What to Do First When Debugging Read Errors, Google, or Ask AI?

Whether you are a novice programmer or have been working for many years, I believe everyone has likely encountered a similar situation. You are coding along just fine, and suddenly the program stops working, the web page goes completely white, or the terminal displays a long screen full of red text. What each person does next might differ. Some people start reading the error carefully. Some immediately copy the message to search on Google. Meanwhile, many people today choose to throw both the error and the code to an AI to help analyze it.

So, which method is the best? The truth is that all three methods are useful, but they should be used at the right time. Starting with the wrong method might cause us to waste time fixing something that isn't the root cause of the problem.

Read the Error First, Because the Answer Might Be Right in Front of You

Error messages are not just there to tell you the program crashed, but they are information that helps pinpoint what type of problem occurred and where it happened.

For example, a JavaScript error will have both the name of the error and an additional descriptive message, while the Stack Trace can display the sequence of function calls, including the relevant files and lines. MDN states that the name and message of an error are the starting point for understanding and fixing the problem that occurred.

Before searching for answers elsewhere, try looking at this basic information first:

What type of error is it?
In which file and on what line did it occur?
Which variable or function is mentioned?
Does the error happen every time, or only in certain situations?
Which part did we modify most recently before the problem occurred?

For Web Developers, you can use the Console and Debugger in Chrome DevTools to inspect log messages, errors, variable values, and pause the code execution at desired locations.

Sometimes, just reading the error completely can reveal that we misspelled a variable name, forgot to import a file, or are calling a value that doesn't have data yet, without needing to open any other websites at all.

Search Google When the Error Relates to Something Unfamiliar

If you read the error and know what happened but still don't know how to fix it, searching for information is still a very useful method. This is especially true for problems related to a Framework, Library, Package, or tool configurations.

Instead of searching with broad terms like

How to fix React not working

Try searching with more specific information, such as

Error message + Framework name + Version in use

Including key phrases from the error will make it easier to find official documentation, a GitHub Issue, or threads from people who have encountered similar problems.

However, you shouldn't copy all the information to search without checking first, because the error or log might contain API Keys, Tokens, Server addresses, Usernames, or internal project data. You should always remove sensitive information first. When finding multiple answers, it is recommended to start with the official documentation of the language, Framework, or Library first, and then look at community answers, as older solutions might not match the version you are currently using.

Even though AI is playing a greater role, developer communities remain an important source of information. The Stack Overflow Developer Survey 2025 indicates that 82% of respondents use Stack Overflow at least a few times a month. Meanwhile, about 35% stated that, at least sometimes, their visits to the site were prompted by issues with AI or AI-powered tools that required additional time to fix, understand, or debug.

Ask AI When You Need Someone to Help Explain the Problem

AI has the advantage that we can send the error along with additional context and ask follow-up questions immediately, such as:

What does this error mean?
Where should I read the Stack Trace from?
Which part of the code might be the root cause?
How can I verify this hypothesis?
Could you explain a solution approach without writing the code for me yet?

GitHub states that Copilot Chat can propose bug-fixing approaches from error messages, syntax, and surrounding code. But the suggestions might be incomplete or not the most optimal method. Users therefore still need to verify and test the results themselves.

Sending questions to AI should include at least the following information:

I am using React version…
I want the code to work like…
When performing this step, I encounter this error…
Here is the relevant part of the code…
Please explain the cause and propose a step-by-step verification method.

The more relevant context you provide, the better chance the AI has to analyze it accurately for your situation. But you should not send confidential source code, passwords, tokens, or customer data without permission.

AI is Popular, But You Still Can't Trust Every Answer

According to the Stack Overflow Developer Survey 2025, 84% of respondents use or plan to use AI in their software development process, and 51% of professional developers use AI tools every day.

But increased usage does not mean everyone trusts AI's answers without question. The same survey found that 46% of developers do not trust the accuracy of AI, while 33% do. Furthermore, 66% feel frustrated with answers that are "almost correct but not entirely right," and 45% believe that debugging AI-generated code might take more time.

Therefore, it is recommended to always verify and test AI-generated code, especially code related to security or critical systems, because the code might look logical but still be incorrect regarding actual requirements.

So, What Should You Start With First?

There is no one-size-fits-all answer for every bug, but a simple sequence you can try using is:

1. Read the Error Completely

Look at the type of error, the message, the file, the line number, and the Stack Trace. Don't just focus solely on the last line yet.

2. Make the Problem Reproducible

Try to figure out what needs to be done for the bug to occur. If you still can't make it reproducible, verifying if a fix actually works will be difficult.

3. Reduce the Scope of the Problem

Observe which parts work normally and which parts start malfunctioning. You might add logs, use breakpoints, or try temporarily disabling some parts of the code.

4. Search Documentation or Google

Once you have the keywords from the error, use them to search along with the name of the language, framework, and version you are using.

5. Use AI to Help Analyze

Send only the necessary context and ask the AI to explain the reasoning, rather than just generating a new block of code to replace the original.

6. Test After Fixing

Verify that the original bug is truly gone and that the fix didn't create new bugs elsewhere. If the project has automated tests, you should run the tests after adjusting the code as well.

In short: read the error to know what happened, use Google to find existing information, and use AI to help explain or connect the context. The three do not need to compete with each other.

No Method is Embarrassing, As Long As You Know Why the Code Was Fixed

Searching Google doesn't mean we are bad at programming. Asking AI doesn't mean we are cheating. And reading errors for a long time doesn't mean we solve problems slowly.

What is more important is that after fixing a bug, we should be able to answer to ourselves:

What caused the problem?
How did the fix change the program's behavior?
Were other parts of the code affected?
How can we prevent the same problem from happening again?

Because making an error disappear might only take a few minutes, but understanding the root cause will help us solve similar problems faster the next time.

Frequently Asked Questions

Should I copy the entire error and ask AI?

You should only send the relevant parts, along with information about the language, framework, version, and desired behavior. Do not send passwords, API keys, tokens, customer data, or confidential source code without permission.

If AI fixes the bug, can I use the code immediately?

You shouldn't. GitHub recommends that users always verify and test AI-generated code because the answer might be incomplete, not match the requirements, or carry security risks.

What should I do if I read the error and don't understand it?

Start by separating the error name, message, file, and the line where the problem occurred. Then, take the keywords to search in the official documentation, or ask AI to explain the error in simple language without having it write a solution right away.

Which is the best method among reading errors, searching Google, and asking AI?

It depends on the problem. However, reading the error first usually gives us enough information to search Google or ask AI more accurately.

Conclusion

When stuck on a bug, we don't need to choose whether to be on Team Read Errors, Team Google, or Team AI because each type of tool serves a different function.

Errors help indicate the starting point. Google and documentation help find existing knowledge. Meanwhile, AI helps explain and propose approaches based on the context we provide. But the person who must make the decisions, verify, and take responsibility for the final code is still the developer.

How about you? When stuck on a bug, what is the first thing you do: read the error, search Google, or ask AI?