Opening

Over the past two decades, we’ve learned to live alongside software. Apps promised convenience, entertainment, and efficiency; we learned to pay monthly, accept ad targeting, and give up a slice of privacy. Yet a quiet shift is underway.

The trigger is the recent breakthrough pace in AI. This isn’t merely “a new technology.” It’s a redistribution of power. When the barrier to producing software collapses—when ordinary people can ask for tools in natural language and get them—an industry structure that has held for decades starts to wobble.

This essay traces that paradigm shift: it critiques the old model, explains how AI reshapes the “production relations” of software, maps today’s technical bottlenecks, and sketches a digital future centered on personal cognitive sovereignty.

Part I: The Hidden Power Structure

Appearance vs. reality

Software companies claim to be “user-centric.” They refine UX, ship features, and personalize endlessly. But beneath the surface sits an asymmetric power relationship.

The real controller is the company. Your data, behavior, and preferences are turned into a precise profile—the raw material for model optimization and monetization. The more convenience you enjoy, the more quietly you outsource judgment and autonomy.

How the attention economy extracts value

“Attention economy” has been discussed for years, but the deeper mechanism deserves a sharper look.

Its essence isn’t merely fighting for your time. It’s the systematic extraction of human cognitive resources. That extraction shows up in three layers:

Time extraction: infinite scroll, autoplay, and the removal of stopping cues make leaving difficult.

Willpower extraction: dopamine loops reshape habits, gradually eroding self-control until “five more minutes” becomes the norm.

Data extraction: behavior data is harvested to train more precise recommendation systems, creating a subtler and harder-to-detect control loop.

When choice itself is engineered, the boundaries of free will blur. This isn’t about “users choosing poorly.” It’s about a digital environment designed so that leaving is structurally hard.

Part II: The User’s Dilemma and Anxiety

The loop of emptiness and anxiety

What do users actually get from these apps? A short burst of pleasure, instant gratification—and then a deeper emptiness and anxiety that pushes them toward the next consumable. It’s a classic existential trap.

Stimulus triggers dopamine; dopamine raises the threshold for pleasure; higher thresholds require stronger stimulus; stronger stimulus consumes more energy—until you land in numbness. To escape the numbness, you return to the same stimulus source, and the cycle hardens.

Three deeper forces reinforce this dilemma:

Lack of substitutes: offline social life, deep reading, and creative work—the “slow satisfaction” activities—get pushed to the margins.

Structural constraints: high-intensity work leaves people too exhausted to do anything but “collapse and scroll.”

Cognitive fatigue: constant information processing and micro-decisions make algorithmic guidance feel like relief.

This isn’t a personal discipline failure. It’s a systemic trap: the design logic of the ecosystem is to make you stay.

Part III: The Paradigm Shift AI Brings

The collapse of the barrier to building

AI’s rapid progress is changing the production relations of software at the root.

Before, if you had a need, you searched for a product, subscribed, or bought a license. It was a passive consumption path: “need → find software → pay.”

Now you can describe the need in plain language, and AI can generate a working solution. It becomes an active creation path: “need → conversation → generation.”

Software shifts from “standardized products” to “personalized services,” from “buy and use” to “create on demand.”

The weakening of the SaaS model

Recent drawdowns in software stocks reflect this reassessment: investors are questioning what software companies will be worth in the next decade.

Core assumptions that once supported SaaS valuations are being challenged:

Software won’t disappear, but it must evolve. Viable paths include moving down the stack (cloud, databases, models), going extremely vertical (medicine, law, other professional domains), or leaning on strong social network effects.

The democratization of software-making

“Everyone can build their own software” is turning from slogan into reality.

The software pyramid is collapsing: from professional programmers, to no-code/low-code, to natural-language programming—until each person becomes the product manager for their own needs.

But new problems emerge: how do you manage your personally generated tools? How do you ensure quality and safety? How do you accumulate and reuse what you’ve built? These are now urgent questions.

Part IV: Today’s Technical Bottlenecks

The personal AI vision faces four major technical bottlenecks:

Data management: your data is scattered across platforms and apps; there is no unified personal data layer.

Tool coordination: AI-generated tools don’t “know” each other; standardized interoperability protocols are missing.

Memory at scale: AI can’t reliably learn and maintain long-term personal context; it needs durable memory management.

Cross-system interaction: different AI systems can’t communicate effectively; AI-to-AI interoperability standards are immature.

Solving these problems will create new platforms—not closed ecosystems controlled by a single company, but open-standard meshes. Just as HTTP connected websites, we will need protocols that connect AI tools.

And, over time, engineering tends to close these gaps.

Part V: The Endgame—The Return of Cognitive Sovereignty

From “platforms control users” to “users control AI”

The debate over AI’s role in human decisions never stops. Some argue that AI crosses a line when it influences value-laden choices. That concern is valid.

But the key question is: Who is AI loyal to?

Most AI today is loyal to platforms: maximize time spent, boost ad conversion, optimize revenue.

The AI we should want is loyal to users: protect attention, preserve long-term well-being, and help achieve personal goals.

This isn’t rejecting technology. It’s reclaiming control of it—shifting power from “platforms control users” to “users control AI.”

Personal foundation models: a digital soulmate

A true “agent” would be this: each person has a personal AI model that understands their physical condition and their inner world.

Such an AI would have four traits:

Personalized: it learns what is unique about you, rather than forcing you into generic templates.

Continuously evolving: it grows with you, records change, and adapts over time.

Goal-oriented: it understands your long-term values and direction.

Supportive and corrective: it helps you progress, and it nudges you back when you drift—rather than simply indulging you.

This is not a mere tool. It’s a collaborator in life—a digital-era soulmate.

The return of cognitive sovereignty

The deeper meaning of this vision is cognitive sovereignty: becoming the owner of your digital life again.

Realizing this vision requires four conditions:

Technical: personal AI needs access to enough data to truly understand you.

Economic: its business model must not conflict with user interests.

Legal: users must genuinely own their data and models.

Philosophical: AI should be framed as “human augmentation,” not “human replacement.”

Closing

We are standing at a historical turning point.

In the past, software harvested users. Now AI offers a path to reclaim control. In the future, each of us may have a digital soulmate.

This isn’t a tech utopia. It’s a technological revival of human autonomy.

Still, the vision carries real challenges: how do we keep AI aligned with a user’s life philosophy over years? How do we balance deep understanding with privacy? How do we avoid unhealthy dependence on a single AI system? The answers will emerge only through technical iteration and social experimentation.

The core question remains: in the digital age, is autonomy still possible—and if so, how?

The answer may be: not by rejecting technology, but by reclaiming control over it; not by consuming passively, but by actively constructing your digital environment. That demands a new kind of digital civic literacy—treating technology as an extension of the self, not a loss of the self.