For the last year, a familiar story has been playing out across the internet. Humans versus robots.
Creators versus AI. Authenticity versus scale.
It sounds abstract until you realize we have seen this movie before.
James Cameron’s Terminator was never really about killer robots. It was about agency. Who makes decisions. Who controls outcomes. And what happens when efficiency is allowed to outrun humanity.
That thesis is now playing out in the real world, not in war (yet), but in content, commerce, and culture.
After I had sketched out my predictions for 2026, I went back and did a deeper dive into what some of the smartest people in the creator economy and media are actually paying attention to. Almost everything still traces back to AI, but not in the way most of the conversation frames it.
I had been overly focused on AI as a content creation tool and largely ignoring its more structural effects: the less sexy shifts that fundamentally change where power and leverage sit.
Search is the clearest example. It is no longer just about ranking pages or even feeds. As AI answers replace links, discovery collapses into zero-click decisions. Content does not just need to be good. It needs to be legible to systems that summarize, select, and decide without ever handing a human off to you.
Then there is edge AI computing. The short version is that more intelligence is moving onto devices themselves instead of living entirely in the cloud. That shifts control away from platforms and toward hardware, operating systems, and local agents that curate what people see based on private context. Distribution becomes more fragmented, more personal, and harder to reverse-engineer.
Agentic scale takes this one step further, but only in certain domains. Software does not just recommend anymore. It acts. It books flights, buys commodities, schedules appointments, replenishes household goods. These are decisions that never required much taste or emotional trust in the first place. They are transactional, repetitive, and easily comparable. In those categories, persuasion matters less than infrastructure. Availability matters more than story. Meaning does not disappear from the internet. It simply exits large transactional surfaces by design.
AdTech feels the shock next. If agents are executing decisions and humans are no longer clicking through feeds in the same way, the old logic of impressions, clicks, and attribution starts to break down. Advertising does not vanish, but it reroutes toward environments where human presence can still be verified, context still matters, and influence is not purely programmatic.
And that is where things finally snap into focus for those of us who actually make things for a living.
From the ground level, this does not feel like humans versus AI. It feels like a fork in the road. On one side are systems optimized for machines, efficiency, and execution. On the other are spaces optimized for humans, taste, trust, and connection.
That split is what I mean by the Great Bifurcation.
So I went back and looked at my predictions, wondering whether they actually aligned with this bigger layer. And they did albeit not necessarily consciously. Everything I have been predicting, in one way or another, is a response to this bifurcation and to the question of how and where humans will continue to hold relevance in this world.
To be clear, I am not talking about AI as a tool to power human creation. Those tools already are in use and will only become more integrated. There will be convergence there. What matters to me is where the point of view remains human, and where creativity is initiated, controlled, and shaped by humans…
So here we go.
Five predictions for 2026 or how humans fight back the robots
1. Community becomes the primary asset class. IP becomes a byproduct.
The winning companies stop treating IP as the starting point and start treating it as the fuel. The real asset is a durable, identifiable community that can support multiple formats, platforms, and revenue streams. Studios that still think in terms of single shows or films struggle. Studios that think in terms of verticals, emotional DNA, and repeatable audience needs compound. This applies equally to creators who want to build scale and to investors chasing these new models.
How this is a response to AI
AI dramatically lowers the cost of producing IP or expanding existing IP. Stories, formats, and concepts become abundant and interchangeable. What does not scale as easily is shared context. Community creates memory, loyalty, and identity that cannot be generated on demand. As agents take over transactional surfaces and discovery becomes increasingly automated, community becomes the place where humans still decide what they care about. IP that emerges from community is harder to replace because it is already rooted in human connection.
2. Vertically built media companies outperform generalists.
By 2026, the middle collapses further. Broad, taste-agnostic studios lose ground. Vertically focused companies, whether built around a genre, a lifestyle, a sport, or a cultural identity, gain pricing power, clearer monetization paths, and stronger creator loyalty. These companies look more like ecosystems than production houses. Content is only one spoke, not the hub.
Two lanes emerge. The first is the OpenVerse lane, where capital attempts to wall off large ecosystems organized around shared interests. Teton Ridge’s effort to organize cowboy culture is one example, with many more emerging. The second lane is verticals built around creators. While this is most obvious at the top end with figures like MrBeast or Dude Perfect, we are also seeing institutional capital back creator-driven ecosystems, such as Whalar’s Lighthouse Studios supporting Cole Bennett’s Lyrical Lemonade as a programmed TV channel that extends a single creator’s DNA at scale.
I return to these examples often because they are early pioneers. As more of these models show real traction, or even the credible promise of it, others will increasingly borrow from these two playbooks.
How this is a response to AI
AI flattens generalism. When creation tools, distribution, and optimization are available to everyone, broad positioning loses its advantage. Vertical companies encode taste, values, and cultural fluency. That specificity matters to humans and remains legible to machines. In an agentic environment, clarity outperforms volume. Verticals know who they serve and why. Generalists increasingly cannot answer either question.
3. Slow media and IRL experiences rebound as a counterweight to scale.
As AI-driven content volume explodes and feeds become more chaotic, attention becomes scarce again. A premium emerges around things that feel finite, intentional, and human. Longer-form writing, curated releases, live events, retreats, screenings, and physical gatherings gain value. Not at mass scale, but at meaningful scale. The business incentive shifts from reach to depth.
How this is a response to AI
AI makes speed and volume meaningless signals. When everything is instant, slowness becomes proof of care. IRL experiences and slow media introduce friction, time, and physical presence. These elements are difficult to automate without destroying their value. In a synthetic environment, effort becomes legible again. Scarcity is no longer manufactured. It is structural.
4. Legacy premium content ticks up, but never reclaims the center.
I had to check my biases before making this prediction, because it conveniently aligns with my own background. But as AI-generated content increases and more thoughtless material floods the system, some consumers retreat back toward legacy businesses. There is a modest recovery in high-end scripted film and television, driven by audience fatigue and a renewed appetite for curation. Netflix, select streamers, and theatrical releases see lift at the top end.
The system does not revert. This premium layer coexists with creator-led ecosystems rather than replacing them. Legacy wins when it leans into taste, restraint, scale, and authorship, not volume. As creator-led content continues to scale in quality, it converges further with legacy platforms. We see more theatrical releases from creators, and more high-end creator content funded and distributed by legacy players. That convergence contributes to the lift as legacy better understands how creators can drive their businesses.
How this is a response to AI
Legacy premium content benefits from visible constraints. Budgets, timelines, and creative oversight reintroduce human judgment. As AI floods the market with competent but generic output, audiences seek signals of authorship. The lift is limited because abundance does not disappear. As Doug Shapiro has noted, our ability to consume content is already saturated. It is a zero-sum game. But curation regains value. Legacy survives by emphasizing what AI struggles with most: taste, patience, and restraint.
5. Capital follows audiences, not companies. And more of it leaves the U.S.
By 2026, meaningful growth capital in entertainment flows more aggressively into Europe, Asia, and Latin America. Not because the ideas are better, but because the ecosystems are earlier. Creator economies in these regions are undercapitalized, under-institutionalized, and still fragmented. That creates room for infrastructure plays, studios, platforms, and services that would be prohibitively expensive to build in the U.S.
Legacy media and private equity look abroad not for hits, but for leverage. This prediction is driven less by comprehensive data and more by firsthand observation, largely anecdotal, across parts of Latin America and Europe, combined with the basic reality that capital chases markets with higher potential margins and lower competition.
How this is a response to AI
AI compresses value fastest in mature, saturated markets. In emerging regions, human taste, local culture, and community still matter more than optimization. Infrastructure is still being built, not optimized away. That creates room for durable systems rather than short-term arbitrage. Capital follows places where humanity remains an advantage rather than a rounding error.
Humanity Will Survive!!! (For now?)
So this was never really about humans versus AI. It was about where humans still matter.
The Great Bifurcation is not something coming down the road. It is already here. Machines are taking over execution, optimization, and scale. They are getting better, faster, and cheaper at decisions that never required taste or trust in the first place.
What humans are left with is not nothing. It is the part that actually matters.
Community. Judgment. Taste. Context. Meaning.
Every one of these predictions is not a rejection of AI. It is an acceptance of its strengths and a refusal to compete on its terms. Machines will win efficiency. That fight is over. Humans win by moving to terrain where efficiency is not the point.
This is exactly what James Cameron understood.
In Terminator, humans do not beat the machines by becoming better machines. They beat them by changing the battlefield. They operate in shadows. They rely on trust. They value memory, sacrifice, and connection. The machines have scale. The humans have purpose.
No time travel required. No nuclear apocalypse necessary.
Just a clear-eyed understanding of what is worth protecting, and where to fight.
Turns out the lesson was never about stopping the robots. It was about remembering what they cannot replace.