For seventy years, Hollywood operated on a simple principle: control distribution, control value. Record labels owned radio playlists. TV networks programmed primetime slots. Movie studios controlled theater releases. Talent agents could create genuine scarcity because there were only so many slots, finite airtime, limited capacity.
This controlled scarcity drove the entire deal-making ecosystem. Premium talent commanded premium rates because access was genuinely restricted. Agents could say "no" and mean it, knowing that turning down one opportunity created leverage for better terms on the next. The mathematics were straightforward: if only 20 songs could be in rotation at a major radio station, artists competed for those slots, and scarcity determined value.
Today, TikTok's algorithm surfaces content to billions of users through personalized feeds where everyone sees something different. There's no person to call. No playlist to influence. No finite slots to compete for. What does scarcity mean when algorithmic distribution creates infinite, individualized experiences?
How Scarcity Shaped Traditional Deal-Making
The old model created predictable leverage dynamics. Record labels controlled which artists reached audiences, so they could demand extensive rights and long-term exclusivity. Agents representing A-list actors knew studios needed recognizable names for tentpole films. TV networks programming limited channels meant time slots had genuine scarcity value—primetime Thursday at 8pm was categorically different from 2am on Tuesday.
This system trained an entire industry around artificial constraints. Talent representatives learned to create additional scarcity through strategic scheduling and exclusive windows. The best agents mastered saying "no" to preserve their clients' perceived value. Deal-making centered on access control rather than audience engagement.
The infrastructure reflected these dynamics. Complex negotiation processes made sense when both sides had significant leverage. Multi-party approval workflows worked when deals took months to finalize. Everything moved slowly because everything was scarce, and scarcity created time to negotiate.
When Everyone Sees Something Different
Algorithmic distribution fundamentally changed what scarcity means without eliminating the value of premium talent. A-list creators still bring cultural influence, mass reach, and brand credibility that algorithms can't manufacture. But the mechanics of how audiences discover and engage with content operate entirely differently.
When everyone's feed is different, traditional scarcity metrics become meaningless. You can't "take up space" on TikTok the way you could dominate radio rotation. There's no "prime time" when algorithmic feeds operate 24/7. You can't block competitors from reaching audiences when the algorithm determines exposure based on individual engagement patterns.
This creates a disorienting new reality for how fame works. A beauty influencer could be so famous in Filipino-American communities across three continents that she can't walk through certain neighborhoods without being stopped for photos, yet remain completely invisible to someone living two blocks away who simply isn't connected to those algorithmic networks. The algorithm doesn't create broad cultural ubiquity; it creates intense pockets of connection distributed across geography and demographics in ways that would have been impossible in the broadcast era.
The Spilling Over Principle
I've been thinking about how algorithmic distribution actually works, and I keep coming back to a framework that Derek Thompson laid out in "Hit Makers." Thompson argues that nothing goes viral from nowhere. Hits emerge from connected networks, spreading through what he calls "dark broadcasting" within communities before breaking out to broader audiences. Thompson was describing how this worked in an era of broadcast media and early social platforms, but algorithmic distribution has amplified this spilling over principle to an entirely new scale.
Unlike traditional media crossover—where TV stars made calculated moves into movies or musicians appeared on talk shows to reach new audiences—algorithmic talent doesn't cross over through strategic decisions. They spill over. Scott Borchetta, founder of Big Machine Records and Taylor Swift's label through her country-to-pop transition, told me this directly when Delta Rae was on the label after leaving Warner. Swift's pivot to pop was absolutely a conscious strategic decision—but the timing was everything. Borchetta described it as recognizing when her audience was already spilling over into pop. Country fans were sharing her music with their pop-loving friends. Pop stations were getting requests. The strategic decision wasn't whether to pivot, but when—waiting until the spillover was already happening rather than trying to force it prematurely.
Spilling over suggests something fluid and uncontrolled, moving beyond its original container not through force but through natural pressure and momentum. Content starts within a community—a niche interest group, a geographic cluster, a specific demographic—and if it resonates strongly enough, it spills over into adjacent communities, then into broader networks. The algorithm amplifies what's already working within communities, creating spillover effects that can eventually reach massive scale. But it all starts with authentic connection within a specific audience, not broad appeal engineered for everyone.
Why This Changes Strategy
Understanding spillover fundamentally changes how brands should think about value. In the controlled distribution era, you bought guaranteed exposure through scarce slots. In the algorithmic era, you can take multiple strategic bets on which creator-brand combinations might catch fire and spill over into broader networks.
Consider a beauty brand launching a new product line. They might partner with one major beauty influencer for $200,000 to establish credibility and reach their core following—that's the traditional scarcity play. But they might also coordinate with 200 micro-creators at $1,000-$5,000 each to generate authentic content across dozens of beauty sub-communities—skincare enthusiasts, makeup artists, sustainable beauty advocates, men's grooming. Each of those 200 pieces of content represents a chance for spillover within and beyond its niche. One might catch fire in the sustainable beauty community and spill over into broader environmental circles. Another might resonate with men's grooming and spill into fitness communities.
The volume strategy doesn't replace the premium strategy; it complements it by playing an entirely different game. One is about guaranteed reach. The other is about maximizing opportunities for unpredictable spillover.
When Your Infrastructure Can't Execute
Deal-making infrastructure built for the controlled scarcity model actively prevents executing volume strategies at algorithmic speed. Current systems assume you're negotiating one high-value deal with significant leverage on both sides. Multi-month approval workflows. Sequential communication across email for outreach/negotiation/contracting (WhatsApp outside the US) that spans weeks.
The average creator deal flow—the process from initial outreach to signed contract—requires 60-80 emails. At 5-10 minutes per email, that's 5-13 hours of human coordination time per deal just managing communication. This works when you're negotiating a single $500,000 celebrity partnership over six weeks.
But imagine you're a brand manager who sees a trending moment on Tuesday morning—a cultural conversation perfectly aligned with your new product launch and starting to spill across multiple creator communities. You have maybe 48 hours before the trend peaks and starts to dissipate. You want to activate 200 micro-creators to ride that wave. But you're staring at a process that requires 1,000-2,600 hours of administrative work just to get contracts signed. Your team of five can't physically process that many emails and negotiations fast enough. By Thursday, the trending moment has passed. The spillover opportunity is gone.
The workflows are fundamentally incompatible. You can't serve premium clients through thoughtful, months-long negotiations while also capitalizing on trending moments that require coordinating hundreds of creators in hours.
Building for Multiple Speeds
The future isn't about choosing between relationship-driven premium talent and algorithmic-driven volume strategies—it's about serving both simultaneously as they operate at different speeds. What we've learned building Basa is that talent literally are the product, which creates decision-making patterns unlike standard business negotiations. A creator isn't just evaluating commercial terms—they're considering how a deal affects their audience relationship, their creative direction, their long-term positioning.
When you're coordinating 200 of these decisions simultaneously to catch a 48-hour window, you can't simply automate the relationship decisions. The solution is eliminating administrative friction so the actual strategic judgments can happen at the speed spillover demands.
Catching the Spill
What strikes me most about this shift is how it inverts our relationship with timing. In the controlled scarcity era, you had time to negotiate precisely because scarcity was controlled—the slot would be there when you were ready. Now, scarcity manifests as narrow windows where spillover momentum exists. Miss the window, and the opportunity doesn't just diminish—it evaporates completely.
The question isn't whether algorithmic distribution eliminates traditional scarcity. It's whether we can build infrastructure that moves at the speed spillover demands—fast enough to catch trending moments, flexible enough to serve both volume campaigns and premium relationships, sophisticated enough to preserve the human judgment that determines which opportunities are worth pursuing. Because in an algorithmic world, scarcity isn't about controlling distribution anymore. It's about having the infrastructure to act when content starts spilling over, before that momentum dissipates and the moment passes.