A Beginner’s Guide to AI Programming Tools: From ChatGPT to Code Interpreters

2024 marked an explosive growth of AI programming tools, and this series introduces several typical categories of such tools.

Zero‑Foundation Coding

An example is presented of a doctor who, despite having no programming background, used AI programming tools for ten days of spare time to create a version 1.0 diabetes‑management app, complete with front‑end and back‑end functionality, deployment, and publishing, thereby directly helping patients.

ChatGPT and Intelligent Dialogue Assistants

The most accessible AI programming method is to describe requirements to a conversational assistant such as ChatGPT, which generates code—typically Python—that the user saves as a program file and runs locally.

Limitations of this approach include:

Debugging is difficult because errors must be fed back to ChatGPT for correction, requiring repeated interaction.

The assistant usually produces only code snippets, suitable for simple scripts but not larger programs.

Frequent switching between the web chat interface and a code editor reduces efficiency.

ChatGPT later introduced a Canvas workspace that eases code generation and modification, yet the above limitations persist.

Code Interpreter

The Code Interpreter, a paid feature of ChatGPT also known as “Advanced Data Analysis,” functions as a general code‑generation and execution tool. It can generate code, run it in an isolated Python environment, automatically fix errors based on runtime feedback, and process uploaded files of various types.

ChatGPT provides a separate Python runtime for each conversation, and similar capabilities are offered by competitors such as Claude.

Advantages over the simple ChatGPT dialogue method are:

No need to install a local runtime; the interpreter runs code in the cloud.

Automatic error correction improves code correctness.

Ability to handle uploaded files such as images and data sets.

Remaining limitations include:

The generated code snippets remain relatively simple, unsuitable for larger applications.

Frequent repeated executions still require saving the code locally and running it on a personal machine.

Conclusion

Future articles in this series will explore additional AI programming tools in greater depth, helping readers discover the most convenient AI‑assisted development approaches.