Core Insights - The emergence of Agents marks a significant shift in the AI landscape, transitioning from large models as mere tools to self-scheduling intelligent entities [1][2] - The Agent sector is rapidly gaining traction, with a consensus forming around its potential, yet many products struggle to deliver real user value, often repackaging old demands with new technologies [2][3] - The true challenges for Agents lie not in model capabilities but in foundational infrastructure, including controllable operating environments, memory systems, context awareness, and tool utilization [2][3] Group 1: Market Dynamics - The Agent market is characterized by a supply overflow and unclear demand, prompting a need to identify genuine problems and opportunities within this space [2][3] - Successful Agents must evolve from initial Copilot functionalities to fully autonomous systems, leveraging user data and experience to transition effectively [9][19] - Coding is viewed as a critical domain for achieving AGI, with the potential to capture a significant portion of the value in the large model industry [11][25] Group 2: Product Development and User Experience - A successful Agent must create a verifiable data environment, allowing for reinforcement learning from clear rewards, particularly in structured fields like coding [26][27] - The design of AI Native products should consider both human and AI needs, ensuring a dual mechanism that serves both parties effectively [31][32] - User experience metrics, such as task completion rates and user retention, are essential for evaluating an Agent's effectiveness and potential [30][31] Group 3: Business Models and Commercialization - The trend is shifting from cost-based pricing to value-based pricing models, with various innovative approaches emerging, such as charging per action or workflow [36][41] - Future commercial models may include paying for the Agent itself, akin to employment contracts, which could redefine the relationship between users and AI [42][43] - The integration of smart contracts in the Agent ecosystem presents a unique opportunity for establishing economic incentives based on task completion [42][43] Group 4: Future of Human-Agent Collaboration - The concepts of "Human in the loop" and "Human on the loop" highlight the evolving nature of human-AI collaboration, with a focus on asynchronous interactions [43][44] - As Agents become more capable, the nature of human oversight will shift, allowing for higher automation in repetitive tasks while maintaining human intervention for critical decisions [44][45] - The exploration of new interaction methods between humans and Agents is seen as a significant opportunity for future development [45][46] Group 5: Infrastructure and Technological Evolution - The foundational infrastructure for Agents includes secure environments, context management, and tool integration, which are crucial for their operational success [56][57] - The demand for Agent infrastructure is expected to grow significantly as the number of Agents in the digital world increases, potentially reshaping cloud computing [61][62] - Key technological advancements anticipated in the next few years include enhanced memory capabilities, multi-modal integration, and improved context awareness [63][64]

Core Insights - The article discusses the significant role of Volcano Engine in promoting the large-scale adoption of AI Agents, emphasizing its innovative pricing strategies and technological advancements [1][3][4]. Pricing Strategy - Volcano Engine has introduced a tiered pricing model for its new Doubao 1.6 model, which reduces costs significantly for enterprises, with a 63% decrease in expenses compared to previous models [6][7]. - The pricing for the 0-32K input range of Doubao 1.6 is set at 0.8 yuan per million tokens for input and 8 yuan for output, making it one-third the cost of its predecessor [6][7]. Technological Advancements - Doubao 1.6 supports multi-modal capabilities and is designed to enhance operational efficiency, allowing for tasks such as hotel bookings and data organization from receipts [9][10]. - The newly launched Seedance 1.0 pro model can generate high-quality videos at a low cost, with each 5-second 1080P video costing only 3.67 yuan [11][12]. Market Impact - Doubao models are currently utilized by 9 out of the top 10 global smartphone manufacturers, 80% of mainstream automotive brands, and over 70% of systemically important banks [14]. - The daily token usage for Doubao models has surged to over 16.4 trillion, reflecting a 137-fold increase since its initial launch [13]. Future Outlook - Volcano Engine aims to maintain a rapid development pace, with plans to release at least one major version of its models annually, driven by clear and substantial market demand [14][15].

Core Viewpoint - The event highlighted ByteDance's commitment to AI development, particularly through its product "Doubao," which has shown significant advancements in various AI capabilities and aims to establish a strong presence in the AI cloud market [4][5][30]. Group 1: Event Highlights - The product launch event for "Doubao" attracted significant media attention, indicating its importance in the industry [2][4]. - ByteDance's CEO Liang Rubo publicly supported "Doubao," emphasizing the company's long-term investment in AI and its strategic importance for the company's growth [7][29]. - The event showcased "Doubao 1.6-thinking," which excelled in complex reasoning and multi-turn dialogue tests, positioning it among the top global models [5][34]. Group 2: Financial Performance - ByteDance's revenue from its cloud services has shown impressive growth, with projections of nearly 50 billion yuan in 2023 and over 110 billion yuan in 2024, reflecting a doubling trend year-on-year [12][15]. - The company aims to achieve over 230 billion yuan in revenue by 2025, potentially surpassing competitors like Baidu [15]. Group 3: Market Position and Strategy - ByteDance's "Doubao" model has captured a significant market share, with a reported 46.4% in the Chinese public cloud model market, outperforming its closest competitors [34]. - The company is focusing on self-research and development rather than external investments, aiming to build a comprehensive ecosystem that includes servers, operating systems, and SaaS [37][41]. Group 4: Technological Advancements - The introduction of "Doubao 1.6" is part of a broader strategy to enhance AI capabilities, with a focus on reducing operational costs by 63% for enterprises [22][24]. - ByteDance is positioning itself as a technology company rather than just an entertainment platform, with a goal to lead in AI and cloud services [43][44].

2025 年，是 Agent 按下加速键的一年。 Manus、Devin 等产品的爆火，都在重申一个共识： 大模型将不再只是工具，而是要成为可以自 我调度的智能体 。 Agent 由此成为继大模型之后，全球科技圈最快形成共识的第二个风口。 从巨头的战略重构到创业赛道的快速跟进，Agent 正成为下一个全民下注的方向。但在 C 端产品 密集涌现、开发者为其狂热的同时，真正跑通用户价值闭环的项目却凤毛麟角，越来越多的产品 陷入了「用老需求套新技术」的焦虑。 热浪过后，市场也回归冷静：Agent 究竟是一场范式的重构，还是一次新的包装？所谓「通用」 与「垂直」的路径分野，是否真的带来可持续的市场空间？而「新入口」背后，是交互方式的进 化，还是旧世界的投影？ 顺着这些疑问继续下探，我们会发现，Agent 的真正门槛，或许并不在模型能力，而在其赖以生 存的底层设施。从可控运行环境，到记忆系统、上下文感知、工具调用，每一个基础模块的缺 位，都是 Agent 从演示走向实用的最大阻力。 这些底层工程问题，构成了 Agent 从「潮流玩具」走向「生产力工具」的最大阻碍，也恰恰是当 下最确定、最高价值的创业蓝海。 在这样一个供 ...

Core Viewpoint - The year 2025 is anticipated to be a breakthrough year for Agents, significantly enhancing the capabilities of large models and transforming human-computer interaction across various platforms, particularly in multi-task automation [1]. Group 1: Agent Development and Platforms - The emergence of the first general-purpose Agent product, Manus, has garnered unprecedented attention, with major internet companies and startups focusing on Agents as a key area of AI competition [2]. - At the recent Force 2025 conference, Agents were highlighted alongside the latest version of the Doubao large model series [3]. - The conference's main forum showcased a new paradigm for AI cloud-native Agent development, emphasizing how Agents can reshape productivity [4]. - The Doubao platform has evolved into a "full lifecycle platform," addressing diverse development and tuning needs for Agents in the era of large models [5]. Group 2: Doubao Platform Features - The Doubao development platform enables low-code Agent development, allowing users with no coding experience to quickly build and deploy Agents across various channels [8]. - The platform empowers Agent development through four main aspects: intelligent IDE, application IDE, a rich set of plugins and workflow templates, and enterprise-level security capabilities [9]. - The application IDE, set to launch in 2024, will allow developers to create GUI-based applications using drag-and-drop features [10]. - Pre-configured Agent templates facilitate rapid deployment of functional Agents, such as smart customer service assistants and educational assistants [12]. Group 3: Eino Framework - Eino, a Go language-based LLM application development framework, draws inspiration from open-source communities and emphasizes simplicity, scalability, reliability, and effectiveness [13]. - Eino standardizes core modules for Agent development, enabling seamless integration with both open-source and closed-source models [14]. - The framework supports flexible orchestration capabilities for complex task decomposition and multi-tool collaboration [15]. - Over 300 systems have been developed internally at ByteDance using Eino, with a GitHub star count of 4.3k, indicating growing interest among developers [16]. Group 4: Agent Lifecycle Management - The Doubao platform establishes a comprehensive Agent lifecycle system encompassing development, evaluation, online observation, and optimization [16]. - The evaluation phase includes quantifying Agent performance to ensure it meets standards, while the observation phase involves real-time data collection and analysis [19]. - Developers can analyze user queries and behavior to adjust Agent performance, identifying and addressing issues through a robust observation system [20]. - The platform supports flexible evaluation set management, allowing developers to create and manage evaluation sets easily [22]. Group 5: Doubao Space - Doubao Space, launched in April, serves as a collaborative platform for high-quality Agents, facilitating efficient task resolution through expert collaboration [25]. - Users can leverage Doubao Space for market analysis, academic guidance, and expert support, with capabilities continuously expanded through the MCP protocol [26]. - The Doubao platform is expected to become foundational infrastructure for Agent development in the era of large models [27].

作者：吴炳见 今年AI应用的投资明显活跃了很多，而套壳这个词，正在从贬义词，成为中性词，甚至褒义词。 主要是市场出现了百亿美金的套壳案例。 什么样的壳有价值？如果把模型能力看成水位线，有的壳是柱子，模型能力涨上来后，柱子就没了。有的壳是船，模型能力提升后，水涨船高。 所以，做船不做柱子。 两个月前，我有个内部分享，这里写一部分出来，讨论下套壳的事。 我们回顾下过去两年多 AI 应用发生过什么，这是 A16Z 发布的AI 应用 Top100 榜单。 | | · D 330 | | | | Gen Al Web Products, by Unique Monthly Vi | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | ChatGPT | 11 | Kimi | 21. | CINITHI | 31 | P. Photoroom | 41 | Monica | | 2 | deepseek | IS | 6 Hailuo Al | 22. | IIElevenLabs | 32. | Moescape Al | ...

Core Viewpoint - Volcano Engine, as a latecomer in the AI and cloud computing sector, is leveraging its rapid iteration of the Doubao model and full-stack AI cloud-native capabilities to accelerate its breakthrough in the market [1][2]. Group 1: Market Position and Competitive Advantage - Volcano Engine's ambition extends beyond just tools; it aims to dominate the AI era's core battlefield, which is the Agent [2]. - The company has achieved a significant market share of 46.4% in the large model service market, far exceeding its competitors [3]. - The scale advantage is highlighted by its internal operations for Douyin and Toutiao, making it one of China's largest cloud service providers, thus reducing costs and offering high-cost performance multi-cloud services [2][3]. Group 2: Technology and Product Development - Volcano Engine emphasizes a "public cloud first" and "AI first" strategy, learning from competitors to avoid pitfalls [4]. - The company is innovating in cost reduction through technology, optimizing existing resources, and enhancing AI service pricing [5]. - It aims to lower the technical barriers for small and medium enterprises by optimizing models and resource scheduling, allowing even small startups to experiment with AI at low costs [6]. Group 3: Client Services and Digital Transformation - Volcano Engine focuses on providing leading products and "accompanying services" to assist B-end clients in their digital transformation [7]. - The company collaborates with clients to co-create solutions, such as hosting AI workshops and exploring AI applications in various industries [7]. Group 4: Ecosystem Development and Future Goals - The company is forming industry alliances and incubating innovative enterprises to promote the growth of AI services in China [8]. - Future goals include deepening collaborations in retail and finance sectors and fostering more AI-first enterprises to build a mutually beneficial ecosystem [8]. Group 5: Industry Trends and Future Outlook - The industry is transitioning from PC and mobile internet to the AI era, with a shift in development paradigms towards intelligent agents [10]. - Volcano Engine is positioned as an "AI cloud," focusing on AI-native technologies and leveraging its internal service experience to assist enterprises in their AI transformation [10]. - The demand for computing power remains strong, with a focus on optimizing model efficiency and enhancing the value of AI rather than merely increasing computing scale [12].

Core Viewpoint - The company believes that scale is crucial for success in the cloud computing industry, and it aims to be a leading player in the AI cloud market, leveraging its technological advantages and market opportunities [4][6][8]. Group 1: Company Performance and Market Position - Volcano Engine has achieved a significant market share, accounting for 46.4% of the domestic cloud model invocation volume, surpassing its closest competitors combined [4][17]. - The daily token processing volume of the Doubao model has increased fourfold to 16.4 trillion since December, indicating rapid growth and adoption in the AI sector [4][26]. - The company set an ambitious revenue target of 100 billion yuan for 2021, which was significantly higher than its competitors at the time, reflecting confidence in its growth potential [5][14]. Group 2: Technological Innovations and Offerings - Volcano Engine has introduced several new services and tools tailored for AI agents, including MCP services, prompt tools, and a reinforcement learning framework, aimed at reducing operational costs and enhancing scalability [5][22]. - The company has innovated its pricing model based on input length, significantly lowering costs to encourage widespread adoption of AI agents [5][23]. - The focus on AI and agent development is seen as a transformative shift in cloud computing, moving from traditional app-based models to more autonomous, self-executing agents [25]. Group 3: Future Outlook and Market Strategy - The company anticipates that the market for AI cloud services will expand by at least 100 times, positioning itself to maintain a leading role in this growing sector [5][14]. - The strategy includes enhancing the capabilities of the Doubao model and ensuring that it meets the evolving needs of clients, particularly in terms of performance and cost-effectiveness [19][28]. - The company emphasizes the importance of vertical optimization and collaboration across departments to ensure that its AI offerings remain competitive and effective [29][30].

Core Viewpoint - The company believes that scale is crucial for success in the cloud computing industry, and it aims to be a leading player in the AI cloud market, leveraging its technological advancements and market positioning to achieve significant growth [2][3][5]. Group 1: Company Performance and Market Position - Fire Mountain Engine has achieved a remarkable market share, accounting for 46.4% of the domestic cloud model invocation volume, surpassing its closest competitors combined [3][29]. - The daily token processing volume of the Doubao model has increased fourfold to 16.4 trillion since December, indicating rapid growth in AI application usage [3][49]. - The company has set an ambitious revenue target of 100 billion yuan for the current year, with a long-term goal of reaching 100 billion yuan in annual revenue, which is 25% of the target achieved so far [21][22]. Group 2: Technological Innovations and Strategies - The company has introduced several new services and tools tailored for AI agents, including MCP services and a prompt tool, aiming to reduce model usage costs significantly [4][45]. - The pricing strategy for AI models has been innovated to be based on input length, which is expected to drive the large-scale application of agents [4][45]. - The company emphasizes the importance of large-scale operations, stating that a larger server base and higher load will necessitate better technology and operational efficiency [4][41]. Group 3: Future Outlook and Market Potential - The company anticipates that the market for AI cloud services will expand by at least 100 times, positioning itself to maintain a leading role in the domestic AI sector [4][20]. - The transition from traditional cloud services to AI-driven solutions is seen as a significant opportunity, with agents expected to surpass the limitations of apps in terms of operational efficiency and economic value creation [48]. - The company is focused on enhancing its capabilities in AI and cloud-native technologies, with a clear objective to be the top player in the AI market [25][20].

Core Viewpoint - The article emphasizes the urgent need for AI-related skills in the job market, highlighting a significant demand for professionals who can work with AI technologies, particularly in large companies, where salaries can reach 700,000 to 1,000,000 CNY annually for those with relevant skills [1][3]. Group 1: AI Talent Demand - The demand for AI-skilled professionals is far greater than the supply, creating a substantial opportunity for those looking to advance their careers or transition into AI-related roles [3][4]. - Companies are particularly interested in candidates who understand AI application development technologies such as RAG, Agent, fine-tuning, and Function Call, which are essential for creating popular applications like intelligent customer service and AI assistants [1][15]. Group 2: Training and Development Opportunities - A practical course titled "Large Model Application Development Practical Training Camp" is being offered to help individuals quickly acquire foundational knowledge in AI model principles, application technologies, and project experience [3][7]. - The course is designed for all technical professionals, regardless of their current role, and aims to facilitate career transitions into high-paying AI positions [4][11]. Group 3: Course Features and Benefits - The course includes insights from industry experts, covering the principles of large models, practical applications, and career development strategies, along with continuous job referral opportunities [9][12]. - Participants will gain hands-on experience through case studies and project simulations, which can be directly added to their resumes, enhancing their employability [12][18]. - The training program has successfully served over 20,000 students, with many achieving high-paying job offers after completion [17].