As someone who has never written code before, I "chatted" my way to creating a functional and shareable "mini-program" in just half an hour.

Since the beginning of this year, "Vibe Coding" has undoubtedly been the most talked-about track in the AI field, second only to Agent.

Novices without any programming foundation can use natural language to "command" Cursor to quickly develop a small program. Meanwhile, seasoned programmers with years of experience are also leveraging Vibe Coding tools to significantly boost their efficiency. At the same time, tech giants like Microsoft, Meta, Google, Tencent, and Huawei have been emphasizing in their financial reports and press conferences that AI programming has brought them substantial efficiency improvements—code output has increased by dozens of percentage points, and development manpower has been optimized accordingly.

From Cursor, the leading player in AI programming, to Windsurf, which has recently been vied for by OpenAI and Google, and TRAE, newly launched by ByteDance, AI programming, especially AI development tools centered around integrated development environments (IDEs), has become one of the hottest technological trends in the industry. Recently, Tencent officially announced its entry into the field, launching its first independent AI development platform—CodeBuddy IDE.

CodeBuddy IDE starts internal testing | Source: Tencent Cloud

In fact, Tencent is no newcomer to the field of AI programming. Several years ago, Tencent launched the "Code Assistant CodeBuddy" as an IDE plugin, providing intelligent code completion and multi-file project generation capabilities for developers using traditional IDEs like VSCode and JetBrains.

In May this year, at the Tencent Cloud AI Industry Application Summit, Tencent first revealed the effectiveness of its internal AI programming tools: currently, 85% of Tencent's programmers are using Tencent Cloud Code Assistant CodeBuddy, and the overall coding time has been reduced by approximately 40%. This tool was upgraded in April, introducing the software development agent Craft, which has advanced its capabilities from code completion to a more proactive "intelligent development" stage.

The newly launched independent IDE platform, CodeBuddy IDE, represents a more ambitious evolution. It is not only Tencent's first independent AI programming product but also the industry's first AI development workbench that integrates the entire process from "product design, R & D, to deployment."

Different from chatbots like ChatGPT, AI IDE platforms can not only generate code based on natural language but also undertake complete development tasks. Users only need to express their requirements through dialogue to complete the entire process, including product concept, interaction design, code generation, testing and debugging, and deployment. This truly enables users with no development experience to achieve the "conversation equals development" experience.

It can be said that products like CodeBuddy IDE give complete beginners in programming their first opportunity to truly participate in the creation process of digital products.

01

After two hours of learning, a novice with no programming experience developed

a functional "mini-program"

Vibe Coding has been popular for some time. To be honest, I had only watched some product demonstration videos before and had never actually used it. Moreover, I had never written a single line of code. So, using CodeBuddy IDE this time was my first attempt to "personally" develop an application.

Codebuddy IDE product interface | Source: GeekPark

When opening CodeBuddy IDE, the interface is mainly divided into two areas: the left side is a standard IDE console, supporting the viewing and editing of generated multi-file projects; the right side is a chat area for interacting with an agent. Almost all development-related operations, including generating and modifying product requirement documents, creating and optimizing code, debugging errors, and even deploying the program online, can be completed through natural language instructions.

This chat area can be further divided into three layers: at the top is a row of function buttons, including importing Figma files, configuring the development integration environment, enabling MCP, previewing, and deploying. These are mainly used to help AI better match the work scenario or facilitate subsequent deployment and testing; in the middle is a dialog box for users to input prompts; at the bottom are functions such as model selection, agent switching, and prompt enhancement, which allow users to adjust the response mode and ability boundaries of AI.

It may seem a bit complicated at first glance, but it is actually very easy to use.

Before really starting, you only need to do two things: First, configure the cloud service platform you want to use. Currently, it supports Supabase and Tencent Cloud's own cloud development CloudBase. If you are just developing a local application, you can actually skip this step; Second, select an AI model. The current version is the overseas version, with options such as Claude, GPT, and Gemini. The domestic version will support domestic models such as DeepSeek and Hunyuan in the future.

After the configuration was completed, I decided to start from a real pain point. Since I can't remember so many passwords, I've been wanting to develop a simple and practical password manager with intuitive operations. Although cloud documents can partially achieve similar functions, this was a good opportunity to try to "develop a more decent product."

First, the conclusion: In less than half an hour, I developed a fully functional password management tool. You can set a login password when using it for the first time, and you need to verify it every time you log in. After entering the system, you can view existing password entries by category. Functions such as adding new records, adding custom categories, and modifying the main password are all available. Finally, I deployed it to the cloud server and generated a QR code, so my friends can use it by scanning the code.

The password manager developed by the author using CodeBuddy IDE | Source: GeekPark

As shown above, the page design is also "aesthetically pleasing": the overall style is simple and modern, the category icons are clear and beautiful, the operation entrances are intuitive and easy to use, and the inner page layout is clean and smooth. It doesn't look like a product that a user with zero development experience could "develop" in a short time.

In the past, it might have taken a professional programmer at least a week to design, develop, and launch a small tool with complete functions and a good user experience. But this time, as a "programming novice" with no experience, I completed the entire process in less than half an hour. I only did the following steps:

First, I described my requirements in natural language:

"Develop a password management notebook. It should have a fashionable and grand appearance. There should be a login password every time it is opened. The main interface should include password categories. The default categories are bank cards, video websites, game accounts, and other categories. The main page should also support adding custom categories, adding new records, and modifying the main password. Newly added records should be able to select categories, fill in the platform name, account, and password. The secondary page should display all records under the category and support modification and deletion."

For custom categories, AI created many selectable icons | Source: GeekPark

Then I enabled the built - in Prompt enhancement function of CodeBuddy IDE. As shown below, AI transformed my relatively vague description into a clearer and more structured prompt, which was easier for the large model to understand and execute:

Develop a simple and grand password management tool with the following functions:

1. Security verification:

· Set the main password when using it for the first time

· Verify the main password every time it is launched

· Support modifying the main password within the application

2. Category management:

· Default categories: bank cards, video websites, game accounts, and others

· Support users to add new custom categories

· Each category has a dedicated icon

3. Record management:

· The primary page provides an entry to add records

· Record fields: type (drop - down selection), platform name, account, password

· The secondary page displays all records under the category

· Support modification and deletion of records

4. Interface requirements:

· The overall design is simple and grand

· Category entrances use icons + text

· The record list clearly displays platform/account information

· Passwords are hidden by default and can be clicked to display

5. Data security:

· All password data needs to be encrypted and stored

· The main password uses a high - strength encryption method

Additionally, I noticed that although the Prompt enhancement function is powerful, it is not without errors. For example, I didn't initially have complex requirements for the encryption method, but AI "added" the setting of encryption strength on its own, which resulted in a bug in the generated function. In other words, users still need to conduct a preliminary review of the generated content when using enhanced prompts.

Next, the agent Craft started working. It first transformed the structured prompt into a standard PRD (Product Requirement Document), which only took a few minutes. Then, based on the PRD and the integration configuration I selected (Supabase in this case), the platform automatically generated front - end code such as HTML, CSS, and JavaScript, and built a multi - file project structure.

After the code was generated, I clicked "Preview" to start the debugging phase.

Add record function | Source: GeekPark

The initial version was usable, but it also exposed many problems: for example, the page reported a 404 error when opened for the first time, the initial password couldn't be set during the first login, new categories couldn't be added, and the page layout was messy.

For the problematic parts, I only needed to simply describe the problems and upload screenshots. By just uploading screenshots and explaining the problems in natural language, such as "the category button doesn't respond" or "the main password setting page can't be opened," AI could identify the problems and automatically fix them. For some more complex bugs, log information could be used for further assistance in locating the problems. However, in my experience this time, AI fixed all the problems without me uploading log information.

The entire debugging process took about 10 minutes. After the product's functions and user experience were basically improved, I clicked the "Deploy" button, and AI started to deploy the project to Supabase's CloudStudio. The process automatically completed all the steps, including permission configuration, database creation, and file hosting. Finally, I received a cloud link and a QR code, which I could access myself or share with others.

From the start to the deployment, the total time spent was less than half an hour.

More importantly: I didn't write a single line of code. I didn't even know what files were in the project, but the large model and the agent took care of everything for me.

02

What impact will AI IDEs bring?

Although I developed a functional application in half an hour using CodeBuddy IDE, its value goes far beyond enabling beginners with no programming experience to write programs. While technology inclusiveness is important, the more practical value of this product currently lies in the efficiency improvement it brings to professional developers.

In the process of developing the application from scratch, I was involved in almost the entire software development process, including writing requirement documents, generating code, expanding functions, debugging problems, and deploying the application. All these could be completed through natural language interaction with the agent. This means that for programmers with existing projects, they only need to import their projects into CodeBuddy IDE and connect to existing Figma design drafts and development configurations through interfaces to achieve more efficient development, debugging, and optimization on the platform.

CodeBuddyIDE | Source: Tencent Cloud

Looking further, when the new paradigm of "Vibe Coding" penetrates into the enterprise - level serious development process through AI IDEs, the entire product collaboration system may also undergo a structural transformation.

For example, product managers, test engineers, and even non - technical operation colleagues may be able to directly collaborate with AI through natural language in the future to complete prototype generation, function verification, and even partial iterative development, without relying on programmers for every change. This will greatly reduce the efficiency loss in cross - functional communication and allow professional engineers to focus more on systematic innovation and solving complex problems.

This is not only an improvement in efficiency but also a change in the way of thinking.

Just as Jianying changed the threshold of video creation and promoted the explosion of short - form videos, AI IDEs are reshaping the path and division of labor in software development in a similar way.

What it brings is not just "writing code faster" for programmers but a reconstruction of the entire development method: product managers can quickly generate prototypes, designers can optimize interaction logic through natural language, independent creators have the opportunity to implement complete applications, and even have the ability to create platforms.

From an ecological perspective, this will give rise to a new group of developers. They may not have a traditional technical background, but with the help of AI IDEs, they may be able to create their own applications, tools, and even content services.

Just as the rise of self - media gave birth to KOLs, UP owners, and IP economy, development tools in the AI era may also give rise to a new type of professional role—the "personal digital product creator."

Looking further ahead, when the capabilities of AI agents are further enhanced, we may even need to rethink the necessity of IDE - based development platforms.

Future development may be "IDE - free": users only need to talk to a general - purpose agent, which can automatically understand requirements, break down tasks, call models, allocate resources, and finally generate usable product results.

In this process, we may no longer care whether the code exists, whether the tool is open, or even the logic of the generation tool. We only need to pose questions, and the agent will handle everything in the background and deliver the results to us.

This will be a technological leap from "generating code" to "generating tools" and