Everything Is TV, and Truth Has to Move Faster

Does LinkedIn really cater to a different audience than X? Is X for hobbies while LinkedIn is for duties? Or are the differences between platforms becoming increasingly trivial now that, as Derek Thompson has argued, “everything is TV”?

At first glance, it’s tempting to say each platform still has a clear niche. YouTube, TikTok, Instagram, X, and LinkedIn all feel distinct. But when you zoom out, nearly all of them now optimize for the same thing. Highly immersive, emotionally engaging, fast-moving content.

The dominant unit of attention is no longer the article, or even the post, but the vibe.

This shift isn’t confined to social media. Physical retail, public spaces, and even workplaces are becoming more immersive and theatrical, reflecting just how limited and contested human attention has become. Cold, deliberate media struggles. Hot, interactive media wins.

Some people explain platform differences using an IQ bell curve, but that framing misses what actually matters. A more useful lens is risk and reward, often expressed through a hobby-versus-duty divide.

Growing up, many of us recognized a familiar split: book-smart versus street-smart, credential-driven versus identity-driven, stable income and saving versus innovation and risk-taking, institutions versus movements. One path isn’t better than the other, they simply reflect different appetites for risk and different ways of navigating uncertainty.

This maps closely onto the idea of effectuation versus prediction. Some people operate by optimizing toward a known goal using credentials, rules, and planning. Others start with who they are, what they know, and who they know, then build forward opportunistically, accepting uncertainty as a feature rather than a flaw.

Social platforms increasingly mirror this divide. LinkedIn clusters around duty, credentials, verification, reputational continuity, and long-term professional signaling. It is optimized for predictability and status preservation rather than effectual experimentation. X clusters around hobby and experimentation, ideas, discourse, pseudonymity, rapid iteration, and cultural or technological exploration.

This isn’t about intelligence. It’s about how much risk someone is willing to absorb in exchange for speed, reach, and novelty, and how open they are to trying new things before fully understanding them. A growth-oriented mindset treats unfamiliar ideas as inputs rather than threats, experiments rather than failures. People operating this way are more comfortable learning in public, updating beliefs in real time, and discovering direction through action instead of waiting for certainty.

The product design of each platform reinforces these behaviors. On LinkedIn, posts can be edited indefinitely, identity is persistent, and employment and education are verified, allowing reputation to compound slowly over time. On X, the editing window is short, quote reposts allow ideas to branch horizontally rather than flow top-down, and replies can persist even if the original post disappears.

This enables deep intertextuality, ideas colliding, remixing, and evolving in public. LinkedIn restricts reposting with new media and enforces tighter norms around professionalism and identity. These aren’t minor UX differences; they actively shape how people behave. X rewards speed, experimentation, and occasionally chaos. LinkedIn rewards stability, signaling, and trust accumulation.

Video goes viral on both platforms, but what is considered worthy of attention differs because the underlying incentives are fundamentally different.

As these environments accelerate, they strain any system trying to distinguish signal from performance in real time.

Despite the rebrand, X remains a place where many people go to get and give news, especially around technology and innovation. It is also where identity can be most depersonalized, or even non-human.

Recent policy changes have quietly reshaped this landscape. The platform has seen a surge in low-effort AI-generated content, reply spam, and engagement farming. When financial or tokenized incentives are removed from structured systems and left to emerge informally, they don’t disappear; they reappear as noise.

This directly affects Facticity.ai and ArAIstotle, which currently operate on X and reward high-quality fact-checking through the FACY token. In an environment increasingly saturated with AI slop, the challenge shifts. It is no longer just about verifying claims, it is first about identifying which content is even worth verifying.

The bar for truth-seeking systems rises.

LinkedIn, by contrast, functions as a kind of social verification layer. Schooling and employment histories are difficult to fake at scale, and credibility cannot easily be bought. When time is scarce and risk assessment matters, LinkedIn offers a rough but powerful filter: lightweight trust and risk signals that simply aren’t available on most other platforms.

This is why many people now ignore cold emails or unsolicited messages, but will respond to a LinkedIn connection request or meet a stranger through a mutual professional network. Identity verification lowers risk, but it does not guarantee correctness.

Identity verification tells you who is speaking. Claim verification tells you whether what they are saying is true. Modern platforms are increasingly good at the former and dangerously weak at the latter.

If everything is TV and attention is driven by immersion rather than deliberation, then truth becomes harder to distinguish from performance. Authority is often performed before it is proven. Content spreads faster than verification. Identity can be fluid, synthetic, or strategically constructed.This is where AI Seer fits in.

Facticity is designed for a world where slowing down is no longer realistic. Instead of asking users to exit systems optimized for speed, it embeds truth-seeking agents directly into the flow of modern media. It does not resist the idea that everything is TV, it attempts to reform truth-seeking from within it.

Whether someone is navigating professional claims on LinkedIn, breaking narratives on X, or viral video content elsewhere, Facticity helps answer a question that is becoming increasingly critical: Is this actually true?

In a world of vibes, bots, and infinite scroll, truth cannot afford to be cold and slow. It has to be fast, contextual, and verifiable at the exact moment attention is captured.

That is the future Facticity, and AI Seer, are building toward.