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Vibe Coding · 강의

인공지능 코드의 함정 피하기

환각, 불필요한 비대화와 조용히 발생하는 버그를 알아봅니다.

인공지능 코드의 함정 피하기은(는) CoddyKit의 무료 Vibe Coding 강의입니다. 이것은 4개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Vibe Coding 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Vibe Coding 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

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.

자주 묻는 질문

“인공지능 코드의 함정 피하기” 강의는 무료인가요?

네 — “인공지능 코드의 함정 피하기” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Vibe Coding 강의 전체를 잠금 해제할 수 있습니다. Vibe Coding 강의에는 총 4개의 강의가 포함되어 있습니다.

“인공지능 코드의 함정 피하기”에서 뭘 배우나요?

환각, 불필요한 비대화와 조용히 발생하는 버그를 알아봅니다. 브라우저에서 직접 실행하는 실습 코드로 Vibe Coding을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Vibe Coding을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Vibe Coding은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 2번째 강의입니다.

“인공지능 코드의 함정 피하기” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Vibe Coding 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Vibe Coding 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

이 강의의 모든 강의

  1. 바이브할 때와 이해할 때
  2. 인공지능 코드의 함정 피하기
  3. 진정한 개발자로 성장하기
  4. 나만의 바이브 코딩 플레이북
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