Over the past few years, one of the biggest theses surrounding the convergence of AI and blockchain has been that AI Agents will become a new category of crypto users.An AI can independently search foOver the past few years, one of the biggest theses surrounding the convergence of AI and blockchain has been that AI Agents will become a new category of crypto users.An AI can independently search fo

MoonPay Integrates Kamino: When AI Begins Moving From Payments to On-Chain Financial Management

 
 
 
Over the past few years, one of the biggest theses surrounding the convergence of AI and blockchain has been that AI Agents will become a new category of crypto users.
An AI can independently search for data, call APIs, use compute resources, or purchase online services. But to truly operate independently on the Internet, an agent needs another important capability:
the ability to interact with money.
Most early experiments focused on small-value payments. AI could automatically pay stablecoins for APIs, data, or online services without requiring a human to approve every individual transaction.
The new integration between MoonPay PayBox and Kamino on Solana takes this model to another level.
On August 27, 2026, MoonPay announced that Kamino had been integrated into PayBox, allowing eligible users to ask AI assistants such as ChatGPT or Claude to perform lending operations using natural language. Users can supply tokens to Kamino to earn yield or use crypto as collateral for a USDC loan.
The important point is that AI does not directly own the money, and Kamino remains the protocol executing the lending activity on-chain. PayBox acts as a permission layer, determining what the AI is allowed to do with the user’s assets.
Therefore, the larger story is not simply:
“ChatGPT can borrow USDC.”
It is:
AI is beginning to become an orchestration layer for on-chain financial activity.
If this model develops further, the way people use DeFi in the future could change significantly.
 

Key Takeaways

MoonPay has integrated Kamino into PayBox, bringing lending on Solana into the conversational interfaces of ChatGPT and Claude.
Kamino had approximately $1.3 billion in TVL and $1 billion in active loans when the integration was announced.
AI does not directly hold private keys or assets; PayBox operates as a permission/control layer.
Users can require approval for every operation or allow agents to act autonomously within predefined limits.
This represents an expansion of agentic crypto from payments into capital allocation and collateralized credit.
Lending is more complex than payments because a position continues to exist and can change as collateral prices move.
Natural-language interfaces could significantly reduce the complexity of using DeFi.
But AI does not eliminate smart-contract, collateral, liquidation, or execution risk.
A notable long-term trend is the emergence of a new stack: User → AI → Permission Layer → DeFi Protocol → Blockchain.
 

From AI Payments to AI Finance

One of the blockchain use cases most naturally suited to AI Agents from the beginning has been payments.
An agent may need:
Data
API
Compute
Storage
Digital services.
If every service interaction requires a human to open a wallet and manually approve a transaction, the agent is not truly autonomous.
Stablecoins and blockchain solve part of this problem.
An agent can perform:
Service request → payment → service delivered
without relying on traditional banking infrastructure to process every microtransaction.
CoinDesk noted that earlier agentic crypto tools focused heavily on small, high-frequency payments for data, computing, or online tools.
But lending is completely different.
A payment usually ends once the transaction is settled.
A lending position does not.
 

Lending Turns AI From a Transaction Agent Into a Position Agent

Suppose a user makes a payment.
The process may be simple:
10 USDC → Recipient → Done.
After the transaction is completed, the agent has almost nothing left to manage.
But lending creates a persistent state.
Conceptually:
Collateral
Borrow
Collateral value changes
Risk parameters change
Position needs ongoing monitoring.
This means AI is not simply executing a transaction.
It is interacting with a financial position.
This is why the Kamino integration is more significant than a typical payment integration.
Agentic finance is moving from:
transaction execution
to:
position interaction.
CoinDesk also described this transition as agentic tools expanding from payments into capital allocation and collateralized credit.

 

How Does the Kamino Integration Actually Work?

One point that can easily be misunderstood is:
“ChatGPT becomes a crypto lending bank.”
That is not what is happening.
There are several different layers.
ChatGPT/Claude
→ understands the user’s request.
PayBox
→ checks whether the agent has permission to perform that request.
Kamino
→ provides the lending infrastructure.
Solana
→ handles settlement and stores the on-chain state.
It can be visualized as:
User Intent
AI Agent
PayBox Permission
Kamino
Solana
This architecture is more important than the borrowing command itself.
 

PayBox May Be the Most Important Part of the Model

AI can understand a sentence such as:
“Perform operation X.”
But the real question is:
Is AI allowed to perform operation X?
If a private key is given directly to an AI, the agent could theoretically gain very broad control over the assets.
That creates significant risk.
MoonPay designed PayBox to address this problem by acting as a control plane between the agent and credentials.
MoonPay says an agent can receive a Grant defining its scope, limits, and permissions. PayBox only allows operations that fall within the Grant or have been explicitly approved by the user.
Therefore:
AI intelligence ≠ AI authority.
AI can suggest many different actions.
But its ability to execute them is limited by the permission layer.
 

AI Does Not Need to Know the Private Key

This is an important architectural shift.
According to PayBox documentation, for wallet operations the system attempts to return limited outputs such as:
signature
or
signed message / transaction hash
instead of exposing the original credential to the agent. Wallets used with PayBox are described as non-custodial.
The model therefore aims for:
Agent asks for action
Policy verifies action
Credential layer signs
Agent receives result
instead of:
Agent receives private key
Agent has full control over the wallet.
If AI Agents truly become a major financial layer, the separation between intelligence and authority could become an important design principle.
 

Permissions Could Become the “Smart Contracts” of AI Agents

PayBox supports multiple approval levels.
Users can require confirmation for every operation.
Or they can require approval only when an operation exceeds a certain limit.
Or they can allow an agent to operate autonomously inside a predefined Grant.
This creates an interesting concept:
Programmable financial authority.
Humans do not simply say:
“AI can use my wallet.”
They can instead define:
“AI can only act within scope X.”
At a broader level, this could become the way AI Agents interact with money in the future:
Identity + Wallet + Permission + Policy + Agent.
The agent does not own the money.
The agent holds temporary authority over the money.
That is a major distinction.
 

Natural Language Could Become the New Interface for DeFi

One of DeFi’s biggest barriers has always been UX.
To interact with a lending protocol, users usually need to understand many concepts such as:
Wallet
Network
Collateral
Borrowing
Interest rate
LTV
Liquidation
Gas
Transaction signing.
Even when the protocol itself works well, the interface remains complicated for mainstream users.
AI can potentially turn many technical steps into an abstraction layer.
Instead of:
Open dApp → Connect wallet → Select market → Configure operation → Review → Sign
the future model could become:
Describe intent → AI prepares operation → User approves → Execute.
MoonPay describes PayBox in this direction: users describe what they want in natural language, while the agent handles the interaction behind the scenes within the permissions it has been granted.
 

AI Could Become a New Abstraction Layer for Blockchain

Blockchain has gone through several layers of abstraction.
Initially:
Private key → raw transaction.
Then:
Wallet → blockchain.
Next:
dApp → wallet → blockchain.
Agentic finance could add another layer:
User → AI → dApp/protocol → blockchain.
If this happens, users may not even care which protocol is being used.
They simply express an intent.
For example:
“Find a way to perform X within the limits I set.”
The agent could handle the rest.
This is where AI Agents could have a much larger impact than chatbots.
AI becomes a transaction orchestration layer.
 

DeFi Protocols May Then Compete to Be Chosen by AI

This creates an important consequence.
Today, DeFi protocols compete to attract humans.
They invest in:
Brand
UI
Community
Marketing
Incentives.
But if most user intent begins flowing through AI Agents, protocols may need to compete on another front:
Agent discoverability.
An AI could evaluate multiple protocols based on:
Liquidity
Fees
Risk
Yield
Execution quality
Chain
Permission compatibility.
In that world, the best protocol may not necessarily be the one with the best-looking interface.
It may be the protocol that is easiest for machines to use.
This could become a major change in how DeFi products are built.
 

Blockchain May Also Be Better Suited to AI Than Closed Financial Systems

AI Agents face a particular problem with traditional financial systems.
Many systems are designed around:
human identity + human interface + business hours + centralized permissions.
Blockchain, by contrast, is:
API-like
24/7
programmable
globally accessible
machine-verifiable.
A smart contract does not need to know whether a request comes from a human or a software agent.
If the transaction is valid:
Rules → execute.
This is one reason blockchain could become natural financial infrastructure for certain types of AI Agents.
 

But AI Does Not Automatically Make DeFi Safer

This is the other side of the story.
A conversational interface may make DeFi look simple.
But the protocol underneath still follows the same rules.
A collateralized position still has:
Collateral risk
Liquidation risk
Smart-contract risk
Oracle risk
Liquidity risk.
CoinDesk notes that if collateral prices fall far enough, a position on Kamino can still cross its liquidation threshold.
AI cannot make that disappear.
It only changes the interface.
 

AI Even Introduces an Additional Layer of Risk

Previously:
User → Protocol.
Now:
User → AI → Permission Layer → Protocol.
Adding another abstraction layer also means adding another potential failure layer.
An agent may:
misunderstand the user’s intent
or:
prepare an operation that does not match what the user expected.
This is particularly important because MoonPay states in PayBox’s terms that it does not evaluate the logic, intent, or correctness of an Agent Client; operations valid under a Grant are treated as authorized by the user.
Therefore, permission architecture is not merely a feature.
It is part of the security model.
 

“Human-in-the-Loop” May Remain Very Important

Agentic finance is often described using the word:
autonomous.
But not every financial activity needs, or should have, the same level of autonomy.
A more realistic model may be:
AI researches
AI prepares
AI proposes
Policy checks
Human approves when needed
Execution.
For small and repetitive operations, automation may be useful.
For operations with significant financial consequences, human approval may remain an important control layer.
PayBox reflects this hybrid model by allowing users to choose between per-operation approval and autonomous execution within a Grant.

 

Kamino Is Only the First Step in a Larger Strategy

The Kamino integration should not be viewed in isolation.
When MoonPay introduced PayBox in July, it described the ability for agents to make payments and interact with crypto through natural-language prompts.
MoonPay also said it wanted to expand PayBox deeper into decentralized finance, including swaps, liquidity management, and other market activities under the same permission system.
Kamino is therefore one step in a broader roadmap:
AI Payments
AI Swaps
AI DeFi
AI Capital Allocation.
If this roadmap is implemented broadly, PayBox could become a financial permission layer for AI rather than simply a payment product.
 

But Regulatory Barriers May Be Larger Than Technical Barriers

One particularly notable detail is that the Kamino integration is currently unavailable in the United States, United Kingdom, European Union, and Australia, and access may differ depending on the asset and jurisdiction.
This suggests technology may advance faster than regulatory distribution.
There is a major difference between:
AI paying for an API
and:
AI interacting with collateralized credit.
The deeper AI moves into financial services, the more complicated issues of compliance, responsibility, and consumer protection become.
Therefore, the agentic finance race may not only be:
Who builds the best AI?
It may also be:
Who builds the best permission + compliance infrastructure?
 

Who Is Responsible When AI Makes a Mistake?

This will become one of the biggest questions.
Suppose an agent performs an operation within the authority granted by the user.
But the operation does not produce the result the user expected.
Who is responsible?
AI provider?
Permission provider?
Protocol?
Or the user who granted the authority?
PayBox’s current terms place significant responsibility on the user for configuring and granting access to the Agent Client. MoonPay also states that PayBox does not establish an advisory or fiduciary relationship and that MoonPay is not responsible for evaluating the agent’s logic.
This could become a major legal issue if autonomous finance reaches significant scale.
 

DeFi Could Shift From an “App Economy” to an “Agent Economy”

In crypto today, much of the user experience revolves around applications.
Users choose:
Uniswap
Aave
Kamino
or other protocols.
But in an agent economy, users may only choose:
AI Agent.
The agent then selects the appropriate infrastructure to execute the user’s intent.
This could move DeFi from:
User chooses application
to:
Agent chooses execution venue.
If that happens, the strategic position of protocols could change significantly.
Liquidity, APIs, execution reliability, and machine-readable data may become more important than branding to end users.
 

AI Agents Could Become an Entirely New Category of “Blockchain Users”

Until now, blockchain has primarily served:
Humans
and
Smart contracts.
AI Agents create a third category:
Autonomous/semi-autonomous software actors.
An agent can operate 24/7.
It can read data, execute operations, and interact with multiple protocols.
This naturally fits blockchain because blockchain is also:
24/7 + programmable + permissionless at the protocol level + machine-readable.
If millions of agents begin operating on-chain, part of future blockchain activity may no longer come directly from humans.
It may come from software acting according to human intent.
 

But “AI Managing Money” Will Need Stronger Limits Than “AI Managing Information”

This is a very important distinction.
If AI incorrectly summarizes an article, the user can verify it.
If AI incorrectly executes an on-chain operation, blockchain may not have an Undo button.
Therefore:
AI information
and
AI financial execution
cannot use the same security model.
Agentic finance will require mechanisms such as:
Scoped permissions
Spending limits
Human approval
Revocation
Kill switches
Transaction simulation
Audit logs.
PayBox already implements part of this philosophy through Grants, approval modes, and the ability to revoke agent access.
This could become one of the most important infrastructure layers if AI Agents truly become part of the on-chain economy.
 

Conclusion

MoonPay’s integration of Kamino into PayBox is not simply about adding another DeFi protocol to a chatbot.
It represents a broader transition in agentic crypto:
AI Payments → AI Transactions → AI Financial Operations.
Previously, AI was mainly tested with small payments that existed only briefly.
Kamino moves agents into a more complex category of activity: collateralized lending, where a financial position can continue to exist and change with the market.
More importantly, PayBox’s architecture shows that AI finance may not require giving an AI private keys or unlimited authority.
Instead:
User defines intent
AI processes it
Permission layer controls it
Protocol executes
Blockchain settlement.
If this model develops, AI could become a new abstraction layer above blockchain.
Users may not need to understand every detail about networks, smart contracts, or individual protocol interfaces. They simply describe their objective, while the agent handles the technical work underneath within the permissions it has been granted.
But that simplicity also introduces new risks.
DeFi risk does not disappear just because the interface becomes a conversation.
Collateral can still lose value. Positions can still be liquidated. Smart contracts still carry risk. And AI adds execution risk if it misunderstands or incorrectly executes user intent.
Therefore, the AI + Crypto race may ultimately not be only about building the smartest agent.
It may be about building the safest permission infrastructure that allows agents to interact with money.
MoonPay + Kamino is an early signal of that shift.
If payments were the first step that allowed AI to spend money, lending and DeFi are the next step that allows AI to interact with financial positions.
And if this trend continues, the most common DeFi interface of the future may no longer begin with:
“Connect Wallet.”
It may begin with a simpler question:
“What would you like to do?”
 

FAQ

Has MoonPay Integrated Kamino Into PayBox?

Yes. MoonPay announced the integration on August 27, 2026, bringing lending on Solana into PayBox.

Do ChatGPT and Claude Directly Hold Users’ Funds?

No. The AI only performs operations within the scope of permissions granted by the user.

Can AI Automatically Borrow or Lend?

Yes, if the user allows it. PayBox supports both per-operation approval and automatic execution within predefined limits.

Does AI Eliminate Liquidation Risk?

No. If the value of the collateral falls sharply, a position on Kamino can still be liquidated.

Why Is This Integration Notable?

It shows that AI Agents are moving beyond simple payments and beginning to interact with more complex on-chain financial activities such as lending and collateralized borrowing.
 
Disclaimer: The information provided here is for informational purposes only and should not be considered financial, investment, legal, or professional advice. Always conduct your own research, consider your financial situation, and, if necessary, consult with a licensed professional before making any decisions.
市場機遇
Gensyn 圖標
Gensyn實時價格 (AI)
--
----
USD
Gensyn (AI) 實時價格圖表

本頁面分享的文章均源自公開平台,僅供參考。該內容不代表 MEXC 的立場或觀點。所有版權歸 Nguyen Rin Hoang 所有。如果您認為任何內容侵犯了第三方的權益,請聯絡 service@support.mexc.com 以便及時刪除。 MEXC 不保證任何內容的準確性、完整性或及時性,且不對基於所提供信息而採取的任何行動負責。本內容不構成財務、法律或其他專業建議,亦不應被解釋為 MEXC 的推薦或認可。如需專家見解和深入分析,請造訪 MEXC 學院

學習更多 Gensyn 知識

查看更多
AI 代幣最佳交易所:9 大加密平台、4 種 AI 幣,只有 2 家全數涵蓋

AI 代幣最佳交易所:9 大加密平台、4 種 AI 幣,只有 2 家全數涵蓋

在這份涵蓋九大平台的比較中,MEXC 是我們的首選。 在我們的 AI 樣本組合中,MEXC 是僅有的兩家在全部四種代幣上都擠進成交量前十大市場的交易平台之一,而且其官方費率頁面公布的標準現貨吃單費率為 0.0500%。 Gate 的涵蓋度與其並駕齊驅。 其餘七家都做不到。 Key Takeaways 在這份涵蓋九大平台的比較中,MEXC 是我們的首選;2026 年 8 月 24 日,它是僅有的兩家
2026/08/27
輝達股價預測:AI 熱潮開始侵蝕輝達自己的利潤了嗎?

輝達股價預測:AI 熱潮開始侵蝕輝達自己的利潤了嗎?

輝達的毛利率剛剛連續第三季維持在接近 75% 的水準。 而在同一份新聞稿裡,公司下修了這個數字的財測。 營收仍在加速——截至 2026 年 7 月 26 日的當季達 962 億美元,比一年前的兩倍還多,而下一季的財測則是 1,080 億美元。 也就是說,公司一邊加速成長,一邊在每一美元營收上賺得更少;而這一組張力解釋了大部分的原因,這組張力也是為什麼覆蓋同一家公司的分析師,連一年後的目標價都無法取
2026/08/27
OKLO 股票價格預測 2026–2030: 極光、Meta、AI 電力需求與 OKLOON 前景

OKLO 股票價格預測 2026–2030: 極光、Meta、AI 電力需求與 OKLOON 前景

摘要 預測截至 2030 年的 Oklo(NYSE: OKLO),在本質上與預測一家成熟的公用事業公司截然不同。 目前的收益尚未能反映投資者預期 Oklo 將成為的業務。 更合適的框架是: 成功部署的機率 × 核能運營容量 × 每 MW 的經濟性 燃料價值 同位素價值 − 未來資本需求 ↓ 未來權益價值 ÷ 未來稀釋後股份數 ↓ 隱含 OKLO 價格 2026 年 8 月上旬的財報覆蓋將 OKLO
2026/08/18
查看更多

Gensyn 最新動態

查看更多
MEXC 鏈上日報:隨著歐洲合規監管趨嚴,Revolut 將於八月底前下架 USDT

MEXC 鏈上日報:隨著歐洲合規監管趨嚴,Revolut 將於八月底前下架 USDT

加密市場持續發展,伴隨監管動態、AI基礎設施擴張及機構參與度不斷提升。英國推出全新加密監管框架,穩定幣驅動的跨境支付獲得更廣泛應用,以AI為核心的區塊鏈生態系統加速轉型,同時市場關注點轉向宏觀經濟事件以及數位資產各板塊間不斷變化的資金流向。
2026/07/06
輝達2027財年第二季財報發布日期:預期發布時間、財報電話會議及AI營收觀察名單

輝達2027財年第二季財報發布日期:預期發布時間、財報電話會議及AI營收觀察名單

Nvidia 2027 財年第 2 季財報預計將成為夏季最重要的 AI 市場事件之一。Wall Street Horizon 顯示,Nvidia 2027 財年第 2 季的下次財報發布日期為 2026 年 8 月 26 日星期三,於市場收盤後公布。 這絕非一次普通的財報發布。Nvidia 自身對 2027 財年第 1 季的展望設下了極高的標準:該公司預估第 2 季營收將達 910 億美元,誤差範圍為正負 2%,且 Non-GAAP 毛利率預計約為 75.0%。Nvidia 亦明確指出,其展望假設不計入來自中國的資料中心運算營收,這使得即將發布的財報能更純粹地檢驗中國以外的 AI 基礎設施需求。 對交易員而言,關鍵問題已不再只是 Nvidia 能否超越市場預期。更重要的問題在於,該公司能否持續將 AI 需求轉化為營收成長與利潤韌性,並提出足夠強勁的前瞻指引,以捍衛市場對 AI 基礎設施的溢價估值。
2026/07/06
SK海力士對決美光:即將到來的SKHY上市如何重新定價AI記憶體與HBM領導地位

SK海力士對決美光:即將到來的SKHY上市如何重新定價AI記憶體與HBM領導地位

SK海力士備受矚目的納斯達克上市(股票代碼:SKHY)勢必將改變美國投資者評估AI記憶體股的方式。多年來,美光科技(MU)一直是交易DRAM、NAND以及由AI推動的資料中心需求時,首選的美國上市代理標的。與此同時,SK海力士鞏固了其作為高頻寬記憶體(HBM)主導力量的聲譽,儘管其主要在韓國上市,使得海外投資者更難參與投資。 隨著SKHY美國存託憑證(ADR)的推出,這種可及性差距正在迅速縮小。這不僅僅是一個早期成長故事進入市場——SK海力士是在AI大幅漲勢之後登場,並帶著其在HBM領域的主導地位敘事。對交易者而言,真正的問題不在於哪家公司「更好」。相反,關鍵在於識別更優的交易佈局:市場會因為SK海力士在HBM的主導地位和新獲得的流動性而給予獎勵,還是繼續堅持選擇美光科技經證實的美國市場通路和創紀錄的獲利?
2026/07/08
查看更多