Vibe Coding · Lesson

Avoiding AI Code Pitfalls

Hallucinations, bloat and silent bugs.

Avoiding AI Code Pitfalls is a free Vibe Coding lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Vibe Coding learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

AI Gets Things Wrong

AI coding tools are confident, fast, and sometimes flat-out wrong. The danger isn't that they fail loudly, it's that they fail quietly, producing code that looks right and runs without errors but does the wrong thing.

In this lesson you'll learn the three most common pitfalls: hallucinations, bloat, and silent bugs, plus how to catch each one before it hurts you.

Pitfall 1: Hallucinations

A hallucination is when the AI invents something that doesn't exist: a function, a library, an API endpoint, or a config option it just made up because it sounds plausible.

You'll see it import a package that isn't real, or call a method like array.sortDescending() that JavaScript doesn't have. The code looks reasonable until you run it and get "is not a function."

Catching Hallucinated APIs

The fastest hallucination check is simply to run the code. Here the AI "helpfully" used a method that doesn't exist. Run this and read the error, that error message is your friend.

const nums = [3, 1, 2];
try {
  // AI hallucinated this method; it isn't real
  console.log(nums.sortDescending());
} catch (e) {
  console.log('Caught:', e.message);
  // Real way:
  console.log('Correct:', [...nums].sort((a, b) => b - a));
}

Defending Against Hallucinations

Three habits stop most hallucinations cold:

Run early, run often. Don't stack 200 lines before testing.
Ask for real, popular tools. Tell the AI to use well-known libraries, not obscure ones it might invent.
Verify imports. If it imports a package, check it actually exists on npm before trusting it.

Use only well-established, popular npm libraries for this.
If you're unsure a function or method exists, say so instead of guessing.
After writing the code, list every external package you used so I can verify it.

Pitfall 2: Bloat

Bloat is when the AI gives you far more than you asked for: extra abstractions, unnecessary libraries, ten config files for a one-page app, or a 100-line solution to a 10-line problem.

Bloat feels productive, more code! but it's a trap. Every extra line is something you have to understand, maintain, and debug later. Lean code is a feature, not a limitation.

Asking for Lean Code

You can steer the AI away from bloat just by saying so. Be explicit that simplicity is the goal, AI will happily over-engineer if you don't push back.

Write the SIMPLEST version that works.
- No extra libraries unless truly necessary
- No clever abstractions, no premature optimization
- Prefer 10 readable lines over 50 "flexible" ones
If you add anything beyond what I asked, explain why in one sentence.

Spotting Bloat in Practice

Compare these two solutions to the same problem: get unique values from a list. Both work, run it, but the bloated one drags in extra machinery for no benefit. When AI hands you the heavy version, ask for the simple one.

const items = ['a', 'b', 'a', 'c', 'b'];

// Bloated: manual loop + helper object
function uniqueBloated(arr) {
  const seen = {};
  const out = [];
  for (const x of arr) { if (!seen[x]) { seen[x] = true; out.push(x); } }
  return out;
}

// Lean: built-in Set
const uniqueLean = [...new Set(items)];

console.log(uniqueBloated(items));
console.log(uniqueLean);

Pitfall 3: Silent Bugs

The scariest pitfall: code that runs without errors but is subtly wrong. The AI handles the happy path and quietly ignores the edge cases.

Classic examples: an empty list, a missing value, a negative number, a date at midnight, a user with no name. The demo works in the meeting and breaks for a real user on Tuesday.

A Silent Bug in Action

This "average" function looks fine and works for normal input. But run it and watch what happens with an empty list, it returns NaN instead of failing loudly. A silent bug waiting to corrupt a report.

function average(nums) {
  let total = 0;
  for (const n of nums) total += n;
  return total / nums.length; // breaks silently when empty
}

console.log(average([2, 4, 6])); // 4, fine
console.log(average([]));        // NaN, silent bug!

// Safer version:
const safeAvg = a => a.length ? a.reduce((s, n) => s + n, 0) / a.length : 0;
console.log(safeAvg([]));        // 0

Hunting Silent Bugs

The cure for silent bugs is to actively go looking for them. After the AI writes a function, ask it to attack its own work:

Here's the function you just wrote. Act like a tester trying to break it.
List the edge cases that could make it fail or give a wrong answer:
empty input, missing fields, zero, negatives, very large values, duplicates.
Then write a quick test for each one and show me the results.

Your Pitfall Defense Kit

Three pitfalls, three reflexes:

Hallucinations → run early, verify imports, ask for real tools.
Bloat → demand the simplest version, question every extra.
Silent bugs → make the AI test its own edge cases.

None of these require deep CS knowledge. They just require the habit of not trusting code until you've seen it behave.

Quick Check

An AI writes a function that runs with no errors and works in your demo, but returns a wrong number when given an empty list. What kind of pitfall is this?

Recap

You can now name and catch the big three AI failure modes:

Hallucinations: invented functions, libraries, or APIs, caught by running code and verifying imports.
Bloat: over-engineered solutions, cured by demanding the simplest version.
Silent bugs: correct-looking code that fails on edge cases, hunted by making the AI test its own work.

Catching these is what separates a builder who ships reliable apps from one who ships surprises. Next: how to use AI to actually grow your own skills.

Frequently asked questions

Is the “Avoiding AI Code Pitfalls” lesson free?

Yes — the full text of “Avoiding AI Code Pitfalls” is free to read here on the web, and the Vibe Coding course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Vibe Coding course, upgrade to CoddyKit PRO.

What will I learn in “Avoiding AI Code Pitfalls”?

Hallucinations, bloat and silent bugs. You practise Vibe Coding with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Vibe Coding?

No prior experience is required. Vibe Coding on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Avoiding AI Code Pitfalls” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Vibe Coding lesson?

Yes. Every Vibe Coding lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

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