Tencent launches AI design agent platform Ardot, enabling editable design drafts to be generated with a single sentence.

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Author | Huang Yu

Tencent is continuously exploring more application scenarios for Agents.

On May 18, Tencent launched another AI design intelligent collaboration platform, Ardot.

It is reported that Ardot is a UI/UX design tool that supports multi-person real-time collaboration, mainly targeting designers and product managers; covering the entire software design process from visual design, code delivery, team collaboration to asset circulation.

Obviously, Tencent is targeting an enterprise-level collaboration scenario characterized by high demand and strong willingness to pay.

With Ardot, users can describe interface requirements in natural language, Ardot generates an editable design draft in real time, which can be converted to code with one click. It also supports direct import of Figma files, completely retaining the original layout, styles, and components. After generation, Ardot also supports precise local modifications of UI.

In the original workflow for internet product design, for product managers, UI/UX designers, and development teams, there exists a lot of repetitive work and collaboration friction. For example: time-consuming prototyping, lengthy design reviews, substandard restoration of designs by developers.

Ardot is precisely targeting these pain points.

According to Wallstreetcn reports, Ardot was developed by Tencent Cloud’s CodeBuddy team.

With the arrival of the Agent era, the CodeBuddy team can be said to be Tencent’s pioneer in Agent products.

Since last year, the CodeBuddy team has successively launched CodeBuddy and WorkBuddy. These two products are currently Tencent’s key Agent offerings.

Reportedly, Ardot is also built upon the underlying architecture of WorkBuddy/CodeBuddy.

Because of this, Ardot has a "code-friendly" gene, providing seamless connection between design and code via MCP (Model Context Protocol).

Developers can extract design context into IDE: variables, components, and layout data are directly pulled into the development environment for reading, creating, and modifying design files, converting drafts and context into code with one click, seamlessly linking with CodeBuddy, and also compatible with WorkBuddy, Cursor, Claude Code, and other Agents supporting MCP.

In this wave of AI Agents dubbed "raising lobsters," Tencent can be said to be the most actively responding enterprise.

Tencent's Chairman and CEO Ma Huateng personally promoted Tencent's "lobster set meal," stating "self-developed lobster, local lobster, cloud-based lobster, enterprise lobster, cloud desktop lobster, security isolation lobster facility, cloud security, knowledge base... and a batch of products are on the way."

Senior Executive Vice President of Tencent and CEO of the Cloud and Smart Industry Group, Tang Daosheng, also stated that the current AI application paradigm is transitioning from "Chatbot" to "AI Agent." In the future, every individual and enterprise will be able to quickly build their own intelligent agent applications using standardized tools, jointly forming a decentralized and highly prosperous Agent ecosystem.

After investing in technology and products over the past few years, AI is no longer just about who has the most powerful model or the hottest entry point. Instead, it must answer a more practical question: when can it bring scalable commercial revenue to enterprises?

Recently, at the earnings conference, Tencent management also disclosed their thoughts on the commercialization of AI products.

Tencent President Liu Chiping stated that the commercial implementation of AI products for individual users is relatively difficult. Meanwhile, unlike traditional Internet products, AI services cannot expand infinitely at ultra-low marginal costs. Each model call and service delivery incurs actual costs.

Therefore, the industry can no longer simply apply the logic of "maximizing scale and DAU" from the Internet era. In Liu Chiping's view, identifying high-value scenarios is at least as important as user scale, if not more crucial, and this has become a new consideration for Tencent in product deployment and model collaborative design.

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