⚠️ This isn’t another “how to use ChatGPT or any other AI” guide. This is a raw, real-life reflection on how I — a self-taught developer of 7+ years — use AI to level up, not dumb down.
✨ Why I Wrote This
We’re living in the AI-driven coding era.
Everyone’s rushing to prompt faster, automate more, and get stuff done with zero real understanding. But here’s the harsh truth:
🧨 If you let artificial intelligence replace your critical thinking, you’re on the fast track to becoming a "vibe coder" — and yes, I said it.
But if you use AI coding assistants wisely...
If you learn when to say “not yet, AI”...
You’ll evolve faster than ever before — without losing your edge as a developer.
This is how I do it.
This is how you can future-proof your dev journey in the AI era.
⚙️ My Philosophy: AI Is a Tool, Not a Teacher
AI coding tools are mind-blowing — but they’re only as effective as your base knowledge. They are brilliant at handling repetitive tasks and summarizing code, but they don’t:
- ❌ Truly understand your unique context.
- ❌ Reason beyond the patterns in their training data.
- ❌ Invent creative solutions on their own.
Remember: AI is trained on public data. It knows what’s out there — not your unique engineering problem.
If it’s not documented online, AI can't solve it. Simple.
So I follow a system:
- Learn the traditional way first.
- Use AI as a validator or productivity booster.
- Never sacrifice understanding.
Here’s how that looks in practice.
📚 Mastering Knowledge: How I Learn with and Without AI
When I want to learn something new (language, concept, framework), here’s what I always do:
✅ My Learning Stack:
- Google like a pro ninja: Use high-intent search keywords.
- Watch multiple YouTube tutorials: Different creators offer diverse perspectives.
- Dig into official documentation: Get the straight facts.
- Explore Stack Overflow, Reddit threads, blogs, and forums: Every discussion reveals hidden nuggets.
- Embrace the confusion: It means I’m challenging my brain and building critical problem-solving skills.
Then, and only then, do I ask AI:
- Here’s what I’ve learned. Did I miss something?
- Is my understanding correct?
- Is there a better way to approach this?
🔥 Why This Method Works for Me
- Retention: I retain technical knowledge longer.
- Enhanced Searching: I build elite research skills.
- Broad Learning: I capture intentional and accidental insights.
🌐 The Internet (Knowledge Goldmine) Knows Everything — If You Know How to Ask
Before diving into my problem-solving framework, here’s a core belief that makes my system work:
🧠 Most coding problems — no matter how weird, niche, or hopeless —
🌍 someone, somewhere on the internet, has already faced, solved, and shared the solution.
You just need to:
- Use high-intent search keywords.
- Be patient and persistently curious.
- Dig deep into dev forums and communities.
🤔 Why Does the Internet Always Seem to Have the Solution?
- ✅ Developers are generous problem-sharers.
- ✅ Real developers blog, post, and document bugs, breakthroughs, and struggles.
- ✅ Open-source communities (Stack Overflow, GitHub, Reddit, etc.) are filled with millions of solved problems.
We humans solve the same categories of problems generation after generation.
The tools change. The syntax evolves.
But the core problems? Most have already been debugged, patched, and blogged about.
✅ Real-World Proof: Two Problems, One Philosophy
🧪 Case Study 1: Programming Problem Solved
Before AI tools like ChatGPT and GitHub Copilot, when I hit complex dev problems with no clear direction, I didn’t rush to AI (it didn’t exist yet). Instead, I used:
- GitHub
- Stack Overflow
- Dev.to
- YouTube deep-dives
I read dozens of threads, mixed partial solutions, and reverse-engineered what worked for my context.
And yes — I found the solution.
From the chaotic, time-tested treasure trove that is the internet.
That’s the power of search. That’s the power of self-reliance.
🔧 Case Study 2: Resurrecting My Hard-Bricked Phone
In 2019, my Realme C2 hard-bricked. Every forum said:
“Hard brick = dead forever.”
But I didn’t give up.
- I searched obsessively for 5 days.
- My internet was slow.
- The phone wasn’t flagship — few wrote about it.
- I scoured niche blogs, sketchy forums, and obscure YouTube videos.
Finally, I found one article with a method to try.
I followed it, and... my phone came back to life.
No AI (it didn’t exist yet). No shortcut. Just curiosity and persistence.
🎯 The Core Idea
🗺️ The solution is almost always somewhere out there.
You don’t need superpowers — just searching skills, curiosity, and time.
That’s why I say:
“Don’t give up because you don’t know the answer. Trust the internet, trust yourself, keep searching — someone probably does.”
While genuinely novel problems are rare, when they arise, I combine AI tools with traditional problem-solving to tackle them.
🧩 My Two-Mode AI-Era Problem-Solving Framework
After hundreds of challenges, I built a framework that blends traditional research with AI assistance:
🧪 Mode 1: Known or Familiar Problem
- Think through the logic.
- Prompt AI with my plan.
- Let AI write the code.
- (Optional) Ask for optimization.
- Done.
🧱 Mode 2: Unknown or Unfamiliar Problem
- Google. Read. Watch. Compare. Analyze.
- Gather 2–3 real-world perspectives.
- Build my own solution manually.
- THEN, ask AI:
- Does this solution make sense?
- Can this be optimized?
- Any alternate approaches?
Compare my approach vs. AI’s. Merge, improve, upgrade.
This creates “mental caching” — solving deeply once, then recalling + prompting.
⚡ Using AI to Supercharge Productivity
Let’s be honest — not every task requires a deep dive.
Some work is repetitive, boring, or already solved.
When I’m working on:
- Filtering data
- Writing boilerplate
- Refactoring structure
- Generating regex or config
...I don’t waste time.
That’s when AI becomes my assistant.
🛠️ Here’s My Process:
- I know the logic.
- I describe the structure.
- I let AI code it:
“Write a Python script to convert this CSV into nested JSON — like this format I’ve used before.”
If I have time, I’ll ask:
“Is this optimized?”
“What edge cases might I miss?”
“Could this be more elegant?”
This way, AI speeds me up, but I’m still in control.
🧠 Why Skipping Traditional Learning Will Cost You
AI feels fast. But here’s the problem:
❌ If you skip the hard part, you miss:
- Diverse developer perspectives.
- War stories and accidental wisdom.
- Problem-solving instincts.
- Long-term retention.
✅ Traditional learning builds:
- Context.
- Technical empathy.
- Deep understanding.
- Real wisdom.
Rely only on AI?
You’re feeding your brain one-liner answers for multi-layered problems.
🤖 What AI Actually Is — A Brutally Honest Reality Check
People romanticize AI. Here’s the truth:
- AI is a statistical language predictor.
- Trained on public data = it knows what exists, not what you imagine.
- It can’t “think” — it mimics.
- Brilliant at summarizing, terrible at inventing.
If your problem isn’t in its training data?
It’ll hallucinate. Throw jargon. Waste your time.
Don’t give AI your trust. Give it your ideas.
Let it help — don’t let it lead.
🚫 Beware the Rise of Vibe Coders
You’ve seen them:
Devs who copy-paste AI answers without understanding. They look fast. But when things break? They’re lost.
If AI disappears tomorrow, vibe coders disappear too.
They’ve built:
- Speed, not skills.
- Productivity, not problem-solving.
- Velocity, not value.
And if this trend continues?
We’ll have coders who ship features but can’t explain a line of their code.
Related read: 🚀 The Rise of "Vibe Coders" – And Why Real Skills Matter More Than Ever
🔒 How to Stay Future-Proof in the AI-Powered Dev World
My anti-vibe coder checklist:
- 🧠 Learn fundamentals (data structures, algorithms, system design).
- 🧭 Use AI for acceleration, not strategy. You lead; it follows.
- ✍️ Craft better prompts through practice.
- 🔍 Search intentionally — ask clear, specific questions.
- 💥 Stay curious. Ask why, not just how.
- ♻️ Re-solve problems manually sometimes.
- ✔️ Validate everything. Cross-check AI outputs.
You become irreplaceable by thinking, not prompting.
💬 Final Thoughts
AI coding assistants are here to stay — like calculators for developers. They boost productivity (studies suggest 30–50% efficiency gains for routine tasks). But they only enhance your work if you maintain strong foundational skills. Learn, search, prompt wisely — and never stop solving problems on your own. This is how you stay valuable in an AI-dominated era.
As tech evolves (see Strictly Savvy and Andrew Zuo), the future belongs to those who use AI to enhance — not replace — human ingenuity.
❓ FAQs
Q: Can I use AI while learning?
Yes — after exploring traditional resources.
Q: Should I prompt AI if I already know the answer?
Absolutely! Save time, but validate and improve.
Q: Isn’t relying on AI cheating?
No. Cheating is when you don’t understand what you’re doing.
Q: How do I get better at problem-solving?
Struggle first. Search deep. Let AI help you grow — not just get by.
Q: Is vibe coding really that bad?
Yes. It leads to shallow skills and limited growth.
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❤️ If this helped you think clearer about AI, leave a like, share your thoughts, and help others avoid becoming vibe coders.
Top comments (2)
This is one of the most honest and insightful takes on using AI as a developer. Loved the balance between embracing AI and preserving core problem-solving skills. Your framework is practical, relatable, and genuinely empowering. A must-read for devs trying to grow without becoming dependent. Thanks for sharing your journey!
you're most welcome 🤗