ChatGPT for coding: what it is good at

ChatGPT is good at explaining code and errors, writing small scripts and functions, drafting tests and turning a plain description into a first version. For work across a whole project, OpenAI’s coding agent, Codex, is included in ChatGPT plans. Either way, run and review everything it writes before you rely on it.

What ChatGPT is good at

• Explaining what a piece of code does, line by line, in plain English.
• Reading an error message and suggesting the likely cause.
• Writing short scripts, such as renaming files or cleaning a spreadsheet export.
• Drafting functions, formulas and database queries from a description.
• Writing tests and comments for code you already have.
• Translating code from one language to another.

It works best on focused tasks where you can paste in everything it needs: the code, the error and a sentence about what should happen.

Where Codex comes in

Codex is OpenAI’s coding agent. Rather than answering in a chat, it works on a project: exploring and understanding the code, building features, reviewing changes and fixing issues. OpenAI says Codex is included in every ChatGPT plan, from Free to Enterprise. Its pricing page lists Codex on the web, in a command-line tool, as an editor extension and on iOS from the Plus plan, along with automatic code review and a Slack integration. Limits differ by plan, so check OpenAI’s Codex pricing page for yours.

Where it goes wrong

• It can invent functions, settings or library features that do not exist.
• It does not know your project unless you show it the relevant code.
• It may solve the question you asked rather than the problem you have.
• Code that runs is not the same as code that is secure.

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How to ask for code you can use

1. 1Give contextSay the language, the framework and what the code is for. Paste the relevant files or error in full.
2. 2Describe the resultSay what should happen, with an example input and output if you can.
3. 3Ask for small piecesOne function at a time is easier to check than a whole app.
4. 4Ask it to explainHave it explain its own code. If the explanation does not make sense, the code probably does not either.
5. 5Run and testTry it on real data and an awkward case before it goes anywhere near customers.

Keep private data out of your prompts. Do not paste passwords, API keys or customer records into any AI tool, and use a business plan if your team will share code with it regularly.

Frequently asked questions