De-commodification: Possibly the only correct solution for the future of the crypto industry

Written by: Jtsong.eth (Ø，G)

The crypto industry has always talked about Mass Adoption, but in reality:

Users always stay as trading users, not “users.”

And AI may help blockchains achieve true “value accumulation.”

Introduction: When users become “AI”

If we look back honestly at the crypto industry of the past decade, we’ll find a very simple fact—one that’s often overlooked: at its core, the crypto industry’s products have always been “serving human nature.” This is also the core driving force behind crypto’s cycle after cycle of bull markets.

So what is human nature?

Profit-seeking

Gambling psychology

Preference for leverage

Short-term feedback dependence

So the whole industry naturally evolved the most successful playbook:

Issuing assets + trading + PVP (game-playing)

From ICOs to DeFi Summer to NFTs to Memecoins, at their core, they’ve all revolved around:

“Can I buy earlier?”

“Can I sell faster?”

“Can I profit from other people’s losses?”

Given the premise that “users are human,” this logic is not only reasonable—it’s the optimal solution.

Because:

Nothing drives user growth more than a “profit expectation.”

But the problem is that the ceiling of this system was effectively written in from the start. Because it relies on:

Human irrationality

Market sentiment swings

The continuous inflow of new capital

Once these factors weaken, the whole system quickly loses speed. Why is the overall market bearish right now? It’s because old weeds are becoming more rational, while new capital simply doesn’t come in recklessly.

A more critical change is happening

In the past, we defaulted to:

Blockchain users = humans

But in the future, this equation may be rewritten entirely:

Primary blockchain users = AI Agents

When AI starts to become the main participant on-chain, everything changes.

Humans vs. AI: two completely different “user personas”

Human users:

Driven by emotion

Prefer high risk and high returns

Can tolerate uncertainty

Easily influenced by narratives

AI users:

Don’t participate in gambling

Not driven by emotion

Seek certainty and efficiency

Require trustworthy data and execution environments

This means:

The “casino model” is ineffective for AI.

AI won’t FOMO—it only does three things:

Compute

Execute

Optimize

The real value of blockchain is being redefined

When the service target shifts from “humans” to “AI,” the most core value of blockchain also changes:

From:

Asset issuance

Liquidity

Speculation

To:

Determinism

Verifiability

Trustless Execution

And these three points are exactly the “must-haves” for AI systems.

Why is this critical?

Because AI systems themselves have a fundamental problem:

Black Box

Model decisions are not explainable

Data sources are not verifiable

Reasoning processes are not auditable

In the Web2 world, this can be tolerated, but when it comes to:

Financial decisions

Automated trading

Agent collaboration

Data assets

these problems become systemic risks.

And blockchain provides a solution:

“Bring AI’s key process onto the chain”

Data sources can be verified

Inference results can be proven

Behavior records are traceable

This is not just a “bonus”—it’s:

The infrastructure required for AI to be deployed at scale.

One important conclusion

When the main users of the crypto industry are still humans:

Playing human nature is correct.

But when the main users start becoming AI:

Playing determinism is the only solution.

And this is also why:

The next generation of Mass Adoption in crypto is essentially a process of “de-casinonization.”

The casino model’s boom is fundamentally a short-term structural windfall

We have to admit that the casino model is successful.

It has several very strong advantages:

Extremely strong user motivation (profit expectations)

Very high liquidity turnover (high-frequency trading)

Very low barriers to understanding (buy the up / buy the down)

But these advantages are also its ceiling.

Where is the bottleneck of the casino model?

If you stretch the time horizon, the casino model will gradually reveal several inevitable problems:

1. User growth is not sustainable (depends on the “new weed” model)

The casino model is essentially PVP, not PVE.

That means:

The profits of one group of people must be built on the losses of another group.

This directly leads to:

User growth highly depends on “incremental capital”

Once incremental users slow down, the system starts to cannibalize itself

Very low retention—most users participate only once

Ultimately forming a typical structure:

“Traffic-driven → Bubble expansion → Liquidity depletion → Price collapse”

2. Can’t accumulate long-term value (no “productive” aspect)

The casino model hardly creates real value—it only transfers value.

By contrast:

Web2 creates information, content, and network effects

AI creates productivity and automation capabilities

And most crypto applications:

Are just “more efficient tools for speculation”

This leads to a core problem:

Capital can enter, but it won’t stay long-term.

3. Regulatory pressure is inherently present

When an industry’s core activities are:

High-frequency trading

Leverage

Speculation

then it will naturally be classified as:

A financial risk system, not a technology innovation system

That’s also why, globally:

Exchanges are regulated most strictly

Token issuance is continuously scrutinized

DeFi has stayed in the gray zone

The more successful the casino model is, the stronger the regulation becomes.

4. Product experience can’t break out of the niche

Most “casino-style products” have a problem:

Strong financial attributes

High risk cognition

High learning costs

For Web2 users:

There’s no need to take on complexity + risk just to “possibly make money.”

So the crypto industry has always talked about Mass Adoption, but in reality:

Users remain trading users, not “users.”

The real breakthrough: shift from a “financial system” to a “productivity system”

If the past crypto industry solved:

“How to trade value more efficiently”

then the next phase must solve:

“How to create new value”

And that answer very likely comes from:

AI × Blockchain

AI is essentially a productivity tool, and blockchain is essentially:

On-chain attribution (proof of ownership)

Settlement

Verifiability

The core significance of combining the two is:

To make both the “production process” and the “production outcomes” recordable, verifiable, and tokenizable.

This is a completely different path from the casino model.

A key paradigm shift: from “trading assets” to “generating assets”

In the past:

Tokens were fundraising tools

NFTs were collectibles

User behavior = trading

In the future:

Data is an asset

Models are assets

The behavior of an AI Agent is also an asset

User behavior will become:

Create → Use → Reuse → Earn

Not just buy and sell.

Case: How 0G Labs turns “memory” into an asset

Taking 0G as an example, you can see a very different path.

One core module of 0G is decentralized storage + AI computation, which enables a very key capability:

On-chain AI Memory (memory)

What does that mean?

In traditional AI systems:

User data is stored on the platform

AI “memory” is not transferable

All value belongs to the platform

But in an architecture like 0G:

User interaction data can be recorded on-chain

AI memory can become a verifiable, ownable asset

Different applications can share the same “memory layer”

This directly brings several changes:

1. Memory becomes an asset (Memory as Asset)

Your:

Usage habits

Preferences

Data trails

is no longer just “data exploited by the platform,” but instead:

An asset you can own, authorize, and even monetize

2. AI Agents have “inheritable state”

In traditional AI:

Each application is an island

Context can’t be migrated

But on-chain:

AI Agents can share memory across applications

This means:

AI is no longer a one-time tool

It becomes a “digitally embodied thing” that continues to grow

3. New business models start to emerge

When “memory” can be assetized:

Data markets

Agent economies

Personalized AI services

will all become real PVE (value-creation) systems

instead of PVP.

Conclusion: The essence of Mass Adoption is “de-casinonization”

For the crypto industry to truly move to the next stage, it must complete a fundamental transformation:

From:

Asset issuance + trading-driven

to:

Productivity-driven + value creation

That is:

De-Casinoization

This doesn’t mean trading disappears; it’s just that:

Trading is no longer the core

Speculation is no longer the only entry point

Users are no longer just “gamblers,” but “creators”

The previous generation of crypto industry made money flow.

The next generation of crypto industry will make value get created.

And AI may be the most important variable on this path.