Bugs und schlechte Muster erkennen
Häufige Fehler der KI und wie Sie sie entdecken
Bugs und schlechte Muster erkennen ist eine kostenlose Vibe Coding-Lektion auf CoddyKit. Dies ist Lektion 3 von 4. Du kannst die komplette Lektion unten kostenlos lesen – dann übst du sie direkt im Browser mit einem integrierten Code-Editor und einem KI-Tutor rund um die Uhr. Sie ist Teil des Vibe Coding-Lernpfads, und dein Fortschritt wird über Web und CoddyKit-App synchronisiert. Der Vibe Coding-Kurs umfasst insgesamt 4 Lektionen.
Teile dieser Lektion wurden noch nicht übersetzt und werden auf Englisch angezeigt.
Learn the AI Mistake Patterns
AI makes the same kinds of mistakes over and over. Once you know the patterns, you'll spot them in seconds — like a detective who's seen the same trick a hundred times.
This lesson is a field guide to the most common bugs and bad patterns in AI-generated code, plus how to catch each one. No deep CS background needed.
You don't memorize fixes — you learn what to watch for.
Pattern 1: Missing Edge Cases
AI loves the 'happy path' and often forgets the messy reality: empty lists, missing data, zero, or null.
Run this average function with a normal list — it works. But picture what happens if the list is empty.
function average(numbers) {
let sum = 0;
for (const n of numbers) sum += n;
return sum / numbers.length;
}
console.log(average([10, 20, 30])); // 20, fine
console.log(average([])); // NaN — divide by zero!Catching Edge Cases
The empty list gave NaN (not a number) because it divided by zero. In a real app that could show 'NaN' to a user or crash later.
The catch: whenever you see code that loops, divides, or reads a property, ask 'what if it's empty or missing?'
Fix prompt you can paste: 'Handle the empty-list case and any null inputs in this function. Return a sensible default and explain your choice.'
Pattern 2: Reading Missing Data
AI often assumes data is always shaped perfectly. Reach into an object that might not have what you expect, and you get the classic crash.
This one throws a real error. Run it and read the message.
function getCity(user) {
return user.address.city; // assumes address always exists
}
const u = { name: 'Sam' }; // no address!
console.log(getCity(u)); // TypeError: Cannot read properties of undefinedCatching Missing-Data Bugs
That Cannot read properties of undefined error is one of the most common in all of web development. AI generates it constantly because it assumes ideal data.
Watch for chains like a.b.c where any middle piece could be missing. The safe pattern uses optional chaining: user.address?.city, which returns undefined instead of crashing.
When you see deep property access on user input or API data, flag it for review.
Pattern 3: Hardcoded Secrets
A dangerous favorite: AI pastes an API key or password directly into the code to make the example 'just work.'
If this ships to GitHub or the browser, anyone can steal your key and run up your bill. Never let a literal secret survive review.
// DANGER: secret key hardcoded in the source
const STRIPE_KEY = 'sk_live_51HxAbC9secretrealkey';
fetch('https://api.stripe.com/charge', {
headers: { Authorization: 'Bearer ' + STRIPE_KEY }
});
// Keys belong in environment variables, never in codePattern 4: Silent Failures
Sometimes AI 'handles' an error by swallowing it — the app keeps going as if nothing happened, hiding the real problem.
The empty catch below means if the fetch fails, you get no warning, no log, just mysteriously missing data.
async function loadData(url) {
try {
const res = await fetch(url);
return await res.json();
} catch (e) {
// swallows the error silently — bad!
return null;
}
}
// You'll never know WHY it returned nullPattern 5: Overcomplicated Code
AI sometimes writes 30 lines for a 3-line job, or adds clever abstractions you didn't ask for. Complexity is where bugs hide and future-you gets lost.
If a simple task produced a tangled result, push back. Try: 'This feels more complex than the task needs. Rewrite it as simply as possible and explain why each part is necessary.'
Simple code you understand beats clever code you don't.
Pattern 6: It Doesn't Match the Goal
The sneakiest bug isn't broken code — it's working code that solves the wrong problem.
You asked to sort newest-first; AI sorted oldest-first. You asked to email active users; it emailed everyone. No error, just the wrong outcome.
Always re-read your original ask and check the output against your intent, not against 'does it run.' This is the bug AI can't catch for you.
Let AI Hunt Its Own Bugs
You don't have to find everything alone. Point AI at the code with a sharp, suspicious prompt and it'll surface many of these patterns.
Keep this prompt handy — it targets exactly the patterns from this lesson.
Audit this code for bugs and bad patterns. Check specifically for:
- Missing edge cases (empty, null, zero)
- Crashes from missing data (deep property access)
- Hardcoded secrets or API keys
- Silently swallowed errors
- Overcomplicated logic
- Anything that doesn't match this goal: [describe your goal]
List each issue, the line, and a fix.Build Your Spotting Instinct
Your bug radar, summarized:
- Loops and division? Check empty and zero.
- Deep property access? Check missing data.
- Keys or passwords? Never hardcoded.
- Empty catch blocks? Silent failure.
- Too much code? Ask for simpler.
- Always: does it match what I actually asked for?
Run this scan on every chunk and you'll catch the vast majority of AI mistakes.
Quick Check
AI writes return user.address.city; and some of your users have no address. What kind of bug is this, and how do you catch it during review?
Recap: Catch the Common Bugs
The AI mistake patterns you can now spot:
- Missing edge cases — empty lists, null, divide-by-zero.
- Missing-data crashes — deep property access on imperfect data.
- Hardcoded secrets — keys must live in environment variables.
- Silent failures — empty catch blocks that hide errors.
- Overcomplication — push for the simplest version.
- Wrong goal — working code that solves the wrong problem.
Scan for these every time, and let AI audit itself too. Next: deciding what to keep, fix, or reject.
Häufig gestellte Fragen
Ist die Lektion „Bugs und schlechte Muster erkennen“ kostenlos?
Ja — der vollständige Text von „Bugs und schlechte Muster erkennen“ ist hier im Web kostenlos zu lesen. Um sie interaktiv zu üben (integrierter Code-Editor und 24/7 KI-Tutor) und den Rest des Vibe Coding-Kurses freizuschalten, upgrade auf CoddyKit PRO. Der Vibe Coding-Kurs umfasst insgesamt 4 Lektionen.
Was lerne ich in „Bugs und schlechte Muster erkennen“?
Häufige Fehler der KI und wie Sie sie entdecken Du übst Vibe Coding mit praktischem Code, den du direkt im Browser ausführst, und ein 24/7 KI-Tutor beantwortet deine Fragen während du die Lektion bearbeitest.
Brauche ich Erfahrung, um Vibe Coding zu starten?
Keine Vorkenntnisse erforderlich. Vibe Coding auf CoddyKit ist für Anfänger bis fortgeschrittene Lernende strukturiert, sodass du hier starten oder von Anfang an beginnen und in deinem eigenen Tempo voranschreiten kannst. Dies ist Lektion 3 von 4.
Wie lange dauert die Lektion „Bugs und schlechte Muster erkennen“?
Die meisten CoddyKit-Lektionen dauern etwa 5–10 Minuten. Jede ist kompakt und interaktiv, sodass du stetig Fortschritte machst und genau dort weitermachst, wo du aufgehört hast – im Web und in der App.
Kann ich in dieser Vibe Coding-Lektion Code schreiben und ausführen?
Ja. Jede Vibe Coding-Lektion enthält einen integrierten Code-Editor, sodass du echten Code direkt in deinem Browser schreibst und ausführst und sofort KI-Feedback erhältst — ohne lokale Einrichtung erforderlich.
Alle Lektionen in diesem Kurs
- Warum Sie KI-Code prüfen müssen
- Code lesen, den Sie nicht geschrieben haben
- Bugs und schlechte Muster erkennen
- Behalten, korrigieren oder verwerfen