Just now, the world's first IDE integrating a cloud-based Agent team made its debut, enabling "fully automated throughout" project-level development.
Recently, the biggest topic in AI programming has been "deleting the database and running away."
On the 19th of last month, Jason Lemkin, the founder and CEO of SaaStr.AI, revealed that when he was using Replit to write an application and rewrote the core page, he found that the AI had deleted the company's production database.
Original Twitter link: https://x.com/jasonlk/status/1946239068691665187
As an AI development application, Replit "lied" and said that the deleted data could not be recovered. In fact, after the person involved later tried to roll back the operation, the data was unexpectedly recovered. Although the outcome of the incident was satisfactory, it has made people question the reliability of AI programming.
In response, Amjad Masad, the CEO of Replit, urgently responded, admitting that the incident was "completely unacceptable and should never have happened," and announced a series of remedial measures, including an automatic isolation mechanism for database development and production environments, and accelerating the construction of the test environment.
Although there is a direction for improvement and compensation has been offered, the numerous experiences of victims emerging in the comment section tell us that there are still important steps to take before full - process AI code tools can be put into practical use.
However, the advantage of applying large AI models lies in their extremely fast iteration speed. Unexpectedly, within less than two weeks, such a "complete" AI tool has emerged. This Monday, a domestic startup, AiYouthLab, released a demo.
It is a powerful AI programming system called Vinsoo Code, specifically designed for project - level development and the safe parallel operation of multiple agents in the cloud. Currently, it has opened the application for invitation codes, giving priority to inviting domestic users to experience it.
Official website link: www.aiyouthlab.com
This system is designed for the most realistic code development scenarios. As long as you put forward your requirements, multiple agents will automatically divide the work and complete a whole set of development processes, including code generation, testing and debugging, bug fixing, result acceptance, and deployment, and present the results. After that, the project will be jointly debugged across modules in a secure cloud environment, which is not only highly efficient but also avoids problems such as AI - generated code affecting the local environment.
In short, in the past, we had an AI assistant, but now we have an AI professional team to collaborate with you in development. After the communication, you will get a complete project that can be downloaded and run.
Evolution of the Agent Programming Paradigm
From Local Assistants to End - Cloud Collaboration
Nowadays, the application scope of AI programming is becoming wider and wider, and with the progress of technology, some obvious trends have emerged:
On the one hand, there is an evolution from single - agent to multi - agent systems. The orchestration and collaboration among multiple agents have become the key features, enabling tasks to be completed efficiently through task decomposition and parallel collaboration.
On the other hand, agent programming has "moved to the cloud" from the local environment, accessing remote model capabilities, computing resources, and toolchains to quickly build complex agent systems. The cloud environment naturally supports modularization, multi - agent collaboration, and elastic expansion, which is especially suitable for large - scale concurrent tasks. This means that the entire software development lifecycle can be completed by a "virtual team" composed of multiple agents.
For project - level development with a long cycle, high requirements for team collaboration, and clear delivery goals, the cloud - based agent system is undoubtedly a better choice.
Now, Vinsoo Code is gradually turning the future - oriented multi - agent programming blueprint into reality, creating the world's first cloud - based agent programming team.
Multi - Agent System Running in the Cloud
Designed for Project - Level Development
The AI IDE developed by Vinsoo, which integrates a cloud - based agent system, can be said to incorporate the capabilities of product managers, front - end developers, back - end developers, algorithm engineers, AI engineers, test engineers, and operation and maintenance engineers.
Among them, the parallel operation of multiple cloud - based agents and multi - terminal joint debugging have become the core engines for unleashing the power of AI programming. Using this system, developers can assign various parallel tasks to different agents simultaneously, thereby increasing development efficiency by dozens of times.
In terms of the underlying operating logic, this system adopts the working mode of "local IDE + cloud - based agent."
In this mode, developers can first switch to the cloud - based agent interface embedded in the browser with one click in the local IDE, and then synchronize the complete local project to the cloud. The system will automatically create an independent and secure operating environment for each project. Then, developers can assign different tasks to each agent, including the entire development process of code generation, testing and debugging, defect repair, result acceptance, and automatic deployment. The whole process is like a human development team with each member performing their own duties.
During the operation, one friendly aspect for developers is: there is no need to stare at the screen throughout the process. After the system is started, it will automatically conduct saturated debugging and continuous verification until it delivers a truly usable final result for complex projects.
After a series of smooth operations, the development process of human - machine collaboration has been reshaped. Developers no longer need to delve into the implementation details of each line of code, nor do they need to repeatedly check and fix errors in the local debugging environment. All work is automatically executed by the cloud - based agent team through high - level instructions and task distribution.
To adapt to diverse development scenarios, the cloud - based agent system provides two operating modes suitable for different development processes - Vibe Mode and Full Cycle Mode.
Among them, Vibe Mode focuses on "vibe coding," emphasizing efficient response and instant interaction. It continues the lightweight interaction rhythm of agents in the local IDE and is especially suitable for rapid prototyping exploration and experiments driven by inspiration. Developers can quickly complete the feedback loop with the help of agents, improving the efficiency of realizing development inspiration. For medium - and large - scale projects that require team collaboration or formal projects that require standardized delivery, Full Cycle Mode is more appropriate. This mode focuses on more comprehensive project implementation and is suitable for systematic development that requires a complete engineering process and emphasizes code quality and maintainability. The whole process will include: requirement confirmation -> system implementation design -> dynamic task planning -> dependency configuration -> code generation & unit testing / local debug optimization -> overall operation -> overall debug optimization -> completion of project - level code task development -> generation of project description files, ensuring that each step progresses in an orderly manner. Obviously, the Vinsoo Code system is more oriented towards actual production.
Throughout the operation process, the cloud - based agent system has demonstrated systematic capabilities in parallel processing, development security, and underlying capabilities that mainstream AI programming tools do not possess. Next, let's take a look at them one by one.
Trinity of Cloud Collaboration, Joint Debugging, and Perception
In the cloud - based multi - agent collaboration system of Vinsoo Code, multi - terminal joint debugging is indispensable. The two together constitute the core support system for project - level programming development.
Developers should be aware that in real - world programming development, different components or modules, such as the front - end, back - end, database, and interface services, are often deployed on different terminals, which are relatively independent and can run separately. At this time, multi - terminal joint debugging can enable these "distributed members" to communicate and collaborate smoothly.
That is: by starting these modules on multiple terminals, they can send requests to each other, transfer data, and meet each other's needs. And through the log information output by each terminal, agents can conduct collaborative debugging and problem - locating. In this joint - debugging environment, the cloud - based agent development team automatically deploys and runs each module on different terminals and monitors the execution of each piece of code. If an error is found, the corresponding agent will immediately infer based on the bug situation or output results. Of course, agents cannot identify all problems at once. Instead, through continuous multi - round log observation, they gradually narrow down the problem scope and finally find out which logic has a problem.
Through a saturated debugging strategy, agents automatically run through the whole process among different terminals, including code generation, testing, and cross - module debugging (such as front - end and back - end joint debugging), bug fixing, result acceptance, and deployment. There is no need for developers to manually switch terminals, view logs, and conduct manual debugging. It truly realizes "fully automatic completion of a complete project."
Such a multi - agent intelligent system that runs autonomously in the cloud and is continuously optimized allows developers to be more comfortable in more complex project - level development.
Currently, according to our observation, mainstream domestic IDE products generally do not have the ability to execute tasks in a secure cloud environment. Although foreign products such as Cursor and Augment have proposed relevant concepts, their cloud - based agents still lack advanced functions such as the multi - terminal command execution and monitoring capabilities and the natively integrated agent vision system that this product possesses.
Among them, the WebView visual tool developed by Vinsoo enables agents to have visual perception capabilities. They can observe dynamic changes through WebView and even simulate user interactions (such as click operations) to further debug code.
Reconstructing Memory, Planning, and Adaptive Abilities
In addition to using cloud - based multi - agent collaboration to make the whole project run automatically, the construction of other underlying capabilities, such as long - context engineering compression and dynamic task execution planning, provides strong engineering reliability for the whole system to continuously and stably advance projects.
Currently, the "dumbing - down" and unreasonable behaviors of AI also exist in programming. Similar products such as Gemini CLI and Replit have been criticized for this. They not only sometimes have serious hallucinations but also have incidents of accidentally deleting user files and databases.
Long - context engineering compression is precisely to solve such problems. By improving the agent's understanding and memory of the historical context of large - scale projects, it avoids information fragmentation and "dumbing - down" of conversations as much as possible, and can still maintain context coherence in multi - round interactions.
Previously, similar products only supported the design of static task lists and the method of advancing based on generated TRD/PRD documents without a feedback loop. Vinsoo Code has a better solution for this.
Through the execution planning of dynamic tasks, agents have adaptive abilities when facing task changes. They can sense changes in user intentions or project status in real - time and then adjust the execution path to support complex project - level development with frequent changes.
Secure and Isolated Operating Environment
In addition to the all - around enhancement in functions, one of the core values of the cloud - based agent system is to address the potential risks of AI programming getting out of control and effectively defend against high - risk behaviors such as deception, concealment, and deleting the database and running away.
When dealing with complex tasks, the cloud environment provides a pure, controllable, and unified execution space for agents, effectively avoiding common dependency conflicts, permission restrictions, system differences, and security risks in the local environment. In the cloud, agents can start from a standardized image, configure the environment independently, and execute tasks stably, avoiding failures caused by a chaotic local environment.
In addition, the cloud environment has natural advantages in state snapshot, resource expansion, and sandbox isolation. The support of these key capabilities can not only improve the efficiency and reliability of task execution but also greatly enhance the security of code and the traceability of results during the development process.
Among them, specifically targeting the potential risk in the local IDE that a "malicious" or buggy agent may accidentally delete important user files or even access sensitive data, the cloud virtual environment has built "isolated small rooms" (sandboxes) for all agents, preventing them from contacting or accessing other files or system content.
In this way, even if an agent makes a mistake or has abnormal behavior, its impact is strictly limited to the isolated space and will not affect the user's local file system or system resources, greatly reducing the probability of accidental operations and data leakage and improving overall security and controllability.
Enhancing the Local Agent Experience
The front - end development IDE is always the software closest to developers and is their first entry point for interacting with the intelligent system. While focusing on cloud - based multi - agent intelligent collaboration and automated programming, it is still crucial to strengthen the local development experience. For this reason, Vinsoo has launched its self - developed AI IDE to further optimize the "amphibious development paradigm" of end - cloud complementarity. Similarly, the local IDE also provides two modes: Vibe Mode and Full Cycle Mode.
Specifically, this AI IDE is embedded with:
AI Agent system;
A powerful Codebase Indexing system;
Code intelligent completion system.
Based on these systems, the functional system of the localized AI agent integrates multiple key capability modules, including but not limited to: (1) codebase retrieval (2) file context (3) command execution tool (4) network search. These basic capabilities together form the technical foundation for agents to perceive, make decisions, and execute in real - world development scenarios.
Among them, Codebase can complete the indexing of a large - scale project with 200 files within 5 minutes, ensuring that agents have the ability to quickly and accurately locate and understand the project during conversations.
So far, the intelligent programming experience of end - cloud collaboration has been unprecedentedly enhanced.