Vibe Coding · 课时

避免人工智能代码陷阱

了解幻觉、代码膨胀和隐蔽错误

避免人工智能代码陷阱 是 CoddyKit 上的免费 Vibe Coding 课时。这是第 2 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Vibe Coding 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Vibe Coding 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

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.

常见问题解答

「避免人工智能代码陷阱」课时是免费的吗？

是的 — 「避免人工智能代码陷阱」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Vibe Coding 课程的其余内容，请升级到 CoddyKit PRO。 Vibe Coding 课程共包含 4 节课。

「避免人工智能代码陷阱」这节课中我会学到什么？

了解幻觉、代码膨胀和隐蔽错误你通过在浏览器中直接运行的动手代码来练习 Vibe Coding，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Vibe Coding 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Vibe Coding 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 2 节课，共 4 节。

「避免人工智能代码陷阱」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Vibe Coding 课中编写并运行代码吗？

能。每节 Vibe Coding 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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