Use AI coding assistants to explain code and errors, suggest approaches, generate boilerplate and tests, and review your work. Keep control by planning the design yourself, asking for small changes, reading every line before accepting it, running tests, and checking for security issues. Beginners should attempt problems first and ask for hints rather than full solutions.
What AI coding assistants are good at
- Explaining: "What does this function do?" "Why am I getting this error?"
- Boilerplate: repetitive setup code, configuration files, simple components.
- Suggestions: different ways to approach a problem.
- Tests: generating test cases, including edge cases you missed.
- Reviews: spotting bugs, unclear names and potential security issues.
- Learning new tools: "Show me how to make an HTTP request in this framework."
Where they are risky
- Code that looks right but fails on edge cases.
- Outdated or invented library functions.
- Insecure patterns, such as missing input validation or exposed secrets.
- Large changes across many files that are hard to review.
- Over-reliance, which stops beginners from developing problem-solving skills.
A professional workflow
- Plan first. Decide the structure: files, functions, data. AI is much better at filling in a clear plan than inventing one.
- Work in small steps. Ask for one function or one change at a time.
- Give context. Share relevant code, the language and version, and constraints such as "no external libraries".
- Read everything. If you cannot explain a line, ask the AI to explain it, or do not accept it.
- Run and test. Execute the code and run tests after every change.
- Review for security. Check inputs, authentication, secrets and data handling.
- Commit often. Use Git so you can undo bad changes. See Git and GitHub for beginners.
Prompts that work for code
- "Here is my function and the error. Explain the cause before suggesting a fix."
- "Give me a hint for solving this, not the full solution."
- "Review this code for bugs, edge cases and security problems. List issues by severity."
- "Write unit tests for this function, including edge cases."
- "Refactor this for readability without changing behaviour. Explain each change."
Rules for students
- Attempt the problem yourself for at least 15 to 20 minutes before asking for help.
- Ask for hints and explanations, not complete answers.
- Retype rather than paste when learning, so the patterns stick.
- Follow your course's rules on AI use for assessed work.
The skill that matters most
As AI writes more code, the scarce skill becomes judgement: knowing what to build, whether code is correct, secure and maintainable, and how parts fit together. That comes from fundamentals and experience. Our web development course teaches fundamentals first, then this AI-assisted workflow, with a developer reviewing your code. See also vibe coding explained.
Frequently asked questions
Will AI coding assistants make me a worse programmer?
Only if you let them replace your thinking. Used to explain, review and speed up routine work, they can make you better and faster.
Which AI coding assistant is best?
Several strong options exist inside code editors and chat assistants. Choose one that integrates with your editor, and focus on the workflow.
Can I use AI in coding interviews?
Usually not, unless explicitly allowed. Practise solving problems without AI as well.
