First distinguish between completion, question and answer, and intelligence
AI programming tools are roughly divided into three levels: when you input, the next piece of code is given, which is completion; when you select the code and ask what it means, it is chat and explanation; when you give a task, it can find files, modify, run commands and test by itself, which is programming intelligence.
The tools all seem to be "writing code", but the actual difference is how far it can see and what steps it can do for you.
If you just want to reduce repetitive code, you don’t need to use the most complicated agent from the beginning; if you want to modify an existing project, you can’t just copy a single function into the chat window. Look at the scope of the task first, then the product name.
Completion while writing: suitable for partial and repeated code
Code completion follows the cursor in the editor. You write a function name, a comment, or the first few lines, and it predicts what will be written next. GitHub Copilot's official description divides this type of capability into gray inline suggestions and "next edit" suggestions.
It is best suited for repetitive and local work: data structure transformations, test skeletons, common interface calls, boilerplate configurations, and small functions in familiar languages. The advantage is that there are fewer interruptions and inappropriate suggestions will not be accepted.
The disadvantage is also very direct: it is easy to continue along the current writing method, including continuing to spread existing errors. Before accepting a large section of completion, check whether input boundaries, error handling, and dependencies really exist, just like you would look at code submitted by a colleague.
Explanation and troubleshooting: first find evidence, then let it change
Chat mode is suitable for explaining unfamiliar code, finding entrances, discussing solutions and narrowing down the scope of errors. You can ask "Which files does this request go through from routing to the database?" or you can give it the error log and related code for analysis.
A truly useful answer should point to specific files, functions and calling relationships, rather than just changing the error report into Chinese. GitHub explains that its warehouse index can find relevant locations based on code meaning; terminal tools can also search for files and read context in the current project.
- Give the complete error message and reproduction steps first, don't just say "it can't run".
- Tell it what was recently changed and what the expected results are.
- It is required to locate the reasons and evidence first, and then propose modifications.
- Have it list assumptions you are not sure about and avoid taking your first guess as the answer.
Change a project: use an agent that can read the repository and run tests
When the task involves multiple files, such as adding a login process, replacing a set of interfaces, fixing tests, and updating documentation, agents are more suitable than simple completion. GitHub Copilot's agent mode will select files, propose editing and terminal commands, and continue to adjust based on the results; tools like Claude Code and Codex can also read, modify, and run checks in the project.
The stronger this ability, the more important the authority boundaries are. Whether the tool can write files, run commands, access the network, and read other directories should be consistent with the task needs. It is easier to review by first using the plan or read-only mode to let it explain what is going to be changed, and then enabling the necessary operations than handing over all permissions at once.
A good task should include goals, unchangeable behaviors, acceptance orders, and scope. For example: "Only modify the checkout page and keep the interface fields unchanged; fix duplicate submissions; add tests; run specified tests and type checks; and finally list modified files."
The real dividing line is whether it can be reviewed and rolled back
AI can write tests for you, and it can also run tests, but "test passed" only means that the conditions written down passed. If it writes implementations and tests at the same time, it may use the same misunderstanding to write both sides consistently.
- Confirm the status of your Git workspace before starting to avoid overwriting uncommitted changes.
- Only hand in one bounded task at a time, and look at the plan and expected modification files first.
- Look at the diff when you're done, not just the final summary.
- Run the project's existing tests, type checks, and format checks, not just newly added tests.
- Perform additional manual review of authentication, payments, deletions, database migrations, and dependency upgrades.
If the project has no version control, no runnable tests, and you can't even tell how to start it, make up these basics first. The more tools can automatically modify, the more they need a way to go back and verify.
Choose the first tool by daily task
- I mainly write familiar code every day. If I want to reduce keyboard input: use the editor to complete it first.
- Frequently read about unfamiliar projects and explain errors: Choose a chat tool that can reference the context of the warehouse.
- Need to complete functions, run commands and tests across files: look at the editor or terminal agent.
- The team's code is in GitHub and has a review process: Evaluate GitHub Copilot's repository along with review capabilities.
- Tools need to work independently on local projects: compare terminal or desktop workflows such as Claude Code and Codex.
There is no need to decide which one to use in the long term. Take a real but low-risk small task and record how much context it misread, which files were changed that shouldn't have been changed, whether the test actually covered the problem, and how long it took you to review it. This result is closer to daily development than the model list.
official information
The tool categories and capability descriptions in this article come from the following official information, and the verification date is August 17, 2026:
