When I first heard the term “vibe coding,” I laughed. What a ridiculous name.
But the more I explored it, the more it made sense.
Dan Martell once said something along the lines of,
“If you mastered coding 10 years ago, you’ll have unlimited opportunities in the future.”
He learned to code from a book and an old computer—while serving a juvenile sentence. Now he’s a millionaire software founder.
Fast-forward to today—2025—and things have changed. The new kind of “coding” isn’t just about syntax or spending countless hours debugging.
It’s about the logic behind your ideas.
Vibe coding is the process of creating things by describing your ideas rather than writing every line of code yourself.
It’s like being a director or team lead—you communicate your vision, and your “crew” (AI, automation tools, and APIs) brings it to life.
At the end of last year, I decided it was time to take coding seriously. I wanted to learn Python to understand how software actually works.
I signed up for a 100-day coding course. It took me more like 200.
And while I don’t regret a single line of code, something interesting happened while I was learning:
Technology sprinted ahead.
By the time I finished, you could already build an app without touching a single line of code.
So the big question…
Was all that effort learning to code for nothing?
But first, let’s go back to a few years ago: if you couldn’t write code, you couldn’t build.
Period.
Now, anyone with an idea and an internet connection can.
That’s what vibe coding is about.
You describe your idea clearly, and AI writes the code, runs the scripts, connects the APIs, and even deploys your project… all while you don’t need to know what any of that means!
It’s like having a full development team in a chat window—one that doesn’t need to sleep, take time off, or ask for a raise.
For a while, I was vibe coding without even realizing it—bouncing between ChatGPT, DeepSeek, and Gemini, refining prompts, pasting outputs, testing, fixing, and learning.
Learning the basics of coding wasn’t useless.
It was the thing that helped me vibe better. 😉
Understanding core concepts like loops, data types, and OOP is important. It helped me become better at directing AI—giving clearer instructions, asking smarter questions, and understanding what was happening behind the scenes.
I could speak the AI’s language fluently enough to tell it exactly what I wanted.
So what does the research say?
The AI-Powered Revolution
1. No-code tools are opening the gates.
AI and no-code platforms are making software creation accessible to almost anyone. Gartner’s 2025 projection predicts that 70% of new enterprise apps will be built using low-code or no-code tools—a massive leap from traditional coding models.
This shift is breaking down old barriers and turning AI from a specialist’s privilege into a universal utility.
A 2024 report by CodeConductor.ai found that the number of “citizen developers”—non-technical creators building apps—will grow by 50% by 2025.
2. AI is supercharging developer productivity.
AI-assisted coding tools aren’t just helping—they’re transforming how fast we build.
A 2024 BIS working paper on generative AI and labor productivity showed that tools like CodeFuse increased code output by over 50% on average, mostly by cutting time spent on debugging and documentation.
Similarly, Google Cloud’s 2025 DORA Report found that 90% of developers now use AI tools, with over 80% saying it makes them more productive.
The Enduring Value of Human Expertise
3. Coding fundamentals still matter—especially for security.
AI may write code, but it can’t always write safe code.
A 2025 Veracode report on GenAI security found that LLMs introduced vulnerabilities in 45% of tasks—particularly in cross-site scripting and log injection.
Without human oversight, these flaws go unnoticed, proving that understanding the fundamentals isn’t optional; it’s essential.
4. Debugging is still a human advantage.
Even the smartest tools can’t replace human intuition when something breaks.
As one DEV Community post put it, “Anyone with experience will do the debugging themselves.”
Without a grasp of programming basics, users can’t interpret error messages or understand stack traces—two skills that keep real developers sharp, even in an AI-powered world.
5. Overreliance on AI can weaken your skills.
The convenience of AI comes with a cost.
A 2025 ITPro article warned that many junior developers risk “trading deep understanding for quick fixes.”
While a Harness report showed that 92% of developers shipped more code using AI, it also found that 59% experienced deployment issues at least half the time.
In short, AI can help you move faster—but not necessarily smarter.
6. Coding still builds something no machine can—better thinkers.
Learning to code teaches structure, logic, and creative problem-solving.
A classic 2014 study on Developing Problem-Solving Skills found that programming naturally builds analytical thinking through step-by-step reasoning—analysis, planning, execution, and evaluation.
These are the same mental models that make us adaptable learners.
In the end, coding isn’t just about building apps; it’s about building the mindset to rebuild yourself—one line at a time.
What I Think
So, is coding still worth learning?
Absolutely.
But maybe not for the same reasons it used to be.
Learning to code today isn’t about memorizing syntax anymore—it’s about learning how to think, structure, and communicate ideas clearly enough that even AI can understand them.
That’s what vibe coding really is—not replacing coding, but reimagining it.
It’s coding with intuition, creativity, and curiosity—guided by your vibe.
(I still really despise the name, by the way.)
But if you want to get into vibe coding and don’t know where to start, I’d suggest first learning the fundamentals of any programming language. There are countless great courses and free YouTube tutorials that are more than enough to get you started.
After a few weeks of drilling the basics, you’ll feel more comfortable diving into the world of vibe coding—and stretching those vibe coding muscles without getting overwhelmed.
I’ll be sharing some helpful resources to help you get started.
Thanks for reading!
Sources
- Gartner, 2025—Projection on Enterprise Application Development using Low-Code or No-Code Technologies
- CodeConductor.ai, 2024—No Code Statistics—Market Growth & Predictions (Updated 2025)
- Gambacorta et al., 2024—Generative AI and Labour Productivity: A Field Experiment on Coding (BIS Working Paper No. 1208)
- Google Cloud/Ryan J. Salva, 2025—State of AI-assisted Software Development (The 2025 DORA Report)
- Veracode, 2025—GenAI Code Security Report: Assessing the Security of Using LLMs for Coding
- Tandap Noel Bansikah / DEV Community, 2025—Why Programming Fundamentals Are Crucial Before Diving Into AI
- George Fitzmaurice / ITPro, 2025 — “We’re Trading Deep Understanding for Quick Fixes”: Junior Software Developers Lack Coding Skills Because of an Overreliance on AI Tools
- Harness, 2025—Report on AI-Assisted Developer Productivity and Deployment Challenges
- Mikum et al., 2014—Developing Problem-Solving Skills and Pair Programming Strategy for a Fundamental Computer Programming Course