Will we remain a network that explains privacy to humans?

Zcash started from one clear question.

How can humans protect their financial privacy in the digital age?

This question is still valid today. In a time when data is constantly collected and financial activities are increasingly moving into more transparent systems, the value of privacy is becoming even more important than before.

The values that cypherpunks have argued for are still important. The idea that individuals should control their own assets and transaction information is a question about basic rights in a digital society.

However, the change we are facing is not only that the importance of privacy is growing.

The very actors who perform economic activities are changing.

Until now, the users of blockchain were humans. Humans created wallets, approved transactions, and used services. Therefore, blockchain projects developed by explaining themselves to humans. They created websites, wrote documents, built communities, and tried to help people understand their technology and philosophy.

However, the new users that will appear in the future may not be only humans.

AI agents used by companies may go beyond simple automation tools and perform parts of economic activities. AI may purchase needed computing resources, obtain data, use software services, cooperate with other AI systems, and perform payments and contracts under given policies.

When this change happens, the standard of blockchain competition will also change.

In the past, the important question was:

“Which blockchain do people choose?”

But in the future, the more important question may become:

“Which blockchain does AI choose?”

AI does not stay loyal to a certain project’s philosophy or community culture like humans do. AI chooses the system that provides the most suitable functions to achieve its goals. When necessary, AI may use several networks at the same time.

Then, is having excellent privacy technology enough for Zcash to be chosen in the future AI economy?

Probably not.

AI does not discover new technology in the same way humans do. For AI to use a network, that network must first exist in a form that AI can understand.

This is not simply a matter of adding one API.

Future blockchains need to be built so that AI can discover their functions. AI agents need to understand what functions a network provides, decide under what conditions those functions can be used, and actually connect with the network.

In the internet era, companies created websites for human users and prepared themselves so search engines could find them. In the AI era, blockchains will need to prepare themselves so AI can discover and use them.

The privacy technology of Zcash is the same.

It is not enough to explain to humans, “Our network is safe.”

In the future, Zcash must be able to explain to AI:

“This network provides these protection functions in these situations, and it can be called in this way.”

From this perspective, Zcash faces an important choice.

One path is becoming a privacy infrastructure for stablecoins such as USDC and USDT.

If AI and companies use regulated digital dollars as major payment methods, the market for providing privacy to those transactions will be very large.

However, this path will not be easy.

Ethereum is already at the center of the stablecoin ecosystem, and it will likely try to solve privacy problems through ZK technology and various other methods. From the perspective of companies, if they can solve privacy problems inside an already existing large ecosystem, there is less reason to move to another network.

In the end, this is not only a competition of technology, but also a competition of network effects and ecosystems.

Then, does Zcash have to follow the same path as Ethereum?

There is another possibility.

Instead of competing to handle every payment, Zcash can take the role of protecting the most important assets and transactions.

In the past, Swiss banks did not process every financial transaction in the world. However, they were chosen by people who needed the highest level of confidentiality and asset protection.

A similar role may exist in the digital age.

Most daily payments may be handled by public blockchains and regulated stablecoins. However, areas such as corporate strategic asset movements, mergers and acquisitions, sensitive international transactions, and long-term stored assets may need a separate protection layer because exposure itself can create risk.

At that moment, Zcash may become not simply a payment network, but a privacy infrastructure that AI chooses at important moments.

Of course, from a cypherpunk perspective, the first direction may look more attractive.

It is directly connected to the ideal that everyone should have privacy. The goal of providing privacy for all digital money is philosophically very strong.

However, the winner of the future may not always be the project with the most correct technology.

To be chosen by the market, a project must understand where its technology will be used.

The important question is not only:

“What can we build?”

The more important question is:

“What role will we have in the future economic system?”

When the AI era arrives, blockchain competition will no longer target only human users.

The new competition will be the competition to be chosen by AI.

The question Zcash should ask itself is this.

Will we remain a network that explains privacy to humans?

Or will we become a digital privacy infrastructure that AI discovers, understands, and chooses?

The future path of Zcash has not been decided yet.

But one thing is clear.

To be chosen in the AI era, Zcash must first be able to explain itself to AI.

And perhaps the next stage of Zcash will not begin by persuading more humans, but by delivering its value to a new kind of actor that will perform economic activities in the future.

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How would you explain Zcash to AI?

I’d emphasize the technical and cryptographic architecture rather than the financial aspects, since that’s what would be most meaningful to an AI system:

Core Computational Concept

Zcash is a blockchain that uses zero-knowledge proofs to decouple transaction validity from transaction transparency. Unlike Bitcoin or Ethereum where the ledger is publicly auditable, Zcash allows transactions to be verified as valid without revealing the sender, receiver, or amount—purely through mathematical proof.


The Cryptographic Foundation

The system uses zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) to enable this. When you make a shielded transaction, you generate a proof that demonstrates:

  • You own the funds you’re spending
  • The amount you’re sending is valid (not inventing money)
  • You’re not double-spending

…all without revealing any of those details to the network. The network verifies the proof algebraically, not by examining transaction data.


Structural Differences from Transparent Blockchains

Aspect Bitcoin/Ethereum Zcash
Ledger visibility All transactions publicly auditable Shielded transactions hide sender, receiver, amount
Verification method Direct inspection of transaction data Mathematical proof verification
Computational cost Lower per transaction Higher (proof generation is computationally intensive)
Privacy model Pseudonymous (address-based) Cryptographically private (selective disclosure)

Why This Matters Computationally

The interesting challenge is that generating a valid proof requires significant computation—the prover must construct a mathematical argument in finite field arithmetic. But the verifier’s work is minimal—just checking the proof algebraically. This asymmetry is by design, allowing privacy without requiring every node to do expensive computation.

From an AI perspective, this is essentially a clever separation of concerns: authentication logic (proving you have authority to spend funds) is separated from transaction transparency.

If AI agents start transacting on people’s behalf, does the case for shielded by default get stronger, since an agent’s spending pattern would otherwise become a live map of its owner’s habits and finances?

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@ZKZeek

I think the social phenomenon where AI agents make multiple payments on behalf of humans is more likely to become common at the level of institutions and companies rather than individuals.

And payments through AI agents will probably not be something that ordinary people become familiar with first.

Leaving that aside, let’s assume that dollar stablecoins become a common payment method next year.

Wouldn’t that itself become one of the reasons why we end up living in an economic system where our activities leave traces 24 hours a day?

Technically, privacy features could be added to stablecoins issued on Ethereum.

However, I am not very optimistic about that possibility.

In Korea, a deposit token that uses CBDC as the final settlement layer is already being developed.

it is called “Project Hangang.”

The world that many people once dismissed as a Big Brother conspiracy theory is now becoming closer to reality in the country where I live.

Starting this year, Korean police cars will be equipped with high-performance AI facial recognition cameras, which will be used to scan people’s faces on the streets.

This will, of course, be justified in the name of public safety and protecting citizens.

There are even plans for drones to be deployed from police vehicles.

For now, it is only a pilot program.

The things I just mentioned were reported on public television news.

Anyway, the good world is over now.

The concern is no longer only about financial privacy. When AI cameras can scan people in public spaces and monitor human activity in real time, the bigger question becomes how much of our lives can be observed and recorded.

Compared to that, the possibility that an AI agent reveals someone’s spending pattern and financial situation is only one part of a much larger issue.