How monday.com transformed its platform into an agent-first product where humans and agents collaboratemonday.com 如何将其平台转型为以智能体为先、人机协作的产品

More than 250,000 companies, from small and midsize businesses to Fortune 500 organizations, use monday.com to manage their work. When the company launched more than a decade ago, its core product was a visual interface that helped teams automate workflows and manage projects. Today, it has rearchitected its product from the ground up around a human-agent collaboration model where AI is woven into work at every level. With Claude at the core, monday’s new platform handles the technical complexity so customers can work at the AI frontier inside workflows they already know.超过 25 万家企业（从中小企业到财富 500 强组织）都在使用 monday.com 管理工作。十多年前公司成立时，其核心产品是一个帮助团队自动化工作流程和管理项目的可视化界面。如今，他们已围绕人机协作模型从底层重新架构了产品，将 AI 融入工作的各个层面。以 Claude 为核心，monday 的新平台处理了技术复杂性，让客户能够在他们熟悉的工作流程中利用 AI 前沿技术。

"The shift to an agent-first product was one of the most significant decisions we've made as a company," said Daniel Lereya, chief product and technology officer at monday.com. "It meant fundamentally reimagining what the platform should do, not just adding AI to existing workflows. Our vision is for monday to be the place where people and AI agents work together seamlessly and Anthropic and Claude have been trusted partners in helping us bring that vision to life."“向以智能体为先的产品转型是我们公司做出的最重大决策之一，”monday.com 首席产品与技术官 Daniel Lereya 表示。“这意味着要从根本上重新构想平台的功能，而不仅仅是在现有工作流程中添加 AI。我们的愿景是让 monday 成为人类与 AI 智能体无缝协作的场所，而 Anthropic 和 Claude 一直是我们实现这一愿景的可靠合作伙伴。”

Hitting the “AI dust” ceiling触及“AI 泡沫”瓶颈

monday’s rebuild unfolded in three phases. In the first phase, as frontier LLM technology matured and customer excitement grew, monday teams worked on embedding AI capabilities into its original platform. The effort culminated in May 2025 with an internal “AI month,” with four weeks dedicated to shipping AI features or products across the company. monday 的重构分三个阶段进行。第一阶段，随着前沿大语言模型技术的成熟和客户热情的增长，monday 团队致力于将 AI 功能嵌入其原有平台。这项工作在 2025 年 5 月达到高潮，当时公司举办了内部“AI 月”，投入四周时间在全公司范围内发布 AI 功能或产品。

Adoption was strong and generated excitement, but soon the team hit a ceiling. “We were building ‘AI dust’, sprinkling automations onto existing workflows without embedding them within or changing the product’s fundamental value proposition,” says Orly Stern Izhaki, VP of Product, AI Works Platform at monday.com. “Our features helped users summarize text and categorize information, but they weren’t creating sustained usage patterns.” 尽管采用率很高并引发了热潮，但团队很快遇到了瓶颈。“我们当时是在制造‘AI 泡沫’，只是把自动化功能零星地撒在现有的工作流程上，并没有将其嵌入或改变产品的核心价值主张，”monday.com AI 工作平台产品副总裁 Orly Stern Izhaki 说。“我们的功能确实帮助用户总结了文本并对信息进行了分类，但并没有创造出持续的使用模式。”

The company needed to shift focus from  adding AI to product features to building it natively into the platform. "Adopting AI features is not the same as becoming an AI company," Izhaki says. "Once we understood that, everything changed."公司需要将重点从“在产品功能中添加 AI”转移到“将 AI 原生构建到平台中”。“采用 AI 功能并不等同于成为一家 AI 公司，”Izhaki 说。“一旦我们意识到这一点，一切都改变了。”

That’s how Izhaki’s team set out to reimagine monday completely: from a work management tool to a place where people and agents get work done together. While the mandate to transform the product came from the top, it was up to each team and each employee to translate that north star into concrete product choices and build their own agents. 这就是 Izhaki 的团队着手彻底重构 monday 的初衷：从一个工作管理工具转变为人类与智能体共同完成工作的平台。虽然转型产品的指令来自高层，但如何将这一北极星指标转化为具体的产品决策并构建各自的智能体，则取决于每个团队和每位员工。

After months of intense work, the company announced the most significant change in its history, rebuilding its entire product experience around humans and agents working together, using already built-in context, workflows, boards, permissions, and governance. Since launching in May 2026, monday’s customers have had more than 5 million interactions with agents on its platform. 经过数月的紧张工作，公司宣布了其历史上最重大的变革，围绕人类与智能体的协作重新构建了整个产品体验，并利用了内置的上下文、工作流程、看板、权限和治理机制。自 2026 年 5 月推出以来，monday 的客户已在其平台上与智能体进行了超过 500 万次交互。

Agents as teammates智能体即队友

Along with access permissions and restrictions, each monday agent is given a name and an avatar, and colleagues can assign agents work through triggers and mentions in the monday platform.  除了访问权限和限制外，每个 monday 智能体都被赋予了名称和头像，同事可以通过 monday 平台中的触发器和提及功能为智能体分配工作。

This design was intentional, addressing a pattern monday noticed across its customer base: many enterprises want to put AI to work, but often stall at an AI chat that runs parallel to where they actually do the work. Embedding agents directly into workflows and enabling people to interact with them like they would with their colleagues turned agentic AI from an abstract concept to a concrete, actionable one.这种设计是有意为之，旨在解决 monday 在其客户群中观察到的一种模式：许多企业希望应用 AI，但往往卡在与实际工作流程平行的 AI 聊天窗口中。将智能体直接嵌入工作流程，并让人们像对待同事一样与它们互动，使智能体 AI 从一个抽象的概念变成了一个具体、可操作的现实。

The jobs monday has mapped for agents range from IT ticket triage and knowledge-base upkeep to candidate sourcing and interview scheduling, competitive-intelligence briefings for sales and marketing, and chief-of-staff work like meeting prep and converting decisions into tracked tasks.monday 为智能体规划的工作范围很广，包括 IT 工单分类、知识库维护、候选人寻访与面试安排、销售和营销的竞争情报简报，以及会议准备和将决策转化为待办任务等幕僚工作。

Agent teams and their jobs for four common workflows.智能体团队及其在四种常见工作流程中的职责。

Four ways to run Claude in monday在 monday 中运行 Claude 的四种方式

Customers use Claude inside the monday platform through four capabilities:客户可以通过以下四种功能在 monday 平台内使用 Claude：

With monday Agents, teams can build custom agents using prompts, and choose Claude as its model. The platform gives the agent a name, a face, and a place on the board where anyone can assign it work.借助 monday Agents，团队可以使用提示词构建自定义智能体，并选择 Claude 作为其模型。平台会为智能体分配名称、头像，并在看板上为其提供位置，任何人都可以为其分配工作。

Bring Your Own Agent (BYOA) makes it possible for Claude Managed Agents to join the platform. Once on the monday platform, an agent one person has built can become a teammate the whole team can mention and assign work to.“自带智能体”(BYOA) 功能使得 Claude 托管智能体能够加入平台。一旦进入 monday 平台，某人构建的智能体就可以成为整个团队的队友，大家都可以提及它并为其分配工作。

Pre-built Agents, available in the monday Agents Store, turn Claude plugins into specialized teammates: a legal team can run a legal plugin as an agent inside its own workflows, and finance teams can do the same with theirs.预构建智能体（可在 monday Agents Store 中获取）将 Claude 插件转化为专业队友：法律团队可以在其工作流程内将法律插件作为智能体运行，财务团队也可以对其财务插件进行同样的操作。

The Claude Coding integration enables teams to connect Claude in the monday dashboard, then plan and assign agents tasks. Claude Managed Agents executes in the customer's own environment, and results and updates land back on the ticket before the task hands off to the next agent or to a human for review. The work runs from business need to working code and back to the business user.Claude Coding 集成使团队能够在 monday 仪表板中连接 Claude，然后规划并分配任务给智能体。Claude 托管智能体在客户自己的环境中执行任务，结果和更新会返回到工单中，然后再移交给下一个智能体或人工审核。工作流从业务需求开始，到生成可用的代码，最后回到业务用户手中。

From brief to landing page without leaving the board无需离开看板即可从简报完成到落地页发布

One end-to-end example: a marketing team runs a campaign production line inside a single board item. The marketer and content lead shape the brief on the item, aligning on goal, audience, key message, and channels. A Strategist Agent built with monday Agents turns that raw input into a structured brief covering the campaign objective, messaging pillars, channel breakdown, and success metrics.一个端到端的例子：营销团队在单个看板条目中运行活动生产线。营销人员和内容主管在条目中制定简报，就目标、受众、关键信息和渠道达成一致。使用 monday Agents 构建的“策略智能体”将原始输入转化为结构化简报，涵盖活动目标、信息支柱、渠道细分和成功指标。

From there, a Landing Page Builder takes over. Running on Claude Managed Agents in the company's own environment, it pulls the approved brief and generates a new variant of an existing landing page, with copy, structure, and messaging adapted to the campaign. The output lands back on the monday item automatically. Before the page reaches approval, a Brand Reviewer, a Claude Managed Agent, checks it against brand guidelines and legal standards and flags anything that needs human attention. The marketing manager then makes one decision: publish or refine.随后，“落地页构建器”接手工作。它在公司自己的环境中运行 Claude 托管智能体，提取已批准的简报并生成现有落地页的新变体，并根据活动调整文案、结构和信息。输出结果会自动返回到 monday 条目中。在页面发布前，“品牌审核员”（一个 Claude 托管智能体）会根据品牌指南和法律标准进行检查，并标记出需要人工关注的内容。最后，营销经理只需做出一个决定：发布还是修改。

A family business at the AI frontierAI 前沿的家族企业

Cooke, a family seafood business founded in 1985 in Blacks Harbour, New Brunswick, has grown from a single farm site with 5,000 salmon into the world's largest family-owned seafood company, operating in 16 countries. Today, Cooke runs project delivery, resource management, and contract management on Claude and monday together. Product managers use Claude to turn approved charters and requirements into initial project plans, generate status reports, and surface risks and issues that feed straight into their monday RAID logs, across roughly 200 active and proposed projects. Claude automates the reporting and data prep that keep lifecycle workflows accurate across 130 contracts—upkeep work that used to be tedious and manual. Cooke 是一家成立于 1985 年、位于新不伦瑞克省 Blacks Harbour 的家族海鲜企业，已从最初拥有 5,000 条鲑鱼的单一养殖场发展成为全球最大的家族式海鲜公司，业务遍及 16 个国家。如今，Cooke 联合使用 Claude 和 monday 来进行项目交付、资源管理和合同管理。项目经理使用 Claude 将批准的章程和需求转化为初步项目计划，生成状态报告，并挖掘直接反馈到其 monday RAID 日志中的风险和问题，涵盖约 200 个活跃和拟议项目。Claude 自动化了报告和数据准备工作，确保了 130 份合同生命周期工作流程的准确性——这些维护工作过去既繁琐又耗时。

“Together, monday and Claude help us read team capacity and make smarter allocation calls,” says Patti Stevens, director of strategy at Cooke. “Monday used to be a platform we had to update. Now we operate from it.”“monday 和 Claude 共同帮助我们了解团队产能并做出更明智的分配决策，”Cooke 战略总监 Patti Stevens 说。“monday 过去是一个我们需要不断更新的平台。现在，我们直接在上面开展业务。”

What monday.com learnedmonday.com 的经验教训

For companies planning a similar rebuild, monday’s team shares five lessons they learned as they transformed their platform into an AI-first product: 对于计划进行类似重构的公司，monday 团队分享了他们在将平台转型为以 AI 为先的产品过程中学到的五点经验：

• The mental model is harder to change than the technology. People naturally want to protect quality and keep improving what already works. Moving teams from "how do we responsibly improve the current product?" to "how do we responsibly rebuild it for a different future?" took longer than the technical work.改变心智模型比改变技术更难。人们天生倾向于保护质量并不断改进现有的工作方式。引导团队从“我们如何负责任地改进当前产品？”转变为“我们如何为不同的未来负责任地重构产品？”所花费的时间比技术工作本身更长。
• Small teams move faster when everything is changing at the same time. Direction, UX, technology, pricing, the trust model, and the company's own definition of good were all in motion at the same time. Layers of stakeholders would lose that much detail, but small teams with clear ownership and fast decision rights stayed close to it.当一切都在同时变化时，小团队行动更快。方向、用户体验、技术、定价、信任模型以及公司对“优秀”的定义都在同时变动。多层级的利益相关者会丢失大量细节，但拥有明确所有权和快速决策权的小团队能始终紧跟变化。
• Adoption depends on trust as much as it does on capability. Product-market fit depends on user confidence and preparedness to let agents into how work actually gets done. Governance, permissions, transparency, and reliability determine whether agents move beyond pilot programs and into production.采用率不仅取决于能力，更取决于信任。产品与市场的契合度取决于用户的信心以及他们是否准备好让智能体介入实际工作。治理、权限、透明度和可靠性决定了智能体能否超越试点项目进入生产环境。
• Capability needs infrastructure to match. Agents perform at a different level when they're grounded in live project data, team history, and structured workflows, and at enterprise scale the backend has to hold. Alongside the agent layer, monday invested in monday DB so the data infrastructure could support the volume, speed, and complexity of agents operating across an organization.能力需要匹配的基础设施。当智能体基于实时项目数据、团队历史和结构化工作流程时，其表现会达到不同水平；而在企业规模下，后端必须能够支撑。在智能体层之外，monday 投资了 monday DB，以确保数据基础设施能够支持智能体在整个组织中运行时的容量、速度和复杂性。
• Build on what already works. monday has always described itself as the place where people team up to drive business outcomes, and the agent-first rebuild extends that promise to a new kind of team member. People still come to monday to achieve their goals, the difference is that some of the team members working alongside them are now agents.基于现有成果构建。monday 一直将自己描述为人们携手合作以推动业务成果的场所，而以智能体为先的重构将这一承诺扩展到了新型团队成员。人们依然来到 monday 实现目标，不同之处在于，现在与他们并肩工作的团队成员中包含智能体。