Why AI Code Repeats Itself: Inside the Loop of LLM Logic

"Insanity is doing the same thing over and over again and expecting different results." — Einstein (probably).

"AI coding is doing the same thing over and over again because it has the highest probability of being syntactically correct." — Us.

One of the most common "vibes" of AI-generated code is repetition. Not just repeating code blocks, but repeating patterns. Why does a machine with access to the entire internet get stuck in such a boring loop?

The Probability Trap

Large Language Models (LLMs) are, at their core, prediction engines. They want to predict the next token that minimizes "perplexity" (surprise).

Repetition is safe. If an LLM writes a `validateUser` function in a certain way, and then needs to write a `validateProduct` function, the statistically safest bet is to use the exact same structure.

Changing the structure introduces risk. It introduces "entropy." And LLMs hate entropy.

Spotting the "Copy-Paste" Vibe

function createUser(data) {
  if (!data) return null;
  try {
    const user = db.create(data);
    log('User created');
    return user;
  } catch (e) {
    log('Error');
    return null;
  }
}

function createPost(data) {
  if (!data) return null;
  try {
    const post = db.create(data);
    log('Post created');
    return post;
  } catch (e) {
    log('Error');
    return null;
  }
}

if (!user.firstName) {
  throw new Error('First name is required');
}
if (!user.lastName) {
  throw new Error('Last name is required');
}
if (!user.email) {
  throw new Error('Email is required');
}
if (!user.password) {
  throw new Error('Password is required');
}

const required = ['firstName', 'lastName', 'email', 'password'];
required.forEach(field => {
  if (!user[field]) throw new Error(`${field} is required`);
});

Why This Matters

You might think, "So what? It works." But repetitive code has a cost:

• Maintenance Nightmare: If you need to change the error handling logic, you now have to change it in 50 places instead of one helper function.
• Bloat: Your codebase grows significantly larger than it needs to be.
• Cognitive Load: Developers have to read more lines of code to understand what is happening.

Breaking the Loop

When you see AI generating repetitive code, don't just accept it. Challenge it.

1. Prompt for DRY: Tell the AI, "Refactor this to be DRY (Don't Repeat Yourself)."
2. Ask for Abstractions: "Create a generic handler for this logic."
3. Manual Refactor: Accept the AI output as a draft, then extract the patterns yourself.