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How to Review AI Generated Code Before You Deploy

IT Academy Nepal · October 26, 2026 · 4 min read

Review AI generated code is a key habit when you build with tools like Grok. A short check before you move code to a live site helps avoid simple errors and keeps your project steady.

You read the code, test it safely, and ask the AI to explain parts you do not follow. This habit fits well with the build steps shown in our lessons on prompts and first deploys.

Read the Code Line by Line

Start by reading every line the AI wrote. Look at the structure and note any parts that feel unclear or too complex for the task at hand. A clear read often shows small issues before any test run begins.

Compare the code to the brief you gave the AI. Check that the main features match what you asked for and that nothing extra was added without reason. This step keeps the project on track.

Write short notes on any lines that stand out. These notes become your guide for the next checks and help you ask better questions later.

• Open the file in a simple editor you know well.
• Read from top to bottom without skipping sections.
• Mark lines that use new methods you have not seen.
• Check that variable names match your brief.
• Note any comments the AI left in the code.
• Save your notes in a separate plain text file.

Run the Code in a Safe Place First

Move the code to a local folder or a staging server before any live test. This keeps your main site untouched while you watch how the code behaves. A safe run shows real output without risk.

Use the same tools you plan for the final site. Make sure the basic functions load and respond as expected. If something breaks here, fix it now rather than later.

Keep a simple log of what you see on screen. The log helps you compare results after each small change.

1. Create a new empty folder on your computer.
2. Copy the AI code files into that folder only.
3. Open a terminal and run the start command.
4. Watch the first screen that appears.
5. Close the run and note any error lines.
6. Repeat the run once more to confirm the same result.

Test the Unhappy Paths

Try the code with wrong inputs or missing data. These unhappy paths often reveal problems that normal use hides. Testing them early saves time once the code is live.

Think of three simple ways a user might do the wrong thing. Run each case and watch what the code returns. Good code handles these cases with a clear message.

Fix any case that causes a crash or blank screen. Then test the same case again to confirm the fix works.

• Enter an empty field where a name is expected.
• Use a very long string in a short text box.
• Submit the form without filling any fields.
• Click buttons in the wrong order on purpose.
• Close the page while a task is still running.
• Reload the page after an error appears.

Ask the AI to Explain Each Part

Paste small sections of the code back into your chat and ask the AI to explain them in plain words. This step helps you understand what each block does and why it is there.

Focus on any line that still feels unclear after your first read. A short explanation from the AI often clears the doubt and shows if the code is safe to keep.

Write the explanation in your own notes. The notes become a quick reference if you need to change the code later.

1. Copy one function at a time into the chat.
2. Ask the AI to explain it step by step.
3. Read the reply and compare it to the code.
4. Mark any part the AI could not explain clearly.
5. Ask one follow up question on that part only.
6. Add the final explanation to your project notes.

Look for Secrets and Hardcoded Values

Search the code for any keys, passwords, or fixed values that should stay private. These items must stay out of the files you share or deploy. Finding them now prevents later problems.

Replace any found values with placeholders or environment variables. This keeps the code clean and ready for different settings without extra changes.

Run a final search for common secret patterns before you finish. A clean scan gives you more confidence when you move the code forward.

• Search for the word key or secret in all files.
• Look for strings that contain long random text.
• Check any file that ends with config or env.
• Replace found values with YOUR_API_KEY style text.
• Save the cleaned files under a new name.
• Delete the old files that still hold real values.

Run One Final Check Before You Ship

Go through your notes one last time and make sure every item is marked done. This final pass catches anything you may have missed in earlier steps. A short checklist keeps the process steady.

Test the main happy path once more on the staging site. Confirm that the core features work as you first planned. Only then move the files to the live server.

Keep a copy of the reviewed code in a safe place. The copy helps if you need to compare versions after future updates.

1. Open your notes and mark each item complete.
2. Run the main flow on the staging site.
3. Check that no secret values remain in the files.
4. Confirm the unhappy paths now return clean messages.
5. Copy the final files to your live folder.
6. Test the live version once with a fresh browser.

A steady review of AI generated code protects your project and builds your own skill. Follow the same steps each time you receive new code. Over time the checks become quick and natural. Want to practise this step by step? Work through the free IT Academy lessons.