Cómo evitar problemas del código generado por IA
Alucinaciones, código innecesario y errores silenciosos
Cómo evitar problemas del código generado por IA es una lección gratuita de Vibe Coding en CoddyKit. Esta es la lección 2 de 4. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de Vibe Coding, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de Vibe Coding incluye 4 lecciones en total.
Partes de esta lección aún no han sido traducidas y se muestran en inglés.
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([])); // 0Hunting 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.
Preguntas frecuentes
¿La lección «Cómo evitar problemas del código generado por IA» es gratis?
Sí — el texto completo de «Cómo evitar problemas del código generado por IA» es gratis para leer aquí en la web. Para practicarla de forma interactiva (editor de código integrado y tutor de IA 24/7) y desbloquear el resto del curso de Vibe Coding, actualiza a CoddyKit PRO. El curso de Vibe Coding incluye 4 lecciones en total.
¿Qué aprenderé en «Cómo evitar problemas del código generado por IA»?
Alucinaciones, código innecesario y errores silenciosos Practicas Vibe Coding con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.
¿Necesito experiencia previa para empezar Vibe Coding?
No se requiere experiencia previa. Vibe Coding en CoddyKit está estructurado para principiantes hasta estudiantes avanzados, así que puedes empezar aquí o desde el inicio y avanzar a tu ritmo. Esta es la lección 2 de 4.
¿Cuánto tiempo toma la lección «Cómo evitar problemas del código generado por IA»?
La mayoría de las lecciones de CoddyKit toman alrededor de 5–10 minutos. Cada una es compacta e interactiva, así que avanzas constantemente y retomas exactamente por donde dejaste en la web y la app.
¿Puedo escribir y ejecutar código en esta lección de Vibe Coding?
Sí. Cada lección de Vibe Coding incluye un editor de código integrado, así que escribes y ejecutas código real directamente en tu navegador y obtienes retroalimentación instantánea de IA — sin configuración local necesaria.
Todas las lecciones de este curso
- Cuándo usar Vibe Coding y cuándo comprender
- Cómo evitar problemas del código generado por IA
- Cómo convertirse en un desarrollador de verdad
- Su guía práctica de Vibe Coding