Hồ sơ của GED | Binance Square

For a long time, we have talked about AI as an assistant.
You ask it a question.
It gives you an answer.
You give it an instruction.
It helps you execute it.
With AI agents, this logic is changing.
AI is no longer limited to generating responses. It is starting to access real data, use tools, and execute actions within defined boundaries.
Binance Agent OS fits directly into this evolution.
Launched on August 20, 2026, Agent OS allows compatible AI agents to connect to the Binance ecosystem, access market data, and, depending on the permissions granted, perform certain trading operations.
And the first usage figures are already attracting attention.
90,000 Requests in a Single Day
According to data shared during the first weeks of Agent OS, the platform processed more than 90,000 requests in a single day.
That number is interesting.
But volume is not the only thing worth looking at.
The reported performance also shows a 97% success rate, with 95% of requests served in less than 60 milliseconds.
In other words, we are no longer looking at a simple technology demonstration.
Users and developers are already starting to connect AI agents to real financial infrastructure.
That is where things become much more interesting.
Chatbot vs. AI Agent
Let’s take a simple example.
You ask a chatbot:
“What is the price of Bitcoin?”
It gives you information.
Now imagine asking an agent:
“Monitor Bitcoin, analyze its performance, check my position, and notify me if certain conditions are met.”
The agent would then need to:
• Retrieve market data
• Analyze that data
• Access certain account information
• Apply the rules you defined
• Trigger an action when the conditions are met
This ability to move from answering to acting is what distinguishes an AI agent from a simple chatbot.
Binance Agent OS connects environments such as ChatGPT, Claude Code, Codex, and Cursor to certain Binance functionalities through MCP, the Model Context Protocol.
Why Market Data Matters
In trading, a few seconds can change a decision.
A human has to open multiple interfaces.
Check the price.
Review the portfolio.
Analyze the market.
Then make a decision.
An AI agent can combine several of these steps into a single workflow.
Binance states that its MCP currently provides access to market data and supported trading functionalities. Developers also have access to other Agent OS tools for wallet, payment, and on-chain activities.
This opens up a new possibility.
The agent is no longer just an analyst.
It becomes an interface between the user and financial infrastructure.
But Who Remains in Control?
This is probably the most important question.
Giving an AI access to financial data is one thing.
Allowing it to execute transactions is another.
Binance has therefore introduced a permission system.
Users can define which features the agent can access, the limits it can operate within, and how long its access remains active. Permissions can also be modified or revoked.
Agents also operate through a dedicated sub-account.
Withdrawals from that sub-account are blocked by default. This creates a separation between the funds available to the agent and the rest of the user's account.
This matters.
An AI that can trade is not necessarily an AI that can withdraw your funds to an external address.
That distinction is fundamental.
The Real Challenge: Autonomy
The arrival of AI agents in finance raises a broader question.
How much are we willing to delegate?
Imagine three levels.
Level 1:
AI analyzes the market.
You make the decision.
Level 2:
AI analyzes the market and prepares a transaction.
You approve it.
Level 3:
AI analyzes, decides, and executes within the limits you have defined.
Agent OS is moving the crypto ecosystem closer to this third level.
That is where risk management becomes critical.
The more autonomy an agent has, the more precise its permissions need to be.
90,000 Requests Do Not Mean 90,000 Autonomous Traders
We also need to avoid misinterpreting the number.
A request is not necessarily a transaction.
An agent may make several calls to retrieve the price, check a position, analyze data, or prepare an action.
The published data also shows that early usage is largely focused on market information, positions, and account data.
The 90,000 requests figure should therefore be understood as an indicator of infrastructure activity.
Not as 90,000 trades.
That distinction matters.
The Beginning of a New Economy
The potential also goes beyond trading.
Binance presents Agent OS as infrastructure that can connect agents to market data, trading, wallets, payments, and on-chain interactions.
Over time, we could see an agent capable of:
• Monitoring multiple markets
• Automatically analyzing a portfolio
• Rebalancing a portfolio based on predefined rules
• Tracking on-chain data
• Interacting with DeFi applications
• Making certain payments
• Communicating with other agents
This is where the concept of an agentic economy becomes interesting.
Software would no longer simply work for humans.
It could also interact with other software and agents.
What About Francophone Africa?
This is probably one of the most interesting angles for our ecosystem.
Africa has a young population that is increasingly familiar with mobile technology and digital financial services.
Yet access to financial tools remains fragmented across several markets.
AI agents could reduce some of these barriers.
For example, a user could interact with a financial service using natural language instead of navigating through several complex interfaces.
But this will require three things.
Security.
Education.
Regulation.
Giving AI more autonomy without explaining its limitations would be the wrong approach.
The Real Test Starts Now
90,000 requests in a single day is an interesting number.
But the real indicator will be Agent OS's ability to turn this initial activity into sustainable usage.
The next questions are much more important:
Will users continue using their agents after the novelty wears off?
Will developers build genuinely useful applications?
Will agents be reliable enough to handle financial operations?
How will regulators address decisions made by autonomous systems?
And most importantly:
Who is responsible when an agent makes a bad decision?
This is where the conversation around AI and crypto becomes much more serious.
We are moving from AI that advises us to AI that can act.
The next battle will therefore not only be about model intelligence.
It will be about access, permissions, security, and accountability.
Binance Agent OS is still young. But the early numbers already show one thing: AI agents are beginning to move out of the laboratory and into real financial infrastructure.
And this transition deserves close attention.

GED

TRỰC TIẾP

Binance Afrique

[Phát lại] 🎙️ Phiên Binance Đã Giải Mã: Làm gì khi tiền mã hóa đang giảm?

28 phút 23 giây · 2k người nghe

GED

AI in Action: How Binance Agent OS Processed 90,000+ Requests in a Single Day

$LAPTOP không khiến ai ngạc nhiên cả đối với những người đã từng theo dõi một đợt ra mắt memecoin trước đây.

Từ lời hứa đến hành động: Binance Agent OS hoạt động như thế nào trong thực tế

Có an toàn khi sử dụng Binance ở Benin vào năm 2026 không?

Tác nhân của chúng tôi, Quy tắc của bạn, Tài chính của bạn: Vì sao Binance đang xây dựng lớp tài chính cho kỷ nguyên tác nhân AI

GED

AI in Action: How Binance Agent OS Processed 90,000+ Requests in a Single Day

$LAPTOP không khiến ai ngạc nhiên cả đối với những người đã từng theo dõi một đợt ra mắt memecoin trước đây.

Từ lời hứa đến hành động: Binance Agent OS hoạt động như thế nào trong thực tế

Có an toàn khi sử dụng Binance ở Benin vào năm 2026 không?

Tác nhân của chúng tôi, Quy tắc của bạn, Tài chính của bạn: Vì sao Binance đang xây dựng lớp tài chính cho kỷ nguyên tác nhân AI

Chủ đề thịnh hành