Forem: Tory

Dopamine Inflation: How Social Media and AI Raised the Price of Attention (2020–2025)

Tory — Fri, 09 Jan 2026 14:51:13 +0000

Five years ago, a casual photo with friends or a "how my day went" text post could get you a couple hundred likes. That felt good. That felt like connection.

Today, the same dopamine hit requires video editing, AI-assisted captions, trend analysis, and competing with millions of algorithmically optimized posts. We're paying more and getting less.

This isn't just a vibe—it's measurable. And I've been tracking it.

The Baseline: When Dopamine Was Cheap (2019–2020)

The old feed was simple. Facebook, VK—mostly friends, a few public pages, and local memes.

To get attention, you needed:

A photo from a trip
A couple sentences about your day
Maybe a thoughtful caption

Likes were about genuine support. Your people clicked the heart because they cared what happened to you, not because you looked like a micro-brand.

Dopamine was nearly free: minimal time, zero production, and a clear circle of people who actually knew you.

According to research on social media and dopamine pathways, these platforms activated the same reward circuits as social interaction—receiving positive feedback triggered dopamine release in the brain's reward centers, creating short-term feedback loops that kept users engaged.

Instagram and the Avatar Economy (2012–2020)

Then Instagram quietly raised the bar. The feed got prettier. So did everyone's life—or at least how it looked.

Photos weren't just "what happened"—they were "how it looks in the grid"
Everyone around you seemed slightly more vibrant than reality

Likes shifted from genuine engagement to social rating. It became less about "I care about your day" and more about "you're playing this game well."

Dopamine now cost more in effort: angles, color correction, caption crafting, Stories strategy, the constant sense that "I should look the part".

By 2020, Instagram's median engagement rate was significantly higher than today—around 2.94% compared to 0.61% in January 2025. The same content that worked then requires dramatically more sophistication now.

TikTok, Reels, and the Attention Casino (2020–Present)

Then TikTok and Reels exploded. The feed stopped being about people you know.

Now anyone could see you—and you could see anyone
The feed became infinite, formats got shorter, everything revolved around instant interest
Algorithms decided who saw your video and for how many seconds

Before, getting noticed meant impressing your circle. Now you're competing with millions of random videos for fractional attention spans.

To get the same dopamine you used to get from 100 likes from friends, you now compete in a global lottery system.

This created:

More aggressive formats (hooks in the first 0.5 seconds)
Maximum expressiveness front-loaded
Focus on the hook, not the story

The data backs this up: TikTok's average engagement rate dropped from 5.77% in 2023 to 4.64% in 2024. Instagram Reels saw median engagement fall from 0.55% to 0.50% in the same period [web:51]. Even as more people post, fewer people engage proportionally.

Twitter, Threads, and the Endless Idea Stream

Meanwhile, Twitter and Threads operate differently—but extract the same cost.

Endless feeds of short thoughts
Any mundane idea can blow up if it catches the timing and mood right

But dopamine here isn't about warmth—it's about significance. Likes and retweets signal: "I'm saying something important. People are listening."

Your brain quickly recalibrates that level of reaction as the new normal.

Research shows that engagement rates on X (Twitter) dropped 48% between 2024 and 2025—the steepest decline of any major platform. Comments increased by 107% year-over-year, but total engagement per post plummeted.

AI Enters the Game—and Raises the Floor

When AI joined the playing field, it seemed like things would get easier.

Models help generate viral headlines
They create graphics, covers, copy, and video
Anyone can look like they have a production team behind them

But here's the trap: when everyone has access to beautiful images, polished videos, and compelling hooks, the baseline quality level rises.

What was "wow" yesterday is just "standard" today.

Before, a couple hundred likes required sharing an authentic moment. Now, for the same effect, you:

Design the format strategically
Plug in AI tools
Filter ideas through "will this actually hook someone?"
Compete not just with humans, but with algorithmically optimized content

According to recent research, 61% of marketers now use AI for content generation, with adoption growing 25% between 2023 and 2024. This means the content you're competing against isn't just more polished—it's increasingly engineered for maximum engagement.

What the Same Dopamine Costs Now

If we simplify drastically, here's what changed:

Then (2019–2020)

Small circle of people who mostly know you
Simple formats: text, photo, personal updates
Likes as gestures of support, not ratings
Dopamine nearly free: some time, zero production

Now (2025)

Infinite feed of random audiences
Video, Reels, editing, AI, hooks in the first seconds
Likes as markers of status, relevance, "expertise"
Dopamine expensive: more effort, energy, and nerves for the same feeling

By the numbers:

Average engagement rates across platforms: 1.4%–2.8% in 2025
Instagram engagement dropped 16% year-over-year
Facebook engagement fell 36%, TikTok 34%, X 48%
Cost per engagement on social campaigns: $1.29 on average
Average CPL (cost per lead): $65 for paid ads, $95 for organic content

We're paying more and the effect lasts less. The same dopamine that used to come from a simple, warm post to your circle now requires mini-production and participation in a global race.

Why I Choose Depth Over Dopamine Hits

At some point, I caught myself measuring my work's value by numbers. Views, likes, saves—they easily substitute for meaning.

But the moments that resonate most with me aren't attention spikes. They're when chaos becomes a clear system, or when a working template emerges from noise.

That's why I'm interested in something different now. Not squeezing maximum dopamine from every post, but understanding how all this works—and how to use AI without completely burning out in the feed.

That's where my research, prompts, templates, and Spaces come from. It's my way of playing not just on the side of algorithms, but on the side of awareness: building systems that work even when a post doesn't "blow up."

According to research on social media as a behavioral dopamine agonist, excessive platform use can lead to cognitive fatigue and emotional distress over time—mimicking dopamine pathway activation patterns associated with addictive behaviors [web:27]. The key isn't avoiding platforms entirely, but building intentional systems around them.

Calculating Your Own Dopamine Cost

If this resonates with you, we can experiment together.

Try counting not just reach, but your personal cost per like: how much time, energy, and money you're trading for that one second of dopamine.

Ask yourself:

How many hours did this post take (ideation, creation, editing, posting, engagement)?
How much mental energy did I spend optimizing it?
Did I enjoy making it, or was I just chasing metrics?
What's my actual return—connection, learning, growth, or just a number?

When you track your real costs—not just money, but attention, creativity, and peace of mind—you might find that some dopamine hits are absurdly expensive.

And that awareness opens up new choices: invest in systems, not spikes. Build depth, not just reach. Create for clarity, not just the feed.

This article was drafted with the help of an AI assistant and then edited and reviewed by me.

Everyone's Generating Videos; I Calculated What AI Video Actually Costs in 2026

Tory — Wed, 07 Jan 2026 22:42:07 +0000

Everyone talks about AI, but somehow they all mean the same thing—another pretty generation, a dancing baby video, or a "TOP-5 content ideas" listicle. Images and viral videos are literally the most superficial things neural networks can do. But everyone's stuck there because Instagram/TikTok trained us: content = visuals.

Yet AI can be used differently—for analysis, research, and breaking down the economics of tools themselves. I decided to figure out what it actually costs to hit a viral trend with AI video. Not "how to make a dancing baby in 5 minutes," but what one video costs when you calculate honestly: accounting for failed attempts, credit systems, hidden limits, and licensing traps.

I invested my time analyzing 24 AI video generation platforms, collecting data on pricing, credit systems, and real per-video costs. I used AI not for content generation, but for what it's genuinely strong at—processing large datasets, comparing pricing tiers, identifying patterns in monetization structures. The results are in this breakdown.

Context: Why This Matters Right Now

Scrolling through my feed—AI content is everywhere. Instagram Reels, TikTok, even LinkedIn are flooded with adorable 10-second clips: dancing babies, cats, and cartoon characters moving in sync to trending audio. TikTok exploded with AI influencers—virtual models dancing, posing, racking up millions of views. AI avatars fill ads, educational content, entertainment channels.

The trend detonated in the first week of January 2026—perfect timing to analyze the economics of AI generation using a current, live case study.

Viral AI videos work on three pillars:

Emotional response (cuteness, awe at realism)
Perceived reproducibility (looks like you can replicate it in 5 minutes)
Algorithmic love for short-form video

Motion is transferred to static photos or AI avatars through motion transfer technology—AI extracts dance movements from reference videos and maps them onto uploaded images or generated characters.

But behind the shiny output lies financial mechanics that tutorials don't discuss. I used this trend as an entry point for deeper research: what does one AI video cost in 2026—not in theory, but in practice?

Methodology: How I Used AI for Analysis

Instead of generating another viral clip, I applied AI to research work:

Data Collection: Automated extraction of pricing information from 24 platforms (Google Veo 3, Runway, Kling AI, Sora 2, Pika, Hailuo, Luma, and more).

Structuring: Used AI tools to normalize disparate data into a unified format—credit systems, subscriptions, pay-per-use, limits.

Comparative Analysis: Identified patterns in pricing, hidden entry barriers, licensing traps.

Visualization: Built a comparison table across 8 key parameters (resolution, duration, cost per video, monthly plan, special features).

This is the real power of AI—not replacing human creativity, but amplifying analytical capabilities.

Financial Mechanics: What One Video Actually Costs

I broke down all platforms into three pricing segments by the cost of one 10-second video. Here's what I found.

Free Options (With a Catch)

Grok AI: Completely free, 2-3 videos/day, 720p quality, 5-10 seconds duration. You can bypass limits through re-authentication and generate 10-15 clips/day. But quality is basic, no camera control or motion precision. Good for concept testing, not final content.

Kling AI Free: 66 credits/day = 3-4 videos at 10 seconds in 720p. Sounds generous until you hit generation queues up to 3 hours and realize every failed attempt burns credits irreversibly. Free tier isn't a tool for timely content—it's a learning sandbox.

Hailuo MiniMax Free: 6-second videos in 1080p with watermarks. Generous generation limits (3 tasks in queue simultaneously), but watermarks make content unsuitable for commercial use.

Media.io Baby Dance AI: Free for non-commercial use, specialized for dancing content. Narrow specialization—works only with specific movement types, but perfect for testing trends.

Verdict on free options: This isn't "free AI for everyone"—it's trial versions with hard restrictions. For one-off experiments without time constraints? Works. For regular content production? No.

Budget Segment ($0.14-0.64 per video)

Pika 2.0 Standard: $10/month = 700 credits = $0.14 per 5-second video in 720p. Cheapest paid option, BUT—the plan doesn't include commercial use. If you have a monetized Reels/YouTube Shorts account, this violates licensing. A trap for beginners who don't read Terms of Service.

Pika 2.0 Pro: $35/month = 2,300 credits = $0.15 per 5-second video in 1080p with commercial license. Now we're talking—adequate for regular content, but short duration (5 seconds) requires stitching multiple clips for full videos.

Hailuo MiniMax Standard: $9.99/month = ~40 videos at 6 seconds in 1080p = $0.25 per clip. Best price/quality ratio in budget segment. Quality matches more expensive platforms, but less known in the West—most tutorials cover Runway and Kling.

Luma Dream Machine Standard: $9.99/month = ~150 generations from 3,200 credits = $0.50-1.00 per 5-second video in 720p. Special feature—loop function for creating looped animations, popular in anime communities.

Kling AI Standard: $10/month = 660 credits = ~33 videos at 10 seconds in 720p = $0.60 per clip. Optimal for regular content: decent duration (10 sec), stable quality, motion transfer works better than competitors in this price range.

Haiper AI 720p: $0.64 per 5-second video (8 credits/second). Format flexibility (text-to-video, image-to-video, video-to-video), but requires detailed study of credit system—each operation calculates differently.

Verdict on budget segment: Real entry threshold for commercial content is $10-35/month. Pika Standard ($10) without commercial rights is wasted money if you plan to monetize. Optimal combo: Hailuo Standard ($9.99) + Kling AI Standard ($10) = $20/month, ~73 quality videos.

Mid-Range Pricing ($0.70-2.50 per video)

Runway Gen-4 Standard: $15/month = 625 credits = $0.70-1.00 per 10-second video in 1080p. Advantage—fastest generation on the market (5-15 minutes vs. 1-3 hours with competitors). Disadvantage—aggressive prompt moderation, blocks even neutral queries.

Runway Gen-4 Pro: $35/month = 2,250 credits = $0.78 per 10-second video in 1080p. More generous credit limit, same moderation issues. Suitable for those who need speed.

Google Veo 3 Fast (API): $0.90 per 6-second video in 1080p ($0.15/second via API). Pay-per-use model—pay only for seconds used. Convenient for irregular production, but requires Google Cloud integration.

Kling AI Pro 1080p: $37/month = 3,000 credits, but Pro Mode consumes 70 credits per 10 seconds = $2.30 per clip in top quality. This is the mode used for viral videos—with camera control, gesture precision, no artifacts. Difference between Standard ($0.60) and Pro Mode ($2.30) is almost 4x, but quality reflects it.

Google Veo 3 (API): $2.40 per 6-second video ($0.40/second). Top quality, optimized for YouTube Shorts, but expensive for individual creators. Makes sense for agencies and production houses.

Google Veo 3 (AI Ultra): $249.99/month—access to Veo 3, professional Flow editor, Gemini 2.5 Pro Deep Think, 30 TB storage. Cost per video ~$2.50, but this is a comprehensive production solution, not just a video generator. Limited availability (USA only).

Verdict on mid-range: Professional quality starts here. If budget allows $35-50/month—Runway Pro or Kling AI Pro deliver stable results. If you need top tier—Google Veo 3, but expect $250/month for the full package.

Premium Segment & Specialized Solutions

OpenAI Sora 2 (ChatGPT Plus): $20/month, limited access, low-priority queue, ~$2.00 per 10-20 second video in 1080p. Maximum video length on the market (up to 20 seconds), but limited monthly generations.

OpenAI Sora 2 (ChatGPT Pro): $200/month = 500 priority generations + unlimited relaxed mode = $0.40 per video. Optimal price for long clips (10-20 sec) if you need high production volume. Not available in EEA and UK.

Runway Gen-4 Unlimited: $95/month with speed throttling = ~$0.30-0.50 per video. "Unlimited" generations in practice means queues during peak hours. Makes sense for studios with constant task flow.

Hailuo MiniMax Unlimited: $94.99/month = unlimited credits = ~$0.15-0.20 per video in 1080p. Best price in premium segment, but platform is less known—fewer tutorials, community, integrations.

Luma Dream Machine Pro: $94.99/month = relaxed mode (unlimited queues) = ~$0.25-0.40 per video. Specializes in loop animations, popular among anime creators.

Kling AI 2.6 + Audio: $8.10-13.50 per 5-second video with professional audio in 1080p (210-270 credits). Most expensive option on market, but includes synchronized soundtrack and maximum quality. For ad spots and commercial projects.

Verdict on premium segment: Difference between cheapest (Pika $0.14) and most expensive (Kling Audio $13.50) is 96x. This isn't just quality difference—these are different tools for different tasks.

Complete Comparison: Per-Video Cost Table

I consolidated data from all 24 platforms into a unified table. Here are the key takeaways:

Platform	Resolution	Duration	Cost Per Video	Monthly Plan	Special Features
Grok AI	720p	5-10 sec	$0	Free	2-3 videos/day, bypass to 10-15
Pika 2.0 Standard	720p	5 sec	$0.14	$10/month	NO commercial use—trap!
Pika 2.0 Pro	1080p	5 sec	$0.15	$35/month	With commercial license
Hailuo MiniMax Standard	1080p	6 sec	$0.25	$9.99/month	Best price/quality
OpenAI Sora 2 (Pro)	1080p	10-20 sec	$0.40	$200/month	Maximum duration
Luma Dream Machine Standard	720p	5 sec	$0.50-1.00	$9.99/month	Loop animations
Kling AI Standard	720p	10 sec	$0.60	$10/month	Optimal for regular content
Haiper AI	720p	5 sec	$0.64	Credits	Video-to-video transformations
Runway Gen-4 Standard	1080p	10 sec	$0.70-1.00	$15/month	Fastest generation (5-15 min)
Runway Gen-4 Pro	1080p	10 sec	$0.78	$35/month	Speed + more credits
Google Veo 3 Fast	1080p	6 sec	$0.90	API	Pay-per-use model
OpenAI Sora 2 (Plus)	1080p	10-20 sec	~$2.00	$20/month	Limited access
Kling AI Pro 1080p	1080p	10 sec	$2.30	$37/month	Motion transfer, camera control
Google Veo 3 (API)	1080p	6 sec	$2.40	API	Top quality for YouTube Shorts
Google Veo 3 (AI Ultra)	1080p	6-8 sec	~$2.50	$249.99/month	Full Production Suite
Kling AI 2.6 + Audio	1080p + audio	5 sec	$8.10-13.50	$92-180/month	Professional sound

Key Insights from Data:

Best price/quality ratio:

Hailuo MiniMax Standard — $0.25 per 1080p 6-second video ($9.99/month)
Kling AI Standard — $0.60 per 720p 10-second video ($10/month)

Minimum price for 1080p:

Pika 2.0 Pro — $0.15 per video, but only 5 seconds

Maximum duration for reasonable money:

OpenAI Sora 2 (ChatGPT Pro) — $0.40 per 10-20 seconds in 1080p

Optimal strategy for $50/month:

Hailuo Standard ($9.99) = 40 HD videos
Kling AI Pro ($37) = 100 standard videos or 13 Pro Mode
Total: 140 quality videos for $47/month

Difference between cheapest and most expensive:

Pika 2.0 ($0.14) vs. Kling AI Audio ($13.50) = 96x difference

Hidden Entry Barriers (That Tutorials Don't Mention)

Beyond direct costs, there are factors that make "free AI" an illusion:

1. Generation Queues

Kling AI on free and Standard plans can process videos for up to 3 hours. If a trend is "hot" and you need to catch it within 24 hours—free plan is useless. Runway Gen-4 generates in 5-15 minutes, but costs $15-95/month. Time is money too.

2. Credit Opacity

Pika 2.0 charges 5 credits for text-to-video on free plan and 10 credits on paid plan for THE SAME video. Runway calculates credits per second but doesn't show final price until generation. Haiper uses different rates for text-to-video (8 credits/sec), image-to-video (8 credits/sec), and enhance (10 credits/sec). Real cost can only be determined through trial and error.

3. Watermarks and Licenses

Hailuo Free and Pika Free add watermarks. Pika Standard ($10/month) prohibits commercial use—if you have a monetized account, this violates Terms of Service. Most people don't read licenses and get caught.

4. Geographic Restrictions

OpenAI Sora 2 is unavailable in EEA and UK. Google Veo 3 works only in USA through limited access. If you're not in the right country—no amount of money helps.

5. Failed Attempts Burn Budget

Every generation consumes credits, even if the result is unusable. Out of 10 generations in Kling AI, typically 2-3 are publication-worthy—the rest have artifacts, broken hands, desynchronized movement. This means the real cost of one successful video is 3-5x higher than advertised.

ROI Math: Content Creator Economics

Here's what real AI video economics look like when accounting for monetization:

Scenario 1: Beginner Creator (10K Instagram followers)

Starting data:

Followers: 10,000
Average Reels reach: 2,000-3,000 views (20-30% of base)
CPM via Instagram Bonus Program: $1-3 per 1,000 views
Revenue per video: $2-9

AI video costs:

Plan: Kling AI Pro ($37/month) for quality motion transfer
Cost per successful video: $2.30 × 5 attempts = $11.50
Videos per month: 10 quality clips = $115 on generation

Profitability:

Revenue from 10 videos: $20-90/month
Costs: $115/month
Loss: $25-95/month

Conclusion: At this stage, AI video is an investment in audience growth, not a revenue source.

Scenario 2: Mid-tier Creator (50K followers, stable viral hits)

Starting data:

Followers: 50,000
Average reach: 15,000-25,000 views
1-2 viral videos/month: 100,000-300,000 views
CPM: $2-5 (higher due to engagement)
Revenue per regular video: $30-125
Revenue per viral video: $200-1,500

AI video costs:

Plan: Kling AI Pro ($37) + Runway Pro ($35) = $72/month
20 videos/month, 2 of them viral
Production cost: ~$150/month (accounting for failed attempts)

Profitability:

Revenue from 18 regular videos: $540-2,250
Revenue from 2 viral videos: $400-3,000
Total revenue: $940-5,250/month
Costs: $150/month
Profit: $790-5,100/month

Conclusion: At this level, AI video pays off if you have stable viral hits (10% of total output).

Scenario 3: Professional Creator (200K+ followers, agency contracts)

Starting data:

Followers: 200,000+
Average reach: 50,000-100,000 views
CPM: $3-8 (premium audience)
Revenue per video: $150-800
Additional: brand integrations ($500-2,000 per video)

AI video costs:

Plan: Google Veo 3 AI Ultra ($249.99/month) for maximum quality
30-40 professional videos/month
Production cost: ~$300/month (Ultra gives unlimited access)

Profitability:

Revenue from 30 videos: $4,500-24,000/month (platform only)
Revenue from brand integrations (5 videos/month): $2,500-10,000
Total revenue: $7,000-34,000/month
Costs: $300/month
Profit: $6,700-33,700/month

Conclusion: At professional level, AI video is necessary production tooling, pays off many times over.

Critical Profitability Threshold

For AI video to start paying off:

Minimum base: 30K-50K followers with 20-30% reach
Regular viral hits: minimum 1-2 per month
Content quality: top 10% in niche (otherwise algorithm won't push)
Starting costs: $20-50/month, profitability in 3-6 months of growth

Reality for most creators:

80% spend $37-95/month on subscriptions
Use only 20% of credits on finished content (rest is experiments)
Don't reach profitability threshold through platform monetization
Recoup through sponsorships/ads, or treat as growth investment

Recommendations by Use Case (Data-Driven)

For beginners ($0-10/month):
Grok AI (free) → Hailuo Free → Pika Free for concept testing
Goal: understand if you even need AI video, without financial risk

For regular content ($20-50/month):
Kling AI Standard ($10) + Hailuo Standard ($9.99) = 73 quality videos/month
Or Runway Gen-4 Standard ($15) + Pika Pro ($35) for fast generation

For professionals ($100-250/month):
Runway Unlimited ($95) or Google AI Ultra ($249.99) with full Production Suite
Makes sense for 200+ videos/month or agencies

For dance/motion content and AI influencers:
Media.io Baby Dance (free for tests) + Kling AI Pro ($37) = motion transfer specialization

For long video experiments:
OpenAI Sora 2 via ChatGPT Pro ($200/month) = up to 20 seconds + unlimited relaxed mode

For analysis and research (my choice):
Perplexity Pro for data collection + Google Sheets/Notion for structuring + AI tools for pattern identification
Cost: $20-40/month, but applicable to any research tasks, not just video

Conclusions: AI Is a Thinking Tool, Not Just Generation

I started this research with the question "what does one AI video cost," and ended with understanding that we're using AI wrong.

Everyone's stuck on visuals—generate images, make videos, create AI avatars for TikTok. But this is the most superficial function of neural networks. The real power of AI is in data processing, pattern identification, analyzing large information arrays, automating routine work.

I used AI to research the market of AI tools—and assembled a unique database across 24 platforms that doesn't exist in any tutorial. This research reveals the industry economics that pretty promo videos hide.

Key Takeaways:

"Free AI for everyone" is a myth. Real entry threshold for commercial AI video is $20-50/month. Free plans are trial versions with hard restrictions on quality, generation speed, and licensing.

Credit systems are opaque. Advertised cost per video ($0.14-2.50) and actual cost differ by 3-5x due to failed attempts, hidden limits, licensing traps. Pika charges different credit amounts for the same operation in free vs. paid plans. Runway doesn't show final price until generation.

Difference between budget and premium is 96x. From $0.14 (Pika Standard without commercial rights) to $13.50 (Kling AI with professional audio). This isn't just quality difference—these are different tools for different tasks and monetization levels.

Profitability comes only at mid-tier. With 10K followers, AI video is unprofitable ($25-95/month loss). With 50K+ and regular viral hits—profit of $790-5,100/month. Critical threshold is 30K-50K followers with 20-30% reach.

AI for analysis beats AI for generation. I got more value from using neural networks to research market economics than creators get from generating visual content without understanding financial mechanics.

AI influencers and avatars are the new wave. TikTok is flooded with virtual models dancing and racking up millions of views. But behind each account is either a $100-250/month budget for top platforms, or a team optimizing costs through tool combinations.

80% of credits go to experiments. Most people buy $37-95/month subscriptions, burn credits testing prompts, selecting references, failed attempts—and only 20% goes to final content. This isn't a bug in credit systems—it's their business model.

What's Next

I continue using AI for research—collecting data, analyzing markets, revealing hidden tool mechanics. This is my way of sharing experience: not through info-scams and "top-5 neural networks for AI influencers," but through deep breakdowns with numbers, tables, profitability math, and honest conclusions.

If you're interested in the financial mechanics of AI tools or want to learn to use AI for analytics (not just generating images and avatars)—I'll keep sharing findings. For now—don't fall for the illusion of "make an AI influencer in 5 minutes for free." Behind every successful account is either budget, or lots of time optimizing, or understanding platform economics.

AI Transparency Note:

This article was structured with assistance from Perplexity AI to organize research findings and format content for dev.to. All data analysis, platform testing, pricing calculations, and conclusions are based on my original research into AI video generation economics and the viral dancing baby trend. I edited and reviewed every section to ensure it reflects my analytical approach and voice.