and fills to indicate interaction intensity.
Content Type Performance Matrix:
Open-ended Questions (Top Left):
“What’s the biggest mistake you’ve made in [topic]?” → 87% interaction (bold black border)
“How do you deal with [common pain point]?” → 73% interaction (bold black border)
“Tell me your experience using [tool]” → 42% interaction (dashed border)
Provocative Statements (Top Right):
“Most [industry] advice is completely wrong.” → 94% interaction (black fill, highest tier)
“I used to believe [myth], now I know better.” → 68%
“Unpopular opinion: [statement]” → 35%
Value-driven statements and vulnerability posts follow similar logic.
Interaction Psychology Breakdown (Center Layer):
Explains high-performing triggers and their psychological foundations:
Controversy / Anti-mainstream takes → Activates tribal defense reflex
Open questions → Zeigarnik effect: unfinished thoughts drive engagement
Personal failure stories → Reciprocity through shared vulnerability
Specific frameworks → Immediate utility signals trustworthiness
Strategic Pattern Sequence (Bottom Bar):
The high-conversion Notes cadence:
“Controversial take → Follow-up question → Value delivery → Soft CTA”
This flow converts 67% more newsletter subscribers than random posting.
Right Panel: Trust Velocity Analysis
Compares interaction intensity with time-to-subscribe:
High-interaction Notes: average conversion in 2.3 days
Low-interaction Notes: 15.2 days
Reveals Notes as a behavioral temperature sensor, not a casual social feed.
Strategic Implication:
Creators on Substack are not just writers. They are funnel architects. Every post, note, and CTA is either accelerating or stalling the conversion sequence.
Signals to Watch:
Algorithmic boosts for Notes-based engagement
Newsletter CTA redesigns that reward funnel depth
Future integrations that mimic CRM logic (not just CMS)
3. YouTube: Editing Is the Real Product
Success favors those who engineer retention, not those who chase ideas.
The Platform Where Structure Becomes Strategy
YouTube is the only major platform where content depth and architectural clarity are still rewarded at scale. But even this reward system is not neutral. It favors a particular form of thinking: narrative engineering.
Ali Abdaal’s pivot to hour-long videos in 2024 was not artistic. It was mathematical. Longer view durations feed into channel-level performance metrics. That, in turn, fuels recommendation loops and playlist clustering.
The system isn’t built for bursts of genius. It’s built for predictable retention curves. The most successful creators treat editing as behavioral modeling. They experiment not with ideas, but with fatigue timing, emotional arcs, and micro-hooks.
YouTube looks like a video platform. It is actually a time allocation market.
[Simulated scenario]
Strategic Implication:
Winning on YouTube requires understanding its behavioral gradients. Editing becomes an economic function. Scriptwriting becomes a funnel mechanic. The creator is no longer the star, the structure is.
Signals to Watch:
First-30-second retention benchmarks dictating growth
Rise of chaptered videos as modular attention units
Channel clustering strategies that treat libraries as ecosystems
[Simulated scenario]
4. Podcasts: Intimacy Is Eroding
What began as permissioned listening is collapsing into feed-driven skimming.
Losing the Moat of Attention Depth
Podcasts historically offered refuge from platform manipulation. They ran on RSS. They respected attention. There were no feeds, only relationships. That era is ending.
Spotify and YouTube are pulling podcasting into the feed economy. The rise of video-first formats, timestamp UX, and clip sharing reshapes consumption into scanning, not listening. Completion rates are dropping. Skimmed consumption is rising.
In trying to expand discovery, platforms are killing depth.
Listeners no longer sit with you. They bounce between you and a thumbnail stack.
The intimacy that once made podcasts powerful is now diluted by format creep.
[Simulated scenario]
This diagram analyzes the trend of podcasts losing their deep listening experience.
Podcast UX Evolution Timeline (Upper Section)
This timeline shows four critical stages in podcast consumption patterns:
RSS Era: Originally, podcasts were directly subscribed through RSS feeds, where users would listen to complete episodes, building deep listening relationships.
Platform Integration: When platforms like Spotify began intervening, we saw a "Drop-off Spike" with algorithms starting to influence content recommendations.
Visual Optimization: Platforms began emphasizing thumbnail optimization, making visual elements more important than audio content itself.
Chapter Skip Era: Users became trained for fragmented consumption, no longer listening linearly through complete content.
The dotted arrow below marks "Intimacy Decay," showing how this evolution gradually destroys podcasting's original deep connection.
Completion Rate vs Discovery Rate Chart (Middle Section)
This dual-axis chart is the most critical, revealing a negative correlation:
Left axis (solid line): Podcast completion rates declining from nearly 100% in 2020 to about 40% in 2024
Right axis (dashed line): Platform-driven discovery rates rising from 100% to nearly 500%
Key Insight:
Algorithm-driven content discovery increases exposure but simultaneously destroys deep listening relationships. The easier it becomes for users to discover new content, the less willing they are to focus on complete listening.
Signals to Watch (Right Section)
Three warning indicators show this trend is accelerating:
Spotify's visual-first interface: Thumbnails matter more than audio controls
Chapter skip becoming default behavior: Users habituated to fragmented consumption
YouTube Podcasts favoring thumbnail scanning: Browse behavior replaces intentional listening
Strategic Implication
The black box at the bottom emphasizes: Creators who built business models on "attention loyalty" must now redesign for "modular consumption." Visual UX, snippet logic, and timestamp design are no longer "nice-to-haves" but "core infrastructure."
The diagram's core argument is: Podcasts are degrading from deep "permissioned listening" to shallow "feed-driven skimming," and creators must adapt to this reality.
Conclusion: Escape Isn’t Exit, It’s Leverage
Platforms won’t change. But creators can shift the game by reclaiming control across distribution, identity, and monetization.
Burnout isn’t a personal failure. It’s a systemic feature of incentive structures that prioritize platform growth over creator well-being.
Each platform engineers its own version of creator success. But that success is conditional, temporary, and contingent on reinforcing the platform’s growth logic.
To escape the loop is not to exit the platform. That’s a false binary.
It’s to build systems that reclaim leverage: direct distribution, durable identity, audience portability, and financial upside aligned with time investment.
The smartest creators and product teams in 2025 are doing one thing in common.
They’re building off-platform insurance inside on-platform strategy.
Anchor Articles and Updates
Crisis Is Not the End. It’s a Catalyst for Product Growth. — Reframing the Narrative of Windsurf, Astronomer, and Cluely
Building Products in the AI Era: The Deep Logic of Speed, Content, and Data Ownership — If you’re building a new product in 2025, you’re not competing on functionality.
You’re competing on attention loops, learning velocity, and data leverage.
How AI Platforms Reshape Innovation: Subordination, Risk, and Workflow Strategy — Rethinking Product Strategy Under Model Governance
How AI Understands User Intent Before They Search: Commercial Decision Loops and the Invisible Funnel — Why pre-intent behavior is becoming more legible and monetizable
Inspired by Lenny’s Growth Inflections: AI and Personal Brands Rewiring Startup Growth — AI automation and personal brands are redefining startup growth inspired by Lenny Rachitsky’s Growth Inflections.
Why Growth Marketing Is Not Digital Marketing and Why This Distinction Matters — It’s not that your marketing strategy is flawed. You might just be addressing the wrong problem.
When AI Products Can’t Find PMF, Build a Landing Client Instead — PMF isn’t always found in the product, Sometimes, it starts with one strategic client
Content as a Revenue Tool: Shortening Time-to-Close in Startup Sales — Content that shortens sales cycles, Not just builds traffic
Building Revenue Systems When Scale Isn’t an Option — Profitability First: How Startup Teams Can Drive Revenue in Constrained Markets
Case Studies
Mountain Gentleman — They knew they needed to go digital but had no idea how to start.So we saw things through the rider’s eyes.It wasn’t just about buying gear because it felt like building out your dream GTR.Every part of the journey was designed to match that thrill.
CoinRank — CoinRank needed a fresh way to stand out in crypto. We created a short video strategy that turns complex info into quick, engaging clips that grab attention fast.
FAQ
What does a project look like?
How is the pricing structure?
Are all projects fixed scope?
Can I adjust the project scope after we start?
How do we measure success?
Do you offer ongoing support after project completion?
How long does a typical project last?
Is there a minimum commitment?