Companies and individuals who only make products have no future; they also need to produce reality.

Writing about: The Rust of Uncle Bu Dong and the Industry

Many people like binary thinking and dualism. In our era, the true opposites worth discussing are no longer capital versus labor, online versus offline, content versus products. Today, many changes are converging on a new dividing line: media and machines.

In the past, people could generally understand the two separately. Machines were responsible for production, calculation, execution, and amplifying efficiency. Media handled dissemination, storytelling, attention, and social influence. One leaned toward factories, the other toward stages. One processed logic, the other shaped perception.

But in today’s AI era, this boundary is rapidly collapsing. Machines are beginning to produce media, and media, in turn, is shaping machines. The familiar companies are quietly transforming during this process.

This is a crucial step in understanding the AI era.

Every era invents its own companies.

In the steam engine era, companies resembled factories—those who could expand capacity, lower costs, and establish discipline would dominate the market. In the mass media era, companies began to resemble brands—those who could occupy television, advertising, and consumer minds could turn products into symbols and attention into profit. In the internet era, companies increasingly resemble platforms—those who can connect users, organize networks, and control distribution channels are closer to the center of the times.

Looking back at business history, you’ll find an important pattern: what a company looks like often depends on the most core infrastructure of that era, and also on the most influential media environment. That’s why the railway era shaped railway companies, the television era shaped consumer brands, and the internet era shaped platform giants.

McLuhan had long warned that media truly shapes “the scale and form of human relations and actions.”

Therefore, companies are never just legal entities or profit machines. They are more like slices of an era. The core capabilities of a company often reveal where the deepest power structures of that time lie.

This is why today’s real question isn’t just which jobs will be replaced or how much tools improve efficiency. The major change is that the organizational form itself—companies—is crossing a threshold.

The most successful and representative companies in the future will likely share a common trait: half media, half machine; producing products and reality simultaneously.

AI isn’t replacing jobs; it’s transforming companies’ dynasties.

Venture capital giants and tech founders are rushing to catch up, as the value of AI expertise skyrockets.

Why must a company grow in two directions?

Many are familiar with “companies like machines.” Since the industrial age, companies have had a strong mechanical quality. Standardized processes, division of labor, hierarchical management, performance assessments—all resemble a giant organizational machine. But today’s changes go even deeper.

Because now, machines are no longer just assembly lines, ERP, or automation tools—they are entering cognition, decision-making, and expression layers. Models can write, read, see, summarize, analyze, and assist decision-making. Increasingly, knowledge work is being broken down into callable, trainable, and replicable processes.

OpenAI’s 2025 corporate AI report states that enterprise AI is moving from experimentation to “core infrastructure,” with usage rapidly increasing. The report also notes that ChatGPT’s message volume has grown 8-fold year-over-year, and API inference tokens’ organizational consumption has increased 320 times. This signals clearly that AI’s role in organizations is becoming as fundamental as electricity, databases, and cloud computing.

But the problem is, a company can’t just be a machine.

Because in this era, capability alone isn’t automatically recognized by the world. Products aren’t automatically understood, technology isn’t automatically trusted, brands aren’t automatically remembered. An organization lacking continuous expression, explanation, storytelling, and attention organization can have powerful technology but still be drowned in noise.

Thus, companies are forced to grow in another direction—mediaization.

Here, “mediaization” is no longer just traditional publicity, PR, or advertising. It means companies start managing their public presence like media outlets. They must keep speaking out, explaining, shaping personalities, organizing cognition, and maintaining relationships with users, markets, developers, investors, and regulators. They increasingly resemble devices that continuously output meaning and emotion.

Today’s fast-moving companies often do two things simultaneously: internalize as machines, externalize as media.

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The realization is clear: AI isn’t about equality; it’s the final battle between capital and labor. The richer you are, the faster you run.

This isn’t just about communication skills; it’s a rewrite of organizational ecology.

To understand this, it’s helpful to revisit Neil Postman, a disciple of McLuhan.

Neil Postman, an American media theorist and cultural critic, author of “Amusing Ourselves to Death,” long studied media ecology at NYU. He made a crucial point: technological change isn’t additive but ecological.

He meant that when a new technology enters society, it doesn’t just add a tool to the existing world; it reshapes the entire environment. Printing changed the knowledge order, television altered public discourse, and computers are reorganizing social life.

Today, this judgment seems almost tailor-made for AI.

Many think a company just gains an AI assistant, a model interface, or some automation. But in reality, AI is redefining what kinds of people are valuable, which jobs are easily absorbed by systems, what expressions are more likely to spread, and which organizations can attract capital and talent. The change isn’t limited to a department; it penetrates the entire company, rewriting the ecosystem.

That’s why, today, talking about AI isn’t just about tools; it’s about media. Because media determines how people access, understand, and organize the world.

McLuhan’s famous “the medium is the message” emphasizes that the focus isn’t on content itself but on how media forms reshape human perception and social structures. According to official explanations, media are important because they “shape and control the scale and form of human relations and actions.”

In the AI era, this becomes even more direct. Natural language has become both an interaction interface and infrastructure. You seem to be asking questions, but you’re actually deploying a capability system. You seem to be writing, but you’re also constructing something new.

This creates another recursive cycle: media creates machines, and machines, in turn, create media.

This is almost an exact portrait of many new companies. Models ingest decades of accumulated text, images, code, videos, and language—digitized media worlds—and produce new text, images, videos, sounds, and interactions—new media. They absorb culture while also regenerating it.

Therefore, the core competition of future companies will increasingly be a coupling of narrative systems and intelligent systems.

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The strongest companies are already showing these new species traits.

If you want one example that best illustrates this change, it’s OpenAI—very typical.

OpenAI has strong machine attributes. It relies on model training, infrastructure, system engineering, APIs, enterprise integration, and continuous iteration. Its 2025 enterprise AI report reveals that enterprise usage is rapidly deepening, with AI moving from a side tool to core workflow.

Recently, OpenAI’s corporate updates also emphasize that enterprise adoption is accelerating across industries. In other words, it’s no longer just a research lab but an industrial system outputting machine capabilities at scale.

At the same time, OpenAI also has a very strong media attribute. It not only releases models but also continuously explains the future. It doesn’t just deliver tools; it shapes public imagination of AI. Every launch, product update, demo, and executive statement quickly enters media, social platforms, corporate meetings, and everyday conversations. It outputs not only capabilities but also a cognitive framework about the future.

This is the prototype of a “new species company”: internally more like infrastructure, externally more like a media network. It’s building smart factories and public imaginaries simultaneously.

Silicon Valley’s venture capital shifts show that even capital has realized media is rising.

More interestingly, this change isn’t limited to AI companies. Even top-tier Silicon Valley funds are actively adjusting.

Andreessen Horowitz, known as A16Z, has been systematically strengthening its content and media capabilities over recent years. It’s long been producing podcasts, newsletters, columns, and research.

By November 2025, A16Z officially launched the a16z New Media team, explicitly stating their goal: to help founders with branding, storytelling, and public narrative, building a comprehensive new media support system around writing, video, podcasts, social media, research, events, and communities. On the same day, they also launched the a16z New Media Fellowship, targeting operators, creators, and storytellers.

Even more telling, in a February 2026 official podcast, the founders Marc Andreessen and Ben Horowitz openly discussed how media landscapes are changing, why individuals are now more important than corporate brands, why speed is crucial in the new media environment, and why A16Z is building “new media tactics” into its core capabilities.

This clearly shows that even capital has realized media skills are no longer optional but a core part of organizational competitiveness.

A venture capital firm, which traditionally focused on fundraising, investing, post-investment management, and exits, is now increasingly building itself into a semi-media organization. The logic behind this isn’t complicated.

In today’s tech world, capital, products, talent, influence, and narrative are hard to separate. Those who can consistently generate attention attract talent more easily; those who define tracks can more easily set valuation; those who organize online cognition can more easily mobilize offline resources.

Thus, today’s companies can’t succeed solely by “doing well.” They must also be seen, understood, remembered, and desired. Media capabilities are moving from the periphery to the core of organizations.

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When companies produce both products and reality.

To understand the AI era, a new change must be recognized: many organizations today are no longer just designing products, platforms, and services—they are designing cognitive environments.

Because once a company has media attributes, it influences not just market choices but also how people understand issues, name trends, and perceive technologies. It doesn’t just sell things; it shapes the “reality” seen by the outside world.

Every engineering decision is a cultural act; every narrative choice has technological consequences. In today’s context, this could describe many companies.

How models are trained, how products are designed, how interfaces are opened, how content is distributed, how founders speak, and how launches are presented—all these seemingly engineering, operational, marketing, and PR issues are collectively shaping a new social reality.

Therefore, future corporate competition will increasingly resemble a contest: who can better translate machine capabilities into social realities.

Social realities include whether users are willing to adopt, whether developers are willing to integrate, whether capital is willing to invest, whether regulators accept, whether talent joins, and whether ordinary people believe it will change the future. Technology is important, but whether it enters society depends ultimately on media filtering.

Because of this, many companies today are starting to resemble “systems with their own personality.” They have both technological cores and public voices; internal automation and external narratives; organizations and interfaces; producing products and expectations.

The internet we know is being ended by AI, along with the underlying logic of online earning.

For ordinary people, the real change is in the logic of work survival.

Here, the question can’t just stay at the company level.

Because once a company becomes “half media, half machine,” individual career paths will also change. Many once believed that as long as they quietly do good work, their value will be recognized.

Today, that path is narrowing. You still need to do your job well, but that’s no longer enough. You also need to explain your value, connect your abilities to systems, and be understood, trusted, and called upon in an increasingly complex information environment.

The division of many future roles may not mainly depend on “using AI.” The deeper split will happen along another axis.

Some will become appendages of systems—scheduled by processes, compressed by models, driven by metrics, working more like maintaining a giant machine; others will become interface talents—understanding systems, organizing narratives, collaborating with machines, communicating with people, creating capabilities, and explaining why their work matters.

The latter will become increasingly valuable.

Because in such an era, knowledge itself is becoming cheaper, and systems that invoke knowledge are more widespread. The truly scarce skills are judgment, translation, integration, organization, and giving meaning.

Can you clearly explain complex systems? Can you turn data into shareable stories? Can you build trust amid noise? These will become new professional moats.

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Finally, what’s truly contested is the operating system of the new era.

The fusion of media and machines is becoming the operating system of this age.

Many still see AI as a technological revolution, but on a larger scale, it’s more like an environmental revolution. It rewrites not just a few industries or jobs but how companies exist, how people work, and how reality is organized.

Future companies won’t just be more efficient—they will be better at shaping environments.

Internally, they increasingly resemble machines—seeking callability, replicability, and scalability. Externally, they increasingly resemble media—seeking dissemination, interpretability, and recognition. They build infrastructure and cognitive frameworks; organize actions and feelings; compete in markets and in the language of the times.

Therefore, the most important change to watch for today isn’t just who AI replaces, but who controls both capability and perception. They influence not only how you do things but also how you see the world.

When companies start to resemble both media and machines, the history of business has already turned the page. The next question depends on who can first understand this page.