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Minara AI launched the next-generation universal financial intelligence agent Minara Harness: supporting 24/7 round-the-clock investment research and automated trading across all asset classes

Minara officially released the next-generation universal financial intelligence tool Minara Harness, which is now available for download by users worldwide. Minara Harness covers multiple asset markets, allowing for investment research 24/7 and operating automated trading within the scope authorized by users. Users can query financial markets using natural language, generate research reports, develop quantitative strategies, and handle daily tasks such as programming, web searching, and document processing. The platform supports users in selecting their own underlying large models.On the investment research side, Minara Harness can simultaneously call multiple professional AI Agents to analyze the same investment opportunity from perspectives such as fundamentals, valuation, market trends, and potential risks. Users can view the information sources and different judgments of each Agent and decide whether to execute trades based on the research results. Minara Harness also supports writing trading strategies in natural language, automatically generating code, and completing backtesting. Users can also subscribe to other traders' strategies, view strategy codes, historical performance, and real-time operating metrics. Minara also offers an optional decision review mechanism, which can verify past judgments against subsequent market results and assess which experiences can be applied to future research. At the same time, Minara announced the benchmark test results of Harness, which outperformed OpenClaw, Hermes, and Claude Code in multiple tests and demonstrated leading performance in tasks such as financial reporting, web research, and spreadsheets.

Tom Lee: Asset tokenization and Agentic AI may trigger a new round of ETH price increase

According to PRNewswire, Tom Lee, Chairman of the Bitcoin treasury company Bitmine, stated that during historical cryptocurrency bull market cycles, the ETH/BTC ratio typically rises as Ethereum's usage increases compared to Bitcoin, such as during the NFT boom of 2020-2021 and the stablecoins of 2025, both of which have been significant catalysts for the growth of Ethereum applications. In the next cycle, Wall Street's tokenization of assets and deployment on the blockchain, along with the use of Agentic AI on the blockchain, may further drive the ETH/BTC ratio higher.Since the third quarter of 2026, ETH has been the best-performing macro asset, outperforming the S&P 500 index by 5430 basis points as of last Friday; the three best-performing asset classes since June 30 have been ETH, BTC, and SOL, with cryptocurrency assets showing significant outperformance compared to other macro assets so far in the third quarter, which is expected to further attract institutions to increase their allocation to cryptocurrency assets.Tom Lee added that as we enter the last few months of 2026, the crypto market faces several positive catalysts, including the anticipated vote on the CLARITY Act in mid-September, South Korean investors re-entering the crypto market and shifting from AI stocks to cryptocurrencies, and what he believes will be a bottoming out of the "four-year cycle" in the coming weeks. These factors may pave the way for a large influx of institutional funds in the last few months of 2026.

X-Agent: The next step for OPC is to enable the Agent to proactively invoke capabilities

X-Agent stated in a recent article that with the help of AI programming tools, "Vibe Coding" is significantly lowering the barriers to software development, allowing a developer to complete work that previously required small product and engineering teams in a short time. However, for a one-person company like OPC, what is truly scarce is not productivity, but demand, trust, and distribution. Being able to quickly create a demo does not mean it will enter the real workflow of users or other Agents.X-Agent indicated that compared to building a complete SaaS from scratch, which includes a website, login, backend, subscription, and customer service system, developers can start with a clear, practical, and callable capability. They can encapsulate data analysis, market research, automated processes, or AI tools as MCP services, enabling Agents to understand what they can do, when to call them, what inputs are needed, and what results will be returned. This is also the focus of the X-Agent AI MCP Hackathon, which is not about competing to build the most complex MCP Server, but rather about helping developers upgrade real and usable APIs, tools, or services into Agent-native services with clear capability boundaries, stable interfaces, verifiable deployments, and ongoing productization potential.X-Agent believes that the most important aspect of the Agent economy is not "service launch," but making services reliable enough to be discovered, trusted, and repeatedly called by other Agents. For OPC, the real advantage is not stacking more features, but capturing market signals faster than large companies and transforming professional capabilities into digital services that can continuously generate value.

first_img Anthropic launches the Claude e-commerce intelligent agent blueprint

Anthropic announced the launch of a blueprint for building e-commerce agents on Claude, providing the framework, patterns, and guardrails needed by engineering teams. It includes reference implementations for shopping agents and merchant agents aimed at retail, travel, telecommunications, and ticketing platforms, as well as the Claude Code plugin. The code can be deployed on Claude API, Amazon Bedrock, Microsoft Foundry, or Google Cloud Vertex AI, and can collaborate with partners such as Accenture, Mastercard, and Visa. The related code has been published in the GitHub repository anthropics/commerce-agents.The company stated that retailers running shopping agents on Claude can increase shopping cart sizes by up to 35%, and the likelihood of shoppers completing purchases improves by 60%. Business clients such as Shopify and Priceline have used Claude to build agents that allow consumers to search, compare, and purchase products using natural language. Shopping agents can interface with catalogs, shopping carts, checkout, preferences, and order history, supporting multi-product planning, personalization, and customer service Q&A, while constraining prices and products with catalog data; merchant agents can answer sales performance, track inventory, suggest pricing and promotions, and draft marketing campaigns, proactively suggesting items to be launched after manual approval.
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