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Manus and Lin Junyang, Collective Return

Aug 12, 14:38
Manus and Lin Junyang, Collective Return
Original Title: "Manus and Lin Junyang, Both Make a Comeback"
Original Author: Joanne, Tencent Technology


On August 12, two star projects and figures that were once in the spotlight in the AI community announced their comebacks.


On August 11, local time in the United States, the AI startup Manus issued a notification to its users stating that the company will "soon resume operation as an independent company." As part of its separation from Meta, data generated by some users on or after December 29, 2025, will be deleted as required by regulations.


According to the company's notification, affected users need to complete a data backup by 7:59 AM Singapore time on August 23. During August 23 to August 24, the relevant data will be deleted, and affected accounts will temporarily lose access. Starting from 8:00 AM on August 25 Singapore time, users can restore the previously backed-up data and resume using the service.


Manus stated that this adjustment was not due to a data breach or security incident but was a measure taken to meet specific jurisdictional regulatory requirements during the company's transition back to independent operation. Unaffected users do not need to take any action and can continue to use the service normally.


A few hours later, another significant comeback announcement came from Lin Junyang. The former Alibaba Qwen Project Technical Lead announced the establishment of the AI laboratory Pragmatik(p7k) Labs in Shanghai, focusing on the research of the next-generation intelligent agents in the digital and physical worlds.


Both are projects involving intelligent agents, one concerning a company's return and the other a tech lead's new venture. However, they both signify the same shift: the AI competition is now extending from the capabilities of the models themselves to how the models interact with tools, adapt to their environment, and complete real-world tasks.


Meta Acquisition Transaction Enters Unwinding Phase


The deal between Manus and Meta began on December 29, 2025.


On that day, Meta announced its plan to acquire Manus. Founded in 2022, the company initially grew in China before moving to Singapore, focusing on developing AI intelligent agent products.


While the transaction amount was not disclosed by both parties at the time, previous reports indicated that the deal was valued at around $2 billion, with a potential total value of up to $2.5 billion, including employee retention arrangements.


After the acquisition, Meta plans to apply Manus' AI assistant technology to its own consumer and enterprise products to enhance its AI capabilities.


However, this transaction subsequently drew regulatory scrutiny.


On April 28, CCTV News reported that the much-watched Manus acquisition case had come to a conclusion. The Office of the Foreign Investment Security Review Mechanism in China (National Development and Reform Commission) made a decision to prohibit foreign investment in the acquisition of Manus in accordance with the law, requiring the parties to withdraw from the acquisition transaction.


Subsequently, Manus and Meta began to progress with operational separation and ceased data sharing between the two parties.


According to previous information, the operational separation between the two parties was completed in May. Currently, Manus is undertaking the final stages of data processing and preparing for independent operations.


This data adjustment mainly involves data generated on and after December 29, 2025.


Manus stated that the relevant data deletion is to meet regulatory requirements. The company has launched data backup and recovery tools to help affected users preserve task records.


Affected users can back up their data multiple times during the backup window. If new task data is generated after the initial backup, users need to back up again to ensure the latest data is saved.


Manus mentioned that users will not be charged during the backup period. After restoring their accounts, the company will also provide a return reward.


For users who registered using an Apple ID or Facebook account and may not have a corresponding email address with Manus, the company reminds users to pay attention to in-app notifications.


Manus Founding Team and Product Roadmap


The company behind Manus is Butterfly Effect, established in 2022.


Founder Xiao Hong has a background in enterprise software development. Information indicates that he studied software engineering at Huazhong University of Science and Technology. After graduating in 2015, he founded Wuhan Nightingale Technology, with its WeChat tools "Yiban Assistant" and "Weiban Assistant" serving over 2 million business users.


Butterfly Effect later launched Monica, an AI assistant product that integrates various language model capabilities. Manus then further expanded AI capabilities into the task execution field.


Manus is positioned as a general AI agent platform, where users can issue natural language commands to the system to perform tasks such as information retrieval, report writing, document processing, and code development.


Co-founder and Chief Scientist Ji Yichao had previously developed an iPhone browser and founded Peak Labs, focusing on information extraction and search technology. Co-founder Zhang Tao had previously worked on product-related tasks at ByteDance and Lightyear.


On March 6, 2025, Manus was officially publicly released.


Rapid Growth Pre-Acquisition, Future Equity Still Undecided


Prior to being acquired by Meta, Manus had completed multiple funding rounds and experienced rapid growth.


Earlier in 2025, the company raised $75 million from Benchmark, reportedly valuing the company at around $5 billion post-investment.


In December 2025, Manus announced that eight months after product launch, its annualized recurring revenue had exceeded $1 billion, with a total revenue run rate of $1.25 billion.


The company also disclosed that the platform had processed over 147 trillion tokens and created over 80 million virtual computers.


At the time of Meta's acquisition of Manus, both parties aimed to further expand the AI agent business. However, following the completion of the deal, Manus's future equity structure and financing arrangements remain undisclosed.


According to previous reports, during the deal completion process, the founding team had explored raising around $1 billion to repurchase company shares.


Some early investors also participated in related discussions, including firms like ZhenFund and IDG Capital.


Manus stated that upon resuming independent operations, the company will continue to serve global users and plans to introduce new product features. The future focus will be on further enhancing the AI agent's capabilities, but no specific product roadmap has been announced.


Regarding data storage, Manus stated that post-independent operation, user data will continue to be stored in the United States and Singapore.


From Training Models to Building AI Agents, Lin Junyang Embarks on New Exploration


With Manus resuming independent operations, this entrepreneurial company centered around a general AI agent will regain the flexibility to adjust its products and financing arrangements independently. On the same day, Lin Junyang, another key tech leader who had previously spearheaded the development of large models domestically, also shifted his entrepreneurial focus to AI agents.


Junyang Lin announced his departure from Alibaba on March 3, 2026. Prior to this, he was heavily involved in large-scale model development, focusing on inference capabilities, intelligent agent training, and the interaction of models with the environment during the development of the Qwen model series.



Transitioning from inference models to intelligent agent systems signifies a shift in the focus of AI competition. Future technological breakthroughs will stem not only from the models themselves but also from how the models integrate with tools, environments, and real-world tasks.


Junyang Lin's new research direction is centered around intelligent agent systems. The name of Pragmatik Labs is derived from "Pragmatics" in linguistics. Lin explained that his initial interest in linguistics was sparked by a friend's recommendation of pragmatics, leading him to pivot towards computational linguistics and natural language processing. "Pragmatik" represents a return to the roots of where things happen, while also reflecting the team's understanding of pragmatism, emphasizing that AGI ultimately needs to address real-world practical issues.


Pragmatik Labs will focus its research on two directions: digital intelligent agents and physical intelligent agents.



In the digital domain, the company aims to build general-purpose intelligent agents for knowledge work, business operations, and industry processes, enabling AI to tackle more complex tasks. In the physical domain, the company is exploring embodied intelligent systems that can enter real-world environments, adapt to changes, and carry out long-term tasks.


Pragmatik Labs introduces on its official website that the next-generation intelligent agents need to possess the ability to reason, invoke tools, learn from feedback, and coordinate actions. Unlike traditional models that primarily generate information, intelligent agents need to operate continuously in the environment, adjust strategies based on outcomes, and achieve long-term goals.


This direction aligns with Junyang Lin's previous concept of "training models → training intelligent agents." He believes that while inference models address how models conduct more effective internal computations before providing answers, intelligent agent systems focus on how models take action in real-world environments. Future AI systems will need to address issues such as tool selection, task planning, environmental feedback, failure correction, and multi-round task collaboration.


Pragmatik Labs is currently strategically positioning itself around this direction, aiming to expand AI capabilities from digital information processing to real-world tasks.


Original Article Link


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