Claude for Coding: From a Clear Brief to Tested Changes
Claude can help with every part of coding work, from reading a codebase and writing new code to reviewing tests and fixing bugs. Here is how to choose the right interface, give Claude the context it needs, and verify the result.
Updated 6 min read
Claude can help with coding at every stage: exploring an unfamiliar codebase, writing new functions, reviewing test coverage, and debugging failures. The interface you choose — Claude.ai, Claude Code, or a coding tool that connects to Claude — shapes how you give it context and how you review its output. Tools like fenbs preserve the requirements, implementation decisions, and lessons so each session starts from a clear, shared base rather than repeating what was already established.
This guide covers choosing a Claude coding interface, giving Claude the repository context it needs, and reviewing changes with confidence.
Choosing a Claude coding interface
Claude.ai is the browser interface. Paste code, ask questions and get an answer. Good for standalone functions, code explanations, algorithm questions and short tasks where you will copy the result back yourself.
Claude Code is an agentic terminal tool. It reads your actual files, edits them, runs commands and operates inside your development environment. Good for tasks that involve multiple files, need context from the whole repository, or require running tests and checking the result.
Editor integrations (GitHub Copilot with Claude, Cursor, Windsurf / Devin Desktop) bring Claude into your IDE for inline completions and chat alongside your code. Good for fast completions and context-aware suggestions without leaving the editor.
Choose by the task. A quick question about an algorithm: Claude.ai or chat in an editor. Refactoring a service that spans ten files: Claude Code. The interface shapes the quality of the context Claude gets, which shapes the quality of the answer.
Giving Claude the context it needs
Claude produces better code when it understands the goal, the constraints and the existing patterns in your codebase. A vague prompt ("make this better") produces a generic answer. A specific prompt ("extract the database query in getUserById into a separate repository method, matching the pattern in getProjectById") produces a useful one.
When using Claude.ai, paste the relevant code, the error message, and a sentence about what you are trying to achieve. When using Claude Code, it reads files directly — but it still benefits from a brief description of what it should focus on, especially in a large codebase.
An AGENTS.md or CLAUDE.md file at the root of your repository lets you describe conventions Claude should follow: naming patterns, error handling rules, which test framework to use. Claude Code reads this file at the start of every session.
For managing coding prompts across sessions and sharing them with a team, see Skills and prompts.
Working through a coding task step by step
Long coding tasks work best in steps rather than one large request. Ask Claude to explain its plan before it writes code. Check the plan against your requirements. Then ask it to implement one step at a time.
After each step, review the change. Look for: does this match the intended behavior? Does it follow existing patterns? Are there edge cases that are not handled? Catching a mistake at step two is faster than catching it after step ten.
If Claude takes an approach you did not expect, say so. "I expected you to use the existing UserRepository class rather than creating a new database connection" is a useful correction. Claude adjusts and you learn something about how it interpreted the original request.
Give every Claude session the same clear starting context
Record the requirements, the agreed approach, and the implementation decisions as task notes in fenbs. When a new session opens, a connected Claude reads that record: the goal, the constraints, and what has already been decided. You do not re-explain the setup; Claude starts from the same clear base every time.
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Reviewing changes with tests
Tests are the practical check for Claude's code changes. Before asking Claude to change code, make sure the relevant tests pass. After the change, run the tests again. A passing test suite before and after is the most reliable check that the change did what it was supposed to.
Ask Claude to write tests before it writes the implementation. This reversal forces it to think about the expected behavior before writing code, which tends to produce more focused and testable results.
When a test fails after a change, do not accept "it should be fine." Ask Claude to read the test, explain what it checks, identify the specific line that causes the failure, and propose a fix. Each of those steps is a check against a guess.
For a comparison of how Claude and ChatGPT handle coding tasks, see Claude vs ChatGPT for coding. For coding-specific Claude Code features, see what Claude Code is.
Mistakes to avoid
Do not accept large changes without reviewing them. Claude is confident even when it is wrong. A review that takes three minutes is faster than a debugging session that takes an hour.
Do not give Claude a task that mixes several unrelated concerns. "Add the export button, fix the date formatting bug, and update the API key" is three tasks. Give each task its own session or turn.
Do not assume Claude knows your codebase. Even with repository access, it benefits from specific guidance: "the payment logic is in src/payments/, not in src/checkout/." Specificity is faster than letting it search.
Recording what Claude code teaches you
Coding with Claude surfaces patterns: which kinds of requests it handles well, which assumptions it makes about your stack, which tests it tends to skip. These are worth recording. The next session — yours or a colleague's — benefits from knowing that "Claude assumes pagination is always offset-based, which is wrong for this codebase."
A lesson recorded once is worth ten corrections repeated across sessions. Record it and let the next Claude session read it before it starts similar work.
When a session surfaces a useful finding — a wrong assumption Claude made, a pattern that works, an edge case to always check — record it as a lesson linked to the project in fenbs . The next session reads lessons before similar work. The same mistake stays in the record, not just in your memory.
How to do this with fenbs
- Create a free account and add the project.
- Write a task for each coding task: the goal, the files involved, the approach agreed, and the definition of done.
- Add your coding conventions — naming, error handling, test patterns — as Decisions and rules.
- Connect Claude Code from Integrations. Ask it to read the project context at the start of each session.
- After each session, record what was completed, what was tested, and any lessons that should inform future sessions.
For using Claude with non-coding tasks, see Claude Code for non-coding tasks. For what Claude is in general, see what is Claude AI.