Driven by the wave of digital intelligence, AI automatic code generation has become one of the most popular topics in the programming field. For zero-basic users, how to quickly understand and practice the tools and processes of AI-generated code is the key to improving learning efficiency, accelerating development entry, and lowering the threshold. In this article, we will use plain language, from the underlying principles to the use of platforms, and then to the practical guidelines, step by step, to take you to master the methods and techniques of automatic code generation with AI.
First, what is AI automatic code generation? Who is suitable for?
AI automatic code generation refers to describing the requirements through natural language, so that intelligent algorithms (such as ChatGPT, Copilot, Baidu Wenxin Yiyin, etc.) automatically output runnable code fragments, functions, and even complete projects. This approach is suitable for:
- White people who have absolutely zero foundation in programming
- Product managers/designers who want to build demos quickly.
- Developers who want to improve efficiency and reduce repetitive labor
AI assistance can also reduce the error rate, improve code specification and efficiency, is the "gas pedal" for novice beginners.
Second, the mainstream types of AI code generation platform and comparison
At present, the mainstream AI code generation platform in the market has the following categories:
| Platform type | Representative products | Advantage | Suitable for the scene |
|---|---|---|---|
| Chat AI conversational | ChatGPT, Wenxin Yiyin | Supports Chinese, flexible answers, can explain the principle | General programming, popular science, Q&A |
| IDE plug-in assisted | GitHub Copilot | Integrated development environment, automatically continue to write, complete the code | Formal development, project collaboration |
| Low code/zero code tools | Flybook/Notion, Tencent Cloud No Code | Drag-and-drop generation, quickly build front-end applications | Page building, data processing, enterprise business |
| Professional API code generation | OpenAI Codex | Multi-language support, API integration and development | Advanced use cases, automated tasks |
Beginners are recommended to start experiencing the dialog AI and platform built-in auto-completion, which has the lowest threshold and the fastest way to get started.
Third, the basic operation process of generating code with AI
After understanding the principles and products, the most important thing is how to really use it. The following mainstream conversational AI and plug-in AI as an example, gradually dismantle the specific operation process.
1. The basic method of using conversational AI (such as ChatGPT)
- Open the official website or app of the AI platform, register and log in the account
- Describe your needs in natural language in the dialog box, for example, "Help me write a Python bubble sort", "Write a JavaScript function to calculate BMI".
- Carefully read the code, text and notes returned by the AI.
- Copy the generated code and paste it into a local editor or online code running environment (e.g. Replit, JSFiddle, Python Tutor) to test the effect.
- Continue to ask AI to help optimize, add comments, convert language or even check bugs.
2. Use AI plugins (e.g. Copilot) to automatically generate code in IDEs.
- Install Copilot plugin in IDEs such as VS Code (requires GitHub account authorization).
- Start a new project or open an existing code file
- Enter a partial comment or description of the requirement, e.g. "// Create a user login form".
- AI will automatically complete or generate code snippets, which can be directly adopted or fine-tuned.
- Supports multi-language and bilingual annotations, suitable for step-by-step learning.
3. Experience AI automation on low-code/no-code platforms
- Sign up for low-code platforms, such as Tencent Cloud No Code, Flybook Smart Forms, etc.
- Select a template, or navigate through "Generate Code" to describe the intent
- Drag-and-drop to generate front-end/process/interface without in-depth code knowledge.
- Real-time preview and release, suitable for rapid prototyping.
Fourth, AI automatic code generation step-by-step text flowchart
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2. Select the appropriate AI platform (such as ChatGPT/Copilot)
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3. describe your goal in detail in natural language
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4. get the code and instructions automatically generated by the AI
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5. run and debug the code in the tool or locally
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6. feedback to AI for continuous improvement if there are new requirements/issues
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7. end up with your own usable and understandable automation code
Five, typical AI automatic code generation scenarios examples
- small website form, e-commerce product list, picture rotating image front-end modules such as one-key generation
- Batch data processing, automatic file reading and writing scripts, simple algorithms.
- WeChat small program, interface service demo building
- Daily office automation, such as batch mail sending, data visualization reports
Six, using AI to generate code common misunderstandings and tips
| Problems/Misconceptions | Suggested Countermeasures |
|---|---|
| Directly copy the AI code all trust without error | Check, run and understand the meaning of the code, and be alert to potential bugs and security risks. |
| English questions are better when asked to AI | Many AIs now support Chinese, the clearer the requirement, the more detailed the sentence, the more accurate the generation. |
| Only write code but not deploy and test | Utilize online IDE or AI to guide you through the compilation and testing process. |
| Use AI to fully automate large projects | AI is suitable for assisting and accelerating development, but the core logic needs to be controlled manually. |
| Forget about saving/version control | Recommended to use Git and other tools to manage their own AI-generated code |
Seven, zero-based users how to continuously improve AI code capabilities
- Check more cases, try to shake different styles of prompt (requirements description method)
- Regularly review the AI code output, gradually understand the principles and try to modify it yourself.
- Take the initiative to learn basic programming logic, the stronger the AI, the more you understand the doorway.
- Pay attention to the platform's new function release and community combat cases, and experience the hottest practice in time.
Practical reference resources
- OpenAI ChatGPT official website
- GitHub Copilot official page
- Tencent Cloud No Code Platform
- Rookie tutorial - online code running
Conclusion
AI automatic code generation, so that "people who do not know how to program" can also be free to try to develop, but also let the people who know how to program like a tiger. As long as you make good use of the tools and methods, you can solve all kinds of computer problems efficiently and automatically from a zero base. In the era of digitalization and AI, everyone can use "language description + AI generation" to start their own creative realization.