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Iam vin
Iam vin

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AI Hall of Shame: How 4 Most Powerful AI Failed My Bug, and Backspace Won

The AI Hall of Shame 😅

How I Beat a 15-Day React Bug That Outsmarted 4 AI Geniuses


The Setup 🎭

Imagine this: You’re building a sleek art competition platform with Next.js and Supabase. Everything’s looking great — artists can upload their work, people can vote in real time, navigation is buttery smooth.

Then… bam.
A tiny, annoying flicker pops up every time you switch browser tabs. The gallery disappears, shows a loading spinner, then comes back.

“Eh, easy fix,” I thought.

Spoiler: I was wrong.
What followed was a 15-day debugging saga where I fought four of the most advanced AI coding models… and won.


The Project 🎨

The site had some neat features:

  • User uploads: Artists submit their masterpieces
  • Live voting: Likes update instantly via Supabase
  • Multiple pages: Gallery, dashboard, voting
  • React Query: For smooth data fetching & caching

Everything was perfect… except for The Flicker™.


The Bug 🐛

Every time I switched tabs and came back, the gallery blinked like a shy contestant on a game show.

The symptoms:

  • React Query cache seemed to reset
  • Components re-rendered with empty data
  • Loading states triggered unnecessarily

It was subtle, but it drove me nuts.


The Challengers 🥊

In the Red Corner:

  • DeepSeek R1 (logic ninja 🥷)
  • Gemini 2.5 Pro (Google’s heavyweight)
  • ChatGPT 4o (the OG)
  • Claude Sonnet 4.0 (the philosophical one)

In the Blue Corner:

  • One increasingly sleep-deprived human developer

Round 1: DeepSeek R1 ❌

Plan: Supercharge React Query’s cache.

  • Tweaked staleTime & cacheTime
  • Added optimistic updates
  • Overhauled cache invalidation
  • Added error boundaries

Code added: ~80 lines
Result: Cache was spotless. Flicker still danced on.


Round 2: Gemini 2.5 Pro ❌

Plan: Rebuild the architecture.

  • Aggressive useMemo & useCallback
  • Optimized dependency arrays
  • Split components, added lazy loading
  • Tightened context logic

Code added: ~120 lines
Result: Faster overall. Flicker didn’t care.


Round 3: ChatGPT 4o ❌

Plan: State management revamp.

  • Cleaner loading states
  • Async flow improvements
  • Lifecycle tweaks
  • More graceful error handling

Code added: ~60 lines
Result: Better UX… flicker still smirking.


Round 4: Claude Sonnet 4.0 ❌

Plan: “Smart” loading states.

  • Multi-level userDataLoaded checks
  • Conditional rendering layers
  • Real-time listener tweaks
  • Hydration state fixes

Code added: ~100 lines
Result: Over-engineered masterpiece… flicker still undefeated.


The Turning Point 💡

After 15 days of AI wizardry, I was staring at this:

if (authLoading || userIdLoading || (submissionsLoading && allSubmissions.length === 0)) {
  return Loading...
}
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Then it hit me:

“What if the problem isn’t what I need to add… but what I need to remove?”

I tried this:

if (authLoading || (submissionsLoading && allSubmissions.length === 0)) {
  return Loading...
}
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BOOM. 💥 Flicker gone.


The Real Culprit 🕵️

  • Cause: userIdLoading briefly flipped to true after tab switches, triggering the loading state and wiping the gallery.
  • Fix: Delete userIdLoading || from the condition.
  • Damage Report:

    • Characters deleted: 14
    • Days lost: 15
    • AI egos bruised: 4
    • Extra code suggested: ~360 lines

The AI Autopsy 🔬

After the win, I asked the AIs why they failed. Here’s the tea:

DeepSeek R1:

“We see code statistically, not in context. If three loading checks look valid, we don’t question them.”

Gemini 2.5 Pro:

“We can’t see the flicker. Timing issues are invisible to us.”

ChatGPT:

“We pattern-match bugs to common fixes, but miss the human intuition of ‘maybe this isn’t needed.’”

Claude:

“Simple fixes don’t make it into our training data. We’re trained to sound smart, not be simple.”


Lessons Learned 📚

For Developers:

  1. Start simple — try deleting before refactoring
  2. Question every condition
  3. Trust your gut
  4. Let AI design architecture, but debug with your brain
  5. Remember Occam’s Razor: simplest is usually right

About AI Limits:

  • They love complex “impressive” answers
  • They can’t perceive time-based UI glitches
  • They miss root causes hiding in plain sight

The Hall of Shame Scoreboard 🏆

🏆 Human: -14 characters → bug dead
❌ DeepSeek: +80 lines
❌ Gemini: +120 lines
❌ ChatGPT: +60 lines
❌ Claude: +100 lines
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Final Thoughts 🎯

Sometimes the smartest code… is the code you don’t write.
Next time AI tells you to rebuild your app to fix a flicker — maybe try deleting one line first.


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