Coding with Claude
Claude is a capable coding assistant across most popular languages and frameworks. It's strongest at generating, explaining, debugging, and reviewing code — but the quality of what you get depends on how much context you give it and how clearly you scope the task.
Writing New Code
When asking Claude to write code, the most common failure mode is underspecifying the context. Claude will write something — but it may not fit your actual codebase, tech stack, or constraints. Give Claude:
- Language and framework: "Write this in TypeScript using Next.js 14 App Router" — not just "write a function."
- Existing code for context: Paste the file or function where the new code will be added. Claude will match your style and conventions.
- What it should do: Inputs, outputs, edge cases to handle, what to return on error.
- Constraints: "No external libraries," "must be compatible with Node 18," "avoid recursion."
For self-contained utilities, Claude can generate working code with minimal context. For anything that integrates with your codebase, more context produces dramatically better results.
Explaining Code
Paste the code and ask Claude to explain it. Specify the level of detail:
- "Explain what this function does in plain English, for a non-developer stakeholder."
- "Walk me through this code line by line — explain why each section exists and what it's doing."
- "What does this regex do and what strings does it match?"
- "Explain the data flow through this component from the initial render through the user clicking the button."
Claude can explain code at multiple levels of abstraction in the same conversation. Start with a high-level overview, then ask for a deep dive on specific sections.
Debugging
For debugging, context is everything. The more of the following you provide, the better:
Provide the full error message
Paste the complete stack trace, not just the first line. The relevant error often appears mid-stack.
Paste the relevant code
Include the function where the error occurs and any relevant callers. "Here's my code" without the code isn't actionable.
Describe what you expected vs what happened
"I expected X to return [Y] but it returned [Z]." This disambiguates whether the bug is in the logic, the data, or your assumptions.
Say what you've already tried
This prevents Claude from repeating suggestions you've already ruled out.
Code Review
Claude is a good first-pass code reviewer. It catches:
- Common security issues (SQL injection, hardcoded credentials, XSS vectors, insecure use of eval)
- Logic errors in clear, bounded functions
- Style and convention deviations (if you specify the standard)
- Missing error handling for obvious failure modes
- Performance antipatterns for common operations
For useful code review output, be specific about what you want reviewed:
- "Review this for security issues only."
- "Review this for correctness — are there any logic errors?"
- "Review this for performance — we process 10M rows per day, so this function runs frequently."
What code review Claude is not reliable for: design-level architectural review (requires full system context), deep business logic review (requires domain knowledge), and reviewing for nuanced correctness in unfamiliar domains (e.g. cryptographic implementations).
Refactoring
Refactoring requests need a clear scope — otherwise Claude may make sweeping changes you didn't want:
- Safe refactoring: "Refactor this function to be more readable — don't change the logic, just improve naming and reduce nesting."
- Aggressive refactoring: "Completely rewrite this class — extract the data fetching logic into a separate module and use async/await instead of callbacks." Only if you intend a significant change.
- Ask for explanation alongside changes: "Show me the refactored version and explain each change you made." This lets you evaluate whether each change is intentional.
Always review and test AI-generated code
Claude generates plausible code, not necessarily correct code. It can produce subtle bugs, miss edge cases, use deprecated APIs, or make incorrect assumptions about your environment. Review every output before running it, and test with your actual data before deploying.
Checklist: Do You Understand This?
- For new code: specify language, framework, existing code for context, and any constraints — underspecification produces generic output
- For explaining code: specify the detail level and target audience explicitly
- For debugging: provide the full error message, relevant code, what you expected vs got, and what you've tried
- Code review works best when scoped to a specific concern (security, logic, performance) rather than "review this"
- For refactoring, state clearly whether you want safe (logic preserved) or aggressive (logic can change) changes
- Always review and test AI-generated code — never deploy without validation