Why Vibe Coding Fails When Real Debugging Is Needed

Anyone can build an app in a day

That’s the promise.

Just vibe it. Use ChatGPT, Claude, Gemini — whatever’s trending. Let AI do the heavy lifting.

Except… that’s not what really happens.

At a Glance

• Vibe coding is popular but misleading
• Real development problems need debugging, planning, and tech skills
• AI tools like ChatGPT, Claude, and Gemini help but don’t replace knowledge
• Case study: what really happened when I tried building a 3-LLM AI app
• Essential tools and takeaways for those serious about building

The Myth of the One-Day App

“Just use an LLM to build your app in a few hours.”

You’ll hear it everywhere.

And sure, you can throw something together fast. A front end, a couple of prompts, maybe a fancy UI from a template site. But that’s surface-level stuff.

Try integrating three large language model APIs.

Try keeping them stable across sessions.

Try logging and debugging when something silently fails.

You’ll quickly find out — vibes don’t scale.

Real Scenario: Building with 3 AI APIs

I decided to build a small app using three different LLM APIs. The concept was simple: compare answers across models to generate a blended result. I thought I’d have it live by the end of the weekend.

Here’s what actually happened:

1. Repeated errors with no clear reason
   One API kept throwing the same error. Logs were useless. I had to guide the AI assistant (yes, the one that helped build the app) to write manual error logging code.
2. LLM-generated code couldn’t self-debug
   I used ChatGPT, Claude, and Gemini at different points. All gave working-looking code. But none could trace the root cause without me stepping in.
3. Developer tools became essential
   I opened the browser dev tools, watched API requests fail in real time, and inspected raw JSON responses. That’s when things started making sense.
4. Finally got it working — manually
   After hours of testing, rewriting, and re-prompting, the app ran properly. Not because of the AI tools — but because I had the background to troubleshoot what they couldn’t.

When Vibes Fail, These Tools Don’t

If you want your app to work beyond the demo, these are the tools that matter.

🔧 Tools That Actually Help

• Postman / Insomnia – Essential for testing APIs properly
• Browser DevTools (Chrome/Firefox) – Inspect network requests and diagnose issues
• VS Code + REST Client – Run and debug requests inside your editor
• Sentry / LogRocket – Catch and log production errors
• Prompt engineering dashboards – Tools like PromptLayer for tracking prompt performance
• GitHub Copilot / Cody – Help speed things up, but only if you check their work

🧠 Skills You Can’t Skip

• Understanding HTTP requests, headers, and error codes
• Handling async flows and retry logic
• Reading API docs and spotting limitations
• Managing rate limits and token usage
• Logging correctly (and actually reading the logs)
• Knowing what “works” really means in production

Without those, your “day-one app” becomes a day-ten headache.

The LLMs Help — But They’re Not Devs

AI coding assistants are useful. No doubt.

ChatGPT, Claude, Gemini, Copilot — they’ll save you hours.

But they still get things wrong.

They hallucinate libraries. Mix up APIs. Skip edge cases. And they rarely handle debugging without you stepping in.

If you don’t know what you’re doing, they’ll just help you get stuck faster.

Final Takeaways

• Vibe coding is a trap for beginners. It works until something breaks.
• LLM tools are powerful assistants. But they need strong direction.
• Real projects need structure. Planning, testing, and fallback logic matter.
• You can’t skip the boring stuff. Logging, API management, error handling — that’s where stability lives.
• Want to ship fast? Learn slowly. The deeper your foundation, the faster your builds.

Anyone can vibe an idea into a prototype.

But if you want something reliable, repeatable, and real?

You’re going to need more than vibes.

🔗 Want More Like This?

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Because the truth is — apps don’t build themselves.

And vibes don’t fix bugs.