产业AI与数字营销技术专家陆鑫加盟飞书深诺共启Agentic AI营销新篇

龚作仁 2026-09-02 09:12

龚作仁 2026/09/02 09:12

邦小白快读

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本文核心信息为AI领域技术专家陆鑫正式加盟飞书深诺担任CTO，推动飞书深诺AI营销战略升级，落地Agentic AI营销新模式。

1. 核心人物背景：陆鑫是国内少有的多赛道AI商业化落地领导者，曾任职百度、蚂蚁集团，亲历中国数字营销从流量采买到算法驱动的技术演进，兼具AI技术深度和商业洞察能力。

2. 飞书深诺战略变化：飞书深诺从原本提供全球营销服务，升级为构建全球增长的AI营销新基建，适配当前出海企业精细化经营的需求，用AI重构营销全链路。

3. 核心产品介绍：核心产品Marvy 2.0是多智能体协同的营销大脑，不是单点AI工具，可完成全链路营销闭环，帮助企业实现广告增长的确定性。

本文能为出海品牌把握营销行业趋势、布局AI营销提供诸多有价值的参考信息。

1. 行业趋势变化：当前企业出海已经告别粗放流量采购阶段，全面进入精细化经营阶段，生成式AI和智能体技术正在重构营销全链路，整个营销行业发生范式转移，品牌需要适配新的营销生产方式。

2. AI营销产品价值：飞书深诺推出的Marvy 2.0是多智能体协同的AI营销大脑，能完成从目标理解到结果迭代的完整营销闭环，相较于传统单点工具，能为品牌带来更稳定的投放ROI，让广告增长从可能性变为确定性。

3. 可依托的基础设施：飞书深诺拥有17万+出海企业服务经验、1.3PB真实营销数据，还和全球顶尖大模型生态合作，能为出海品牌提供成熟的AI营销基础设施，帮助品牌降低营销运营成本。

本文为出海卖家梳理了AI营销领域的最新变化，能帮助卖家抓住新的增长机会。

1. 行业环境变化：当前出海营销已经告别粗放流量采购的红利期，进入精细化运营阶段，AI技术重构营销全链路，整个行业正在迎来技术升级带来的新增长红利，卖家需要及时跟进AI营销升级趋势。

2. 新的机会提示：飞书深诺打造的Marvy 2.0AI营销产品，依托十余年积累的出海营销经验、真实数据和媒体资源，能实现从市场洞察、媒介策略到智能投放、数据分析的全链路AI自动化执行，解决了卖家投放ROI不稳定的痛点。

3. 行动参考建议：卖家可以尝试接入这类新型全链路AI营销产品，替换传统的单点效率工具，降低营销环节的人力投入，同时借助AI的能力提升投放精准度，获得更稳定的增长效果，抓住AI营销升级的风口。

本文对于布局出海业务的生产工厂，在推进数字化转型、抓住新商业机会方面有不少参考价值。

1. 行业背景启示：当前出海已经进入精细化运营阶段，AI重构了营销全链路，做自有品牌出海的工厂，需要适配新的营销模式，通过AI技术降低营销运营的门槛，聚焦自身核心的产品生产与设计环节。

2. 可对接的商业机会：飞书深诺已经搭建好了面向全球出海企业的AI营销新基建，推出了成熟的Marvy 2.0AI营销产品，工厂不需要自行搭建复杂的营销技术体系，可以直接借助第三方成熟的AI基础设施完成营销环节，降低数字化转型的成本。

3. 反向优化的思路：工厂接入AI营销体系后，可以获得AI沉淀的市场数据和用户反馈，帮助工厂更精准地把握海外市场的用户需求，反向优化自身的产品生产和设计，提升产品的市场适配性。

本文为数字营销相关服务商，展现了AI营销领域的最新发展趋势、客户痛点和可参考的解决方案方向。

1. 行业发展趋势：当前营销行业正在发生AI驱动的范式转移，营销生产方式已经从“人使用工具完成营销”逐步转向“人定义目标，AI组织智能体完成营销”，整个营销行业的基础设施正在经历新一轮重构。

2. 当前客户核心痛点：出海客户已经进入精细化经营阶段，核心需求是获得稳定可预期的投放ROI，传统单点AI工具无法覆盖全链路营销需求，通用大模型的全局平均输出，也达不到出海营销要求面向ROI的局部最优解，无法满足客户需求。

3. 可参考的解决方案：打造垂直AI营销产品需要遵循全媒体、行业Know-how、数据沉淀、AI四力共振的思路，融合通用大模型能力，搭建多智能体协同交叉验证的全链路体系，才能构建技术壁垒，满足客户对增长确定性的需求。

本文对于布局AI营销赛道的平台商，提供了头部玩家的最新做法和行业需求参考，有较高的借鉴价值。

1. 当前行业对平台的核心需求：出海企业已经进入精细化运营阶段，不再满足于单点AI效率工具，需要平台能提供全链路自动化的AI营销基础设施，帮企业实现稳定可预期的增长，解决传统营销模式增长不确定性的问题。

2. 头部平台的最新战略做法：飞书深诺选择了差异化的技术路线：由通用大模型提供通用智能，平台沉淀营销专业智能，全球业务场景提供数据和反馈闭环，三者互相驱动持续进化，同时引入兼具技术深度和商业洞察的核心人才，攻克多智能体落地的工程难题。

3. 平台运营的参考方向：平台需要沉淀自身多年业务积累的行业Know-how和数据资产，深化和全球顶尖大模型生态的合作，同时重视核心AI人才的引入，打造多智能体协同的产品体系，才能形成自身的核心竞争力，满足市场需求。

本文为营销科技领域的研究者，提供了AI营销领域最新的产业动向、创新实践和研究方向。

1. 最新产业动向：营销科技行业已经完成了三次迭代：从计算广告时代的算法驱动，到移动互联网时代的数据驱动，现在进入AI驱动的新一轮基础设施重构阶段，智能体技术正在重构营销全链路，改变整个营销行业的生产方式。

2. 新商业模式探索：飞书深诺已经完成了战略转型，从传统的全球营销服务提供商，转型为全球AI营销新基建的搭建者，通过推出Marvy 2.0多智能体AI营销产品，为出海企业提供全链路AI营销服务，探索出了垂直AI领域新的商业化路径。

3. 核心创新方向：行业内提出了四力共振构建垂类AI产品壁垒的思路，通过多智能体协同交叉验证解决全链路闭环问题，弥补了通用大模型在垂直营销场景的不足，为AI在营销领域的落地提供了新的研究方向。

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Quick Summary

This article covers the key announcement that veteran AI industry technologist Xin Lu has officially joined MeetBot as Chief Technology Officer, to drive the company's AI marketing strategy upgrade and roll out a new Agentic AI-powered marketing model.

1. Background of the key leader: Lu is one of the few leaders in China with proven experience commercializing AI across multiple verticals. With previous stints at Baidu and Ant Group, he has witnessed first-hand the technical evolution of China's digital marketing industry from traffic procurement to algorithm-driven operations, combining deep AI technical expertise with sharp business acumen.

2. MeetBot's strategic shift: MeetBot is evolving from a provider of global marketing services into a builder of AI-powered marketing infrastructure for global growth. The upgrade is tailored to the refined operation needs of China's cross-border enterprises, and will reconstruct the entire marketing workflow with AI.

3. Core product introduction: Its flagship product Marvy 2.0 is a multi-agent collaborative marketing brain, rather than a single-point AI tool. It can run a complete end-to-end marketing closed loop, helping enterprises achieve predictable, reliable advertising growth.

This article offers valuable insights for cross-border brands to track industry trends and map out their AI-powered marketing strategies.

1. Shifting industry landscape: Cross-border expansion has moved beyond the era of rough, volume-focused traffic procurement into a stage of refined operations. Generative AI and agentic technology are reconstructing the entire marketing workflow, driving a paradigm shift across the industry that requires brands to adapt to new marketing production models.

2. Value proposition of AI marketing products: MeetBot's Marvy 2.0 is a multi-agent collaborative AI marketing brain that can run a full marketing closed loop from goal interpretation to performance iteration. Compared with traditional single-point tools, it delivers more stable return on ad spend (ROAS), turning potential growth into predictable, reliable results for brands.

3. Proven infrastructure to leverage: With more than 170,000 cross-border enterprise clients and 1.3 petabytes of real-world marketing data, plus partnerships with the world's leading large language model ecosystems, MeetBot offers mature AI marketing infrastructure that helps brands cut marketing operation costs.

This article outlines the latest developments in AI marketing for cross-border sellers, helping them capture new growth opportunities.

1. Changing industry landscape: Cross-border marketing has exited the era of easy growth from rough traffic procurement, and entered a stage of refined operations. AI technology is reconstructing the entire marketing workflow, unlocking a new wave of growth driven by technological upgrade that sellers need to adapt to quickly.

2. New opportunity highlight: Built on MeetBot's more than a decade of cross-border marketing experience, real-world data and media resources, Marvy 2.0 can automate the entire end-to-end marketing workflow from market insight and media strategy to intelligent placement and data analytics, solving the long-standing pain point of unstable ROAS for sellers.

3. Actionable recommendations: Sellers can test this new type of end-to-end AI marketing product to replace traditional single-point efficiency tools, reduce labor input across marketing operations, and leverage AI capabilities to improve targeting accuracy for more stable growth, positioning themselves to capitalize on the AI marketing upgrade wave.

This article offers useful insights for manufacturing factories pursuing cross-border expansion to advance digital transformation and capture new business opportunities.

1. Industry context takeaway: Cross-border business has entered a stage of refined operations, with AI reconstructing the entire marketing workflow. Factories building their own direct-to-consumer brands need to adapt to the new marketing model, lower marketing operation barriers through AI, and refocus resources on their core strengths: product development and manufacturing.

2. Accessible business opportunity: MeetBot has already built out mature AI marketing infrastructure for global cross-border enterprises and launched the fully developed Marvy 2.0 AI marketing product. Factories do not need to build their own complex in-house martech system; they can leverage mature third-party AI infrastructure to handle all marketing processes, cutting the cost of digital transformation.

3. Reverse optimization opportunity: After connecting to the AI marketing system, factories can access AI-curated market data and user feedback, helping them more accurately capture consumer demand in overseas markets and reverse-optimize their product development and manufacturing to improve product market fit.

This article outlines the latest industry trends, core client pain points and reference solution frameworks for digital marketing service providers in the AI era.

1. Industry development trend: The marketing industry is currently undergoing an AI-driven paradigm shift. Marketing production is gradually shifting from "humans using tools to complete marketing work" to "humans define goals, and AI coordinates agents to execute marketing work", driving a full round of reconstruction of the industry's underlying infrastructure.

2. Core current client pain points: Cross-border clients have entered the stage of refined operations, where their core demand is stable, predictable ROAS. Traditional single-point AI tools cannot cover end-to-end marketing needs, while the generalized average output of general-purpose large models fails to deliver the ROAS-focused local optimization required for cross-border marketing, leaving client demand unmet.

3. Reference solution framework: Building vertical AI marketing products requires a "four-power synergy" framework that combines full media coverage, industry know-how, data accumulation, and AI capability. By integrating general-purpose large model capabilities and building an end-to-end system with multi-agent collaborative cross-validation, companies can build solid technical barriers and meet client demand for predictable growth.

This article offers high-value reference on the latest moves of leading players and core market demand for platforms positioning themselves in the AI marketing track.

1. Core market demand for platforms: Cross-border enterprises have entered the stage of refined operations, and are no longer satisfied with single-point AI efficiency tools. They require platforms to provide end-to-end automated AI marketing infrastructure that helps them achieve stable, predictable growth and solves the problem of uncertain growth under traditional marketing models.

2. Latest strategic moves from a leading player: MeetBot has adopted a differentiated technology route: general-purpose large models provide baseline general intelligence, the platform accumulates professional marketing intelligence, and global business scenarios provide data and feedback loops, with all three driving each other for continuous evolution. The company has also hired core talent with deep technical expertise and business insight to solve the engineering challenges of deploying multi-agent systems at scale.

3. Reference direction for platform operations: To build core competitiveness and meet market demand, platforms need to capitalize on the industry know-how and data assets accumulated from years of operations, deepen partnerships with top global large model ecosystems, prioritize recruiting core AI talent, and build multi-agent collaborative product systems.

This article provides the latest industry developments, innovation practices and research directions for researchers in the martech space.

1. Latest industry trends: The marketing technology industry has gone through three iterations: algorithm-driven in the computational advertising era, data-driven in the mobile internet era, and now it has entered a new AI-driven stage of infrastructure reconstruction. Agentic technology is reconstructing the entire marketing workflow and reshaping the production model of the entire marketing industry.

2. New business model exploration: MeetBot has completed a strategic transformation, shifting from a traditional global marketing service provider to a builder of global AI marketing infrastructure. Through the launch of Marvy 2.0, its multi-agent AI marketing product, the company provides end-to-end AI marketing services for cross-border enterprises, and has explored a new commercialization path for vertical AI.

3. Core innovation direction: The industry has proposed the "four-power synergy" framework to build barriers for vertical AI products. The approach uses multi-agent collaborative cross-validation to solve the end-to-end closed loop problem and弥补通用大模型在垂直营销场景的不足, offering a new research direction for AI deployment in the marketing industry.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

近日，产业AI与数字营销领域技术专家陆鑫正式加入飞书深诺Meetsocial，担任CTO。

陆鑫拥有在计算广告、产业AI及营销科技等多领域多年的技术实践经验，将负责进一步推进飞书深诺AI技术体系建设、Marvy 2.0产品演进及全球营销场景的AI技术落地。

此次陆鑫的加入，是飞书深诺持续推进AI战略升级的重要人才规划和技术布局，也是公司以AI为核心驱动引擎、以技术和数据为基础设施的全球AI营销新基建的重要发展标志。

从“提供全球营销服务”到“构建全球增长的AI营销新基建”

过去十余年，飞书深诺持续服务中国企业全球化增长，积累了覆盖全球市场、媒体生态、行业场景和营销链路的深厚Know-how。如今企业出海已经告别粗放流量采购，进入精细化经营阶段。且随着生成式AI和智能体技术快速进入产业，营销行业正在发生新的范式变化———AI技术正在重构营销全链路。

飞书深诺也正在由此开启全新战略升级：以AI重构营销生产方式，以数据沉淀企业智能，以全球化场景推动AI规模化商业落地。

目前，公司已围绕Marvy Agentic AI持续构建AI营销产品体系，并通过与全球顶尖通用AI大模型及技术生态合作，将前沿模型能力与飞书深诺长期积累的全球营销Know-how、数据资产和业务场景深度融合，构建面向全球企业增长的AI营销新基建。

陆鑫：从Martech技术底层规则搭建者到AI时代智能体产品定义者

陆鑫的加入，与飞书深诺的AI战略高度契合。

陆鑫的技术生涯始于百度广告体系，曾参与凤巢、网盟等核心广告系统的底层架构建设，长期深耕搜索广告、精准匹配、程序化广告、用户定向等计算广告技术。从“出价×质量度”的广告排序机制，到RTB实时竞价和受众定向，陆鑫亲历了中国数字营销从流量采买走向算法驱动的技术演进，是中国首批将计算广告底层算法带入营销科技领域的技术开拓者。

此后，他进一步进入金融、本地生活等产业AI领域，参与蚂蚁集团蚂小财、支小助等AI产品及相关技术实践。横跨搜索、本地生活、金融、营销四大产业场景，多次完整经历AI从实验室到规模化商业落地验证过程，是国内罕见的多赛道AI商业化落地领导者。

陆鑫的技术经历从计算广告，到产业AI，再到AI智能体时代，整体其技术路径贯穿了过去十余年营销科技与AI最重要的几次技术跃迁。他既理解AI底层技术，也理解复杂商业场景；既能够搭建技术系统，也能够推动AI成为真正的生产力。

飞书深诺创始人兼CEO沈晨岗表示：" 飞书深诺的AI战略升级，亟需陆鑫这样兼具技术深度与商业洞察的复合型领导者。他拥有企业级多智能体架构的扎实实战功底，能攻克执行校验、上下文管理等核心工程难题，让多智能体系统在复杂业务场景中稳定跑通、持续迭代，实现端到端自动化交付；同时深谙计算广告与出海营销底层逻辑，对海外媒体生态、投放ROI及实验评估体系有深刻理解。更关键的是，他始终以业务结果为锚，兼顾长期技术愿景与商业化落地，坚持为客户创造可验证的实际价值。"

持续深化Marvy 2.0技术演进，进一步夯实智能体营销增长的确定性

加入飞书深诺后，陆鑫将进一步推动Marvy 2.0的技术演进与产业落地。

陆鑫表示，自己更追求技术对商业系统的全局改造，而非仅实现单点效率提升。通用大模型追求全局平均输出，但出海营销需要面向ROI的局部最优解。一套可用的营销智能体，必须完成目标理解、可信数据获取、专业工具调用、受控业务执行、结果迭代的完整闭环。

叠加只是及格，相乘才是壁垒。全媒体、行业Know-how、数据沉淀、AI四力共振，决定垂类AI产品的最终价值。

Marvy 2.0依托17万 + 出海企业服务经验、1.3PB真实营销数据、数百位专家经验与300+ 专业Skills打造，由Supervisor Agent统筹市场洞察、媒介策略、智能创意、智能投放、数据分析五大Agent，实现多智能体协同与交叉验证。它不是又一款AI单点工具，而是一个会思考、会协同、会进化的营销大脑，让广告增长从 "可能性" 走向 "确定性"。

这改变的不只是效率，而是营销的生产方式—— 从 "人使用工具完成营销"，转向 "人定义目标，AI组织智能体完成营销"。

飞书深诺长期积累的全球市场数据、媒体资源、行业Know-how与客户场景，构成了Marvy持续迭代的企业上下文。

由此，飞书深诺形成了一条专属技术路线：模型提供通用智能，Marvy提供营销智能，全球业务场景提供数据与反馈闭环，三者相互驱动，持续进化。