How to Read and Verify Code Generated by AI

## How to Read and Verify Code Generated by AI

Briefly: AI code cannot be taken as a ready-made answer. It should be read as someone else’s work, for which you are now responsible. Even if the code works, it doesn't mean anything.

## What situation does it usually start with

Usually everything happens quite casually. You ask the AI to help with the task, it answers, and a neat piece of code appears in front of you. It looks confident, logical, sometimes even starts immediately without errors. At this point, there is a feeling that the stage of “understand” can be skipped and just go on.

This is where mistakes are most often made. Working code is perceived as correct, although in fact it has not yet encountered real conditions. Until you look inside and see what he's doing, you don't know what he's holding on to or where he'll break first.

## Why AI code should not be read line by line

Almost all beginners start the same way. They open the code and try to read it from top to bottom, line by line, like plain text. This is quickly tiring and rarely provides insight, especially if the programming language is unfamiliar.

It’s much better to take a step back and look at the whole code first. Not to understand the details, but to catch the form. Where the work begins, where it ends, where the data comes from, and what should come out of it. If you can’t answer these questions after this look, then the code already needs attention, even if it looks neat.

## Example: First meaning, then details

Let’s say the AI generated this code:

function getTotal(items) {
  let sum = 0;
  for (let i = 0; i < items.length; i++) {
    sum += items[i].price * items[i].count;
  }
  return sum;
}

If you’ve never seen JavaScript, the code may be incomprehensible. Not intimidating and not complicated - exactly incomprehensible. And that's a normal starting point. There is no need to “understand” or guess the meaning by the appearance of brackets. The challenge at this stage is to understand what this code does in general.

In the above example, it is enough to see the basic picture. There's a function, it gets a list, it counts something inside, and at the end it returns one number. This is enough to make sense: the code counts the total amount. Even if you can’t see it right away, it’s not a problem. In such a situation, you do not need to read the lines and try to understand the syntax.

The important thing is that if the meaning is not clear, it can and should be asked by AI. Directly and without circumvention. For example, “Explain what this code does in simple words” or “Describe what’s going on here step by step.” As part of training for people with no experience, this is a normal and expected step, not cheating.

## Where does the real test start

When the general meaning has become clear, then the test begins. It’s helpful to stop looking at code as an author and start looking at it as a user. If there are questions in your head, they should not be postponed or ignored. They can be addressed by AI again.

For example, you can ask what happens if the list is empty, if one of the items does not have the necessary data, or if the data comes in unexpected form. Even if you don’t know what questions to ask, it’s also solvable. You can ask directly, “What problems are possible here?” or “In what cases can this code break?”

In our example, it is easy to see that the code is designed for perfect data. It assumes that the right fields exist and have the right type. It's not a mistake or a flaw. It simply means that no one has yet checked out bad scenarios.

## Why “working” is not a test

The phrase “I work for you” says nothing about the quality of the code. Working code can be fragile, inconvenient to change, or incomprehensible the next time you access it. This is especially important if you do not write the code yourself, but work with the result of generation.

AI almost always writes code for the current query and current situation. It does not consider how this code will be used further unless asked to do so separately. Therefore, the fact of the launch is not the end, but only the beginning of the test.

## How to use AI if you can’t code

AI is useful not only as a generator, but also as an explanatory tool. It can be used as a translator between code and human language. You can ask them to explain logic, specify weaknesses, or rewrite code more easily if the current version is unclear.

The important thing here is to accept the simple fact that if you don’t understand the code, the next step is to ask another question. The explanation does not give a hundred percent guarantee, but without it understanding will not appear at all.