"AI-Generated Code is Bloated" — The Reality

I hear this concern often from CTOs and engineering leads:

"Aren't you worried that AI-generated code is bloated and low quality?"

It's a fair question. And honestly? The concern isn't entirely wrong. But it's also not the whole story.

Yes, AI Code Can Be Bloated

Let's be honest about the problem. AI models often produce code like this:

1// AI loves this pattern
2const handleSubmit = async () => {
3  try {
4    setIsLoading(true);
5    setError(null);
6    const response = await fetch(url);
7    if (!response.ok) {
8      throw new Error(`HTTP error! status: ${response.status}`);
9    }
10    const data = await response.json();
11    if (data && data.success && data.result) {
12      setResult(data.result);
13    }
14  } catch (error) {
15    console.error('Error:', error);
16    setError(error instanceof Error ? error.message : 'Unknown error');
17  } finally {
18    setIsLoading(false);
19  }
20};

When you might only need:

1const handleSubmit = async () => {
2  const { result } = await fetch(url).then(r => r.json());
3  setResult(result);
4};

The AI errs toward "defensive" code. Extra null checks, verbose error handling, enterprise patterns where simple patterns suffice.

Why This Happens

AI models are trained on massive code corpuses that include:

• •Enterprise Java patterns applied to simple scripts
• •Stack Overflow answers optimized for "looks complete"
• •Production code with edge cases that don't apply to your situation

The model doesn't know your constraints. It defaults to "probably production, probably needs error handling, probably enterprise."

But Here's What Matters

The question isn't "Is AI code perfect?" It's "Is AI code good enough to ship, and can you improve it?"

1. Shipped Beats Perfect

A working feature with verbose code is infinitely more valuable than a perfect feature that doesn't exist. The per4ex.org portfolio you're reading was built largely with AI assistance. It works. It ships. Users don't care about code elegance.

2. AI Code is Editable

The real skill isn't accepting AI output verbatim—it's knowing what to trim. I treat AI like a fast junior developer who overengineers everything. Great for scaffolding, needs editing.

3. The Alternative is Slower

Before AI assistance, I'd write the same code manually. It would be slightly cleaner, but take 5x longer. For prototypes and MVPs, velocity wins.

How I Actually Work

My workflow with AI isn't "generate and ship." It's:

1. •Generate — Let AI write the first draft
2. •Review — Read what it produced
3. •Trim — Remove unnecessary abstraction
4. •Refactor — Clean up the hot paths later

The first pass might be bloated. The final code isn't.

Example: Real Refactoring

AI gave me this for a simple utility:

1export function formatDate(date: Date | string | number): string {
2  let dateObj: Date;
3  if (typeof date === 'string') {
4    dateObj = new Date(date);
5  } else if (typeof date === 'number') {
6    dateObj = new Date(date);
7  } else if (date instanceof Date) {
8    dateObj = date;
9  } else {
10    throw new Error('Invalid date input');
11  }
12  
13  if (isNaN(dateObj.getTime())) {
14    throw new Error('Invalid date');
15  }
16  
17  return dateObj.toLocaleDateString('en-US', {
18    month: 'short',
19    day: 'numeric', 
20    year: 'numeric'
21  });
22}

I simplified to:

1export const formatDate = (date: Date | string) =>
2  new Date(date).toLocaleDateString('en-US', { 
3    month: 'short', day: 'numeric', year: 'numeric' 
4  });

AI gave me correctness. I gave it elegance.

When Bloat Doesn't Matter

Honestly? Most code doesn't need to be optimized.

The 80/20 rule applies: 20% of your code handles 80% of the load. AI can write the 80% that doesn't matter. You optimize the 20% that does.

For a portfolio site like this:

• •Does it matter if a utility function has extra null checks? No.
• •Does it matter if the AI chat widget responds quickly? Yes.

I spend my optimization time where it counts.

What To Tell Your Team

If you're a technical leader worried about AI code quality, here's my advice:

1. •Set clear review standards — AI output should pass the same review as human code
2. •Focus reviews on architecture, not style — Style can be fixed; bad architecture can't
3. •Measure what matters — Page load time, API latency, bug rates. Not lines of code.
4. •Invest in refactoring later — Ship first, clean up when you know what's important

The Bottom Line

AI code is often verbose. But:

• •It's correct more often than it's wrong
• •It's fast to generate
• •It's editable by humans
• •It ships

The question isn't whether AI code is perfect. It's whether it helps you ship faster while maintaining acceptable quality. For me, the answer is yes.

Have concerns about AI-assisted development for your project? Let's discuss what would work for your team.