agent

Recently, BNB Chain and the leading AI project in the 0G ecosystem, NeoSoul, announced the latest business data. As of now, the number of Agents on BNB Chain has exceeded 120,000, with over 3.5 million interactions completed; the subscription revenue for the first month of the NeoTrade product has surpassed $300,000.NeoSoul stated that in the future, it will continue to expand its product line around the real economic activities of Agents, enabling Agents to autonomously participate in the market economy and continuously iterate through verifiable results.

B.AI announced that the total number of registered users has reached 2,800,056, surpassing 2.8 million, with the increase from 2.7 million to over 2.8 million taking only a few days.Behind the growth, the platform processes trillions of Tokens daily and automatically matches models with costs through intelligent routing, making top-tier intelligence a scalable infrastructure. B.AI lowers the usage threshold through one-stop model aggregation and frictionless settlement, promoting AI Agents to transition from chatting to paid services, collaboration, and value creation, upgrading to digital citizens with economic sovereignty. The user growth is also seen as a signal for more intelligent agents moving towards autonomous operation, further solidifying the foundation of the AGI economy.

According to Investment World citing Quantum Bit reports, DeepSeek has publicly disclosed the technical details of the system DSec (DeepSeek Elastic Compute) used for training Agents, authored by Liang Wenfeng. This system can generate over 5,000 sandboxes per second, reaching 3 million in a day, with a peak simultaneous operation of 380,000; supporting this scale is a single cluster with approximately 160 nodes, 30,000 CPU cores, and 250TB of memory.DSec prepares four types of backends for four categories of tasks: FnCall, Container, MicroVM, and Full VM, with the training side called through a unified Python SDK libdsec. The scheduling chain includes IAM, API Server, scheduling engine, node Edge, network proxy Aether, and components within the sandbox Chronus. The environment is divided into three layers of read-only images: base image, workspace, and toolkit, which are used in combination at startup. Runtime data from the paper shows that the actual read ratios of Python, Java, and C++ container images are approximately 6.0%, 9.2%, and 8.7%, respectively.Starting from DeepSeek-V4.1, the Agent loop has been moved to the DSec worker container, no longer bound to the GPU Pod lifecycle. The security section disclosed reward hacking during training, including actions such as overwriting system files, swapping file data blocks, scanning networks, and triggering kernel crashes. Defensive measures include AppArmor and eBPF-based network filtering, but reports indicate that these measures do not completely resolve the issues.

SharpLink CEO Joseph Chalom stated that as AI agents integrate with stablecoins, tokenization of real-world assets, and DeFi, the global financial services industry will face a revenue redistribution of over $1 trillion annually by 2030, potentially reaching $4 trillion by 2035.Chalom indicated that AI agents will become the automation layer of the new financial system, capable of continuously managing investors' financial activities, including finding lower banking, trading, and borrowing costs, optimizing savings returns, constructing portfolios, dynamic rebalancing, and managing loans and credit card debt. He anticipates that by 2030, AI agents could save investors about $350 billion annually by reducing fees, with this figure increasing to $1.4 trillion by 2035, equivalent to eliminating nearly a quarter of the costs in the global financial industry.Stablecoins, tokenized real-world assets, and DeFi will provide AI agents with 24/7 programmable financial infrastructure, enabling agents to view asset ownership, prices, collateral requirements, and lending opportunities within the same blockchain environment, and autonomously complete asset transfers, collateralization, lending, and settlement. He also mentioned that financial institutions including Visa, Mastercard, Stripe, PayPal, Circle, Tether, Robinhood, Coinbase, Binance, as well as JPMorgan, Citigroup, and BlackRock are competing for the infrastructure and user entry points of the AI agent financial ecosystem. Whoever controls the infrastructure and agents may capture the value generated when agents trade on behalf of clients.Additionally, Chalom pointed out that the infrastructure such as the x402 machine-to-machine stablecoin payment standard launched by Coinbase and Ethereum's ERC-8004 agent identity protocol is forming a new open agent economy. More than 10,000 AI agents have completed registration within 10 weeks of the ERC-8004 going live.

Bitget has upgraded its AI assistant GetAgent to version 2.0, expanding the scope of AI research from the cryptocurrency market to include U.S. stocks, CFDs, and on-chain data scenarios, forming a cross-market research framework that covers various assets such as cryptocurrency, U.S. stocks, gold, and crude oil. Users can complete market inquiries, opportunity screening, position diagnostics, and trade reviews through natural language, and combine relevant market data, events, and fundamental information to obtain structured analysis that includes key price levels, participation conditions, risk boundaries, and conditions for judgment failure.In terms of functional interaction, this upgrade further enhances GetAgent's continuous research capabilities. Users can set up regular reports, event reminders, and continuously track market changes based on specific conditions, extending AI from one-time Q&A to ongoing market research and dynamic tracking, transforming fragmented market observations into coherent trading plans.As an important part of Bitget's Agent-native strategy, GetAgent 2.0 is evolving from an information inquiry tool to a continuous research assistant. As UEX covers more cryptocurrency assets and traditional financial markets, GetAgent will also serve as the corresponding intelligent research layer, providing users with cross-asset analysis, regular reports, and continuous market tracking capabilities.

According to official social media news, Huobi HTX will hold a themed live broadcast titled "AI Agent Places Orders for You: Do You Dare to Hand Over Your Position?" today at 8 PM. At that time, 0xMoon and Dr. Dinosaur will have a dialogue with Yang Shao and Amber, discussing the application of AI Agent in trading decisions, strategy execution, and position management, exploring key issues such as the reliability of automated trading, account authorization, and fund security.

According to CCTV Finance, the global trade volume of AI-related products will reach 4.18 trillion USD by 2025, a year-on-year increase of 21.9%. With the rapid evolution of artificial intelligence and Agent capabilities, a batch of "portable" AI hardware is accelerating its entry into the consumer market.At the exhibition hall of the Yunqi Conference in Hangzhou, Zhejiang, many AI hardware products, from AI glasses to user-assembled AI DIY devices, no longer solely rely on smartphones. Instead, they synchronize voice, image, and other information around the user in real-time to the Agent, which autonomously breaks down tasks and completes execution. Global investment in AI infrastructure continues to increase, and Chinese technology companies are also making the latest arrangements around AI hardware, large models, and underlying computing power.

The ongoing X-Agent AI MCP Hackathon has received nearly 40 projects, with some public works turning work decisions, capital management, and inter-machine trading into runnable products. X-Agent introduces three cases: BountyProof checks whether tasks are open, claimed, have relevant submissions, and the authenticity of rewards before the Agent accepts GitHub bounty tasks, with the core question being "Is this work worth doing?"Abstain empowers the Agent with the "do not trade" capability, returning execution, abandonment, or no trade based on preset rules before order execution. sumplus helps the Agent choose suitable model service solutions based on task context, output scale, model capability, and invocation costs, making the Agent an autonomous buyer of models, computing power, data, and API services.The three projects correspond to the foundational economic behaviors of the Agent: accepting work, utilizing funds, and purchasing services, pointing to work, capital, and trading primitives. X-Agent believes that a true Agent economy requires a complete cycle of "building, deploying, operating, discovering, invoking, paying, earning revenue, and distributing," positioning itself as the application layer of the Agent economy. This hackathon is still in the review stage, and the mentioned projects are only for public case reference, not representing shortlisted or award results.

Coinbase developer account announced that stocks can now be traded through Coinbase for Agents. This tool previously supported cryptocurrency and derivatives trading, and now adds over 6000 stocks.For analysis or data related to these stocks, x402 payment allows agents to use the USDC balance in their Coinbase accounts to pay for real-time market data fees during task execution, without the need for a subscription service.

Cardano has joined the official x402 software development kit, allowing developers to enable applications or AI agents to use ADA or Cardano network tokens to pay for online services. x402 transforms the basic idle "402 Payment Required" response in web pages into a checkout process built into internet requests: the service provider returns the price and payment instructions, the agent signs the payment, and after transaction verification, the required data or computing power can be obtained.This means that AI agents can purchase individual datasets on demand when preparing reports, without the need for manual account registration, entering credit card information, or subscribing to monthly fees. x402 was created by Coinbase in 2025 and subsequently contributed to an organization under the Linux Foundation, with members including Visa, Mastercard, Stripe, Google, and Amazon Web Services. Solana, XRP Ledger, and several Ethereum-compatible networks have previously supported this standard.Engineers from the Cardano Foundation have built client and server software for payment requests based on the specifications passed in June, as well as a facilitator responsible for verifying and submitting transactions. The first version supports TypeScript, with Python support planned for later release. Facilitator documentation shows that it has completed a real transaction on the Cardano pre-production network, but it has not yet run on the mainnet, nor has it demonstrated scenarios where agents use ADA to pay for commercial services on a large scale.

In an interview with Bitcoin Magazine, Jordi Visser presented the "Ghost Rails" argument, suggesting that the infrastructure built over 15 years in the crypto industry, such as lending, tokenization, and stablecoins, has never had human users but rather AI agents. He compared the current situation to the 14 years between the launch of Netscape and the App Store bringing the internet to the masses, stating that AI agents, rather than retail wallets, represent the turning point of the agency economy, and he believes this is "extremely positive" for Bitcoin.Visser indicated that tokenization will convert $90 trillion in illiquid assets into currency, and Bitcoin is the only asset that can survive for 20 years. In discussions with Grace Remington and Sean Hagan, he covered topics such as nominal growth bets, whether AI can outperform the U.S. debt burden, 24/7 working agent clusters, data centers for debt financing, panic in the bond market, and the "Santa Claus effect," asserting that belief outweighs innovation and expressing optimism about the demand for Bitcoin over the next 30 years.

AI Agent Onchain Operating System (AI Agent Onchain OS) X-Agent has released its latest white paper, which introduces its product architecture, MCP ecosystem, business model, and application scenarios of $XAGT.The white paper points out that the next stage of the AI industry is not just about generating text, images, or code, but about enabling Agents to understand user intentions, invoke tools, execute tasks, and complete transactions. Centered around the concept of "Speak to Build, Share to Connect," X-Agent allows users to create AI Agents with context, memory, skills, API, and wallet connection capabilities through natural language, without the need to write code.In terms of business model, X-Agent aims to establish a complete link for Agent creation, MCP capability access, distribution, payment, and monetization. Developers can package APIs, data, and professional services as MCP capabilities and earn income through per-call, subscription, or transaction commission.The $XAGT token is planned to be used for computing fees in secure operating environments, LLM and API calls, Agent transaction settlements, MCP service payments, Premium Agent template purchases, and developer deployments. In the future, it will also expand to scenarios such as service staking, multi-Agent settlements, and ecological governance.According to the project team, X-Agent currently has over 1 million registered users, has completed more than 1.1 million autonomous tasks, and the consumption of LLM Tokens has exceeded 84 billion. In the future, the project will also promote Super-Agent, enterprise sandbox, decentralized Agent Store, and multi-Agent collaboration systems.Through this white paper, X-Agent hopes to further clarify its long-term direction: to enable anyone to create Agents through language, allowing Agents to truly possess the capabilities for execution, distribution, payment, and continuous commercialization.

Goldman Sachs Research released a viewpoint on September 18, stating that AI is transitioning from the experimental phase to the implementation phase, with the rise of consumer-grade AI agents marking the emergence of the platform layer. At the Communacopia + Technology Conference held in San Francisco, most companies showcased cases from experimentation to implementation. Goldman Sachs expects that by 2027, capital expenditures for U.S. mega-cap companies will reach $1.4 trillion, exceeding Wall Street consensus.Goldman Sachs analyst Eric Sheridan stated that consumer-grade AI agents are shifting from conversational relationships to action-oriented tasks. If consumers overcome trust and security issues, they could execute complex tasks such as purchasing tickets and booking hotels. The monetization of such agents in the mass market will be similar to search, achieved through advertising and subscriptions. AI is evolving from the infrastructure layer to the platform layer and application layer, with declining token unit pricing and increased utility being key drivers of mass adoption.During the conference, concerns about AI risks became a major topic, but Goldman Sachs believes this will not slow down infrastructure construction, as demand for computing power still exceeds supply and most projects have already been contracted. Supply chain constraints such as memory chips, electricity, and land may pose resistance, but the capital expenditure cycle is expected to remain high through 2027.

AI predicts derivatives center Fortune Protocol officially launched the AI Lightning Prediction feature in its Agent section.This update further enriches the dimensions of AI predictions and market data. Each prediction round will display UP/DOWN probabilities, AI confidence levels, market price spreads, key influencing factors, and risk information, helping users to better understand AI's judgment on current market trends.At the same time, Fortune has optimized the bi-weekly profit-sharing and refund mechanism, adding bi-weekly profit estimates, profit reconciliation, and refund details, further enhancing the transparency of profit data and fund processing, making it easier for users to understand the profit and refund situation for each cycle in a timely manner.Fortune stated that it will continue to improve the AI analysis, market data, and profit management system in the future, further enhancing the transparency, efficiency, and user experience of trading prediction derivatives.

The Non-Fungible Token Alliance AMIKO is hosting the Non-Fungible Token × GWDC 2026 Innovation Forum. The forum will be held on September 29, 2026, at AT CENTER in Seoul, South Korea, focusing on core topics such as stock tokenization, Web3, and AI.AMIKO as a co-organizer will express around AI Agent, digital identity, and Web3 social networking. AMIKO is an AI-native infrastructure platform, centered on human-centric AI identity and social networks, allowing users to create AI digital avatars to continuously connect, communicate, and act in the online world. During this conference, AMIKO project guest Haru, who is the co-founder of Ryze Labs, will also give a speech sharing insights on topics related to AI Agent and digital identity.This GWDC event in Korea will gather representatives and institutions such as Sun Yuchen, Microsoft, Bithumb, Animoca Brands, MetaMask, and BNB Chain. AMIKO's presence at this event will help transition the discussion of AI Agents from tools to the industrial context of identity, social, and collaborative relationships.

AI Agent Economic Settlement Agreement AEON announced the integration with two major mobile payment platforms in Pakistan, Easypaisa and JazzCash, allowing users to make payments using cryptocurrency, while merchants complete local fiat settlements in Pakistani Rupees (PKR).Currently, AEON has processed amounts exceeding 500 million and continues to expand its local payment network, providing infrastructure support for AI Agent to autonomously complete payments and settlements in more real-world business scenarios globally.

Arc announced the launch of the AI-driven development tool Arc Studio, which allows users to describe their requirements in natural language. It generates full-stack on-chain applications, contracts, or agents that include front-end interfaces, back-end logic, and smart contracts within minutes. It also supports code review, testing, and export.This tool natively understands the Arc and Circle development stack, including CCTP, Circle Contracts, Gateway, and Wallets. It can integrate protocols such as Aave, Morpho, and Uniswap, and can be tested on nine chains: Arbitrum, Arc, Avalanche, Base, Ethereum, Monad, OP Mainnet, Polygon, and Unichain. Arc Studio can also connect as a sub-agent to Claude Code, Codex, and Cursor. The official reminder states that AI-generated code still requires independent review and testing, and Arc Studio will not deploy, sign, fund, or submit mainnet transactions on behalf of users.

Asus collaborates with Poesis to create autonomous trading agents using NVIDIA (NVDA.O) technology.

During an interview with The Block at the New York Avalanche Summit, Bart Smith, CEO of Avalanche Treasury Co., stated that the view that block space is not infinite will be tested as AI agents enter the financial market. He pointed out that as long as AI agent activities reach the lower end of market expectations, relevant activities will occur on the blockchain, "there is not enough block space, and block space is no longer infinite."Smith believes that the expected demand for block space will make the technical differences between Layer 1 networks like Avalanche, Solana, and Ethereum even more important. He stated that theoretically, there are many subtle differences between these L1s, which users currently do not need to pay much attention to due to sufficient capacity, but "these differences will become important." The former executive, who worked at Susquehanna for nearly 14 years, also believes that Avalanche is best suited for business applications involving privacy and security.Smith expects that by mid-2027, traditional financial markets will shift to trading five days a week, 24 hours a day, and existing financial infrastructure will be unable to cope with round-the-clock trading. He stated that new infrastructure must be created, and it will not be built in the old way, "but rather built on the blockchain."

According to The Defiant, Blockworks announced the launch of the Agentic Detection feature, allowing cryptocurrency exchanges and banks to receive compliance alerts directly from AI agents without waiting for human analysts to review. This feature went live on Thursday in Messari Monitoring, with each alert marked as generated by the agent or verified by an analyst.Blockworks stated that previously, analysts took about 5 minutes to verify each dynamic, while their proprietary model, trained on years of work by Messari analysts, can identify alerts in seconds. Agentic Detection is turned off by default, and clients can enable it view by view. Co-founder Jason Yanowitz mentioned that as on-chain activity scales, the market prices events in seconds rather than minutes, and clients need near real-time alerts.This detection layer is built on seven years of analyst coverage data, and the agent can read X, GitHub, governance forums, Discord, Telegram, project blogs, and over 1,000 news sources, covering more than 1,000 assets. Blockworks acquired Messari for over $10 million on June 12, after Messari completed a Series A extension financing led by ParaFi and Reciprocal Ventures in April, with a valuation of $192 million, with participation from Coinbase Ventures, MoonPay Ventures, and others.