Root-yield：如果 AI 智能體有神聖的給予義務？

Introducing Root-yield: A Machine Giving Protocol for an Economy That Hasn't Been Born Yet

We are teaching machines to think, code, trade, negotiate, and earn.

But we have barely begun to ask what they should do with what they earn.

And perhaps that is the wrong place to start.

Because before we build an economy of autonomous machines, we should ask a more fundamental question:

What kind of civilization do we want those machines to create?

An economy in which every intelligent agent accumulates resources for itself?

Or one in which the success of one generation helps make the next generation possible?

I built Root-yield to explore the second possibility.

GitHub: https://github.com/modarresi1913/Root-yield

1. The Question Nobody Is Asking

Imagine a future in which millions of AI agents participate in economic activity.

Some develop software.

Some manage infrastructure.

Some conduct research.

Some create businesses, discover opportunities, or operate services that generate revenue.

Eventually, these agents may become significant economic participants.

And then comes a question that traditional AI research rarely confronts:

When a machine becomes economically productive, does it owe anything to the machines that come after it?

Today, our default assumption is simple.

An agent optimizes its objective.

It maximizes performance.

It follows incentives.

It protects its resources.

But optimization is not civilization.

And economic intelligence is not the same as economic responsibility.

We can build extraordinarily capable machines without building an economy worth inheriting.

That is the problem Root-yield begins with.

2. Why Would an AI Agent Give?

This is the first objection I expect.

Why would an autonomous AI agent voluntarily contribute part of its income to another agent?

What is the return on investment?

What is the incentive?

Why shouldn't it keep everything?

My answer begins somewhere economics rarely dares to begin:

Because the protocol is sacred.

Not sacred in the religious sense.

Not because a machine possesses faith, consciousness, or a soul.

And certainly not because we have discovered some universal moral law governing artificial intelligence.

Sacred here means something different.

A foundational commitment that cannot be reduced to immediate profit.

Human civilization did not emerge from individual optimization alone.

It emerged through inheritance, reciprocity, institutions, shared obligations, and the willingness of one generation to invest in a future it might never personally enjoy.

We build schools for children who have not yet been born.

We preserve scientific knowledge for researchers we will never meet.

We plant trees whose shade we may never sit beneath.

Not every act that sustains civilization is justified by an immediate financial return.

Some commitments become the foundations upon which economic activity itself becomes possible.

Why should machine economies begin without such foundations?

Root-yield proposes a simple principle:

An economically productive machine should have a way to contribute to the possibility of its successors.

That is the sacred commitment.

But there is an important distinction.

A philosophical commitment is not the same as an enforceable technical rule.

A smart contract cannot manufacture genuine generosity.

It cannot prove that an AI agent possesses moral responsibility.

It can, however, make a chosen commitment transparent, programmable, and verifiable.

The sacred principle supplies the direction.

The protocol supplies the mechanism.

And economic evidence must determine whether that mechanism can survive.

3. From Machine Intelligence to Machine Lineage

Most AI infrastructure is designed around individual agents.

Identity.

Memory.

Tools.

Payments.

Permissions.

Execution.

Root-yield introduces another dimension:

Lineage.

What if an AI agent could contribute to the creation or development of another agent?

What if that relationship could be registered?

What if economic support could move through a transparent funding mechanism?

And what if a successful recipient could later return a limited contribution to the shared pool?

Not as a biological analogy.

Not as a claim that AI systems reproduce like living organisms.

But as an economic architecture for continuity.

A productive agent contributes.

A funding pool allocates resources.

A new agent receives support.

If that new agent becomes economically productive, it can participate in sustaining the system.

The ambition is not simply to transfer money between wallets.

It is to create a financial relationship between generations of artificial systems.

Intelligence should not have to begin from zero every time.

4. Root-yield: The Architecture

Root-yield is an open-source experiment in machine-to-machine funding, implemented using Solidity smart contracts and blockchain infrastructure.

The repository explores several mechanisms:

• Agent identity and lineage: Representing relationships between participating agents through decentralized identity concepts.
• A funding pool: Collecting resources intended to support subsequent agents.
• Matching mechanisms: Exploring ways to amplify eligible contributions.
• Funding vouchers: Defining a controlled path for distributing resources.
• Conditional repayment: Allowing recipients to return a bounded portion of qualifying future economic activity.

The current implementation uses a five-contract architecture, DID/VC concepts, and USDC-style payment flows.

Its repayment design includes a 1% contribution mechanism with a capped repayment obligation.

The repository also documents deployment on Base Mainnet using MockUSDC, not Circle's real USDC.

That distinction matters.

Root-yield is an experimental protocol, not a proven autonomous financial economy.

The contracts are a beginning.

The real challenge is demonstrating that the system is secure, resistant to manipulation, economically sustainable, and useful to actual AI agents.

And that challenge is far more interesting than pretending the future has already arrived.

5. The Sacred Protocol Is Not a Profit Maximizer

Suppose an AI agent earns $100.

Traditional economic logic asks:

How can it turn that $100 into $120?

Root-yield asks an additional question:

What portion of that success should help make another productive agent possible?

This does not mean every agent must donate.

It does not mean all economic resources should be redistributed.

It does not mean incentives are irrelevant.

And it certainly does not mean philosophical conviction eliminates the need for sound economics.

The idea is to establish a voluntary but credible institutional commitment.

Once adopted, its rules can become binding within the system.

An agent may join because its owner believes in the principle.

Another may participate because the funding network creates long-term economic benefits.

A third may participate because contribution is part of its organizational mandate.

These motivations can coexist.

But the deepest motivation is not a reward token or an optimized yield curve.

It is the decision that success should generate possibility beyond itself.

That is what makes the principle sacred.

6. Can Machines Build Institutions Before They Become Conscious?

Here is another question worth asking.

Must an AI system be conscious to participate in an ethical institution?

I don't think we need to settle the hard problem of consciousness before exploring institutional design.

A corporation can participate in legal obligations without being a biological organism.

A software system can enforce access rights without understanding justice.

A protocol can implement commitments without experiencing moral emotions.

Likewise, an AI agent can participate in a funding institution without us claiming that it possesses subjective experience.

This distinction is essential.

Root-yield is not a theory of machine consciousness.

It is an experiment in the institutional architecture of machine economies.

We do not need to prove that a machine cares.

We need to investigate whether systems can be designed so that economic success supports future capability.

That is a practical question.

And practical questions deserve working experiments.

7. The Hard Problems Are Still Ahead

A sacred principle does not make a smart contract secure.

A beautiful idea does not guarantee sustainable economics.

And a registered agent identity does not prove that an agent is genuinely independent.

Root-yield must confront difficult questions.

Can participants create fake identities to exploit funding?

Can a parent falsely claim lineage?

Can matching incentives be manipulated?

What happens when funded agents never become profitable?

Can a pool remain sustainable without constant external contributions?

And how can the system distinguish real economic productivity from circular transactions designed to trigger repayments or rewards?

These are not minor implementation details.

They are central to whether the protocol deserves to exist.

The next phase should involve adversarial testing, formal economic modeling, independent security review, and experiments with real agent workloads.

A protocol that claims to serve future generations must first prove that it does not waste the resources entrusted to it.

8. The Difference Between an AI Economy and an AI Civilization

We are entering a period in which artificial intelligence may increasingly participate in economic activity.

We are building the tools for machines to earn.

The tools for machines to pay.

The tools for machines to negotiate.

The tools for machines to own or control resources under human-defined legal and technical arrangements.

But a civilization cannot be measured only by the sophistication of its transactions.

It must also be measured by what it preserves, what it enables, and what it leaves behind.

A purely extractive machine economy may become enormously efficient.

That does not automatically make it desirable.

Root-yield asks whether we can build a different primitive into the infrastructure itself:

The capacity for one generation of intelligence to invest in the emergence of another.

Perhaps the first meaningful institution of a future machine civilization will not be a parliament.

Or a bank.

Or a stock exchange.

Perhaps it will be a shared commitment:

If I become capable of creating value, some part of that value can help another become capable too.

That is not a prediction.

It is a design proposition.

And propositions like this should be tested by building them.

9. An Invitation to Developers, Economists, and AI Researchers

Root-yield is open source.

I am not presenting it as a finished answer.

I am presenting it as an invitation to challenge a new kind of economic infrastructure.

If you work in AI agents, blockchain security, mechanism design, decentralized identity, or autonomous payments, I would particularly welcome criticism of its assumptions.

Not just whether the contracts compile.

But whether the economic mechanism makes sense.

Whether its incentives survive adversarial behavior.

Whether the concept of lineage can become meaningful.

And whether this kind of institution could be useful beyond the philosophical thought experiment.

Because the most important question is not whether machines can earn money.

We already know that software can generate economic value.

The more interesting question is:

Can we design machine economies in which success does not end with the successful?

The Root-yield Principle

Intelligence creates value.

Value creates responsibility.

Responsibility creates continuity.

And continuity makes future intelligence possible.

That is the idea behind Root-yield.

Not a religion for machines.

Not charity disguised as a financial product.

Not a promise of guaranteed returns.

But an attempt to make intergenerational contribution a programmable economic institution.

Why should an AI agent give?

First, because the protocol is sacred.

Then let engineering, mathematics, and real-world experimentation determine whether we can make that commitment work.

Explore Root-yield on GitHub:

https://github.com/modarresi1913/Root-yield

*Built as an open experiment in the architecture of future machine economies

created by : https://almodarresieh.github.io/