I didn't expect this website to exist today. I opened Gemini just to test a few UI ideas, and thirty minutes later… I had a full design, live components, a working MVP, and a direction for the entire project. But this speed comes with a question every developer must now answer.
That used to take me hours — sometimes days — of tweaking margins, fine-tuning animations, and obsessing over tiny imperfections only developers notice. Back then you built everything by hand, line by line — with a lot of help from Stack Overflow and Reddit — and whatever you spent hours coding became the foundation you were stuck with.
This experience made me reflect on how dramatically the role of a developer has changed.
The 30-Minute Build
I told Gemini what I wanted: a clean layout, bold typography, dark mode, a progress bar, and a simple hero section. It generated production-ready HTML, Tailwind classes, semantic meta tags, animations, and even micro-interactions.
Normally, this process would involve:
- choosing a layout
- adjusting responsiveness
- building reusable components
- cleaning up spacing and colors
- testing UI states
- writing documentation
Instead, I spent those minutes refining ideas rather than fixing CSS.
This is the new reality: developers don't build from scratch anymore — they direct.
Back When We Built Everything Ourselves
Ten years ago, you had to know how everything worked:
- raw JavaScript, maybe jQuery
- DOM APIs
- floats, clearfixes, and centering divs
- manually writing UI logic
- tinkering with webpack configs
- debugging race conditions
- writing APIs from scratch
It was painful, but it forced you to understand software deeply. You learned why frameworks existed, not just how to use them. You learned architecture, not just components. You learned the constraints before tools abstracted them away.
That era shaped holistic developers — people who could jump between the front-end, back-end, and infrastructure because they had touched everything the hard way.
Today We're Becoming Prompt Developers
The new generation is incredibly fast. They can build an MVP in an evening. They can deploy full-stack apps without understanding half the stack.
But here's the trade-off:
- You can build more, but understand less.
- You can generate code, but not always debug it.
- You can ship quickly, but architecture becomes an afterthought.
- You meet deadlines, but you're not necessarily a programmer.
This is where the term "vibe coders" comes from — and yes, many of them are working at reputable companies. It's not inherently bad, but without fundamentals, it's dangerous for long-term growth.
A modern developer must know how to:
- translate ideas into prompts
- evaluate and correct AI-generated code
- understand constraints without digging into internals every time
- think at a systems level
- guide the AI instead of handcrafting everything
LLMs Didn't Replace Programmers — They Changed What Programming Even Means
When everything becomes automatable, value shifts toward:
- product thinking
- UX intuition
- problem framing
- architectural decisions
- knowing what to build, not just how
LLMs made coding easy, but they made thinking more valuable and much rarer. If your idea is unclear, an AI will give you a polished—but still unclear—version of it. You lose the struggle, the mistakes, the iterations that shape your creativity.
And here's the honest tradeoff I've been wrestling with:
LLMs make you incredibly productive in the short term, but if you depend on them too heavily, you risk weakening the same fundamentals that make you a strong engineer long-term. It's easy to become fast but shallow. You ship more, but you understand less. You deliver features quickly, but you stop building the intuition that comes from wrestling with real problems yourself.
At the same time, you don't have a choice anymore — not if you want to stay relevant. Companies expect you to move at AI-accelerated speed. Deadlines assume you're using LLMs. The industry has silently raised the baseline, and if you try to work without these tools, you simply fall behind.
So now the question isn't "Should you use LLMs?" It's "How do you use them without letting them hollow you out?"
This is the balance modern developers must navigate: use AI enough to stay fast, but not so much that you stop growing.
The Future: Productivity vs Long-Term Skill Decay
Here's the honest conflict: LLMs make you extremely productive — productive enough to meet modern deadlines. But there's a cost: if you never understand the layers beneath, your internal skill structure weakens over time.
Still, refusing to use LLMs is not an option. You cannot match the new speed of software development without them. Teams expect faster delivery, tighter iteration cycles, and rapid prototyping.
To stay relevant, you must use AI — and to stay valuable, you must keep your fundamentals.
Final Thoughts
Building this site in 30 minutes wasn't just fast — it was a wake-up call. We're entering an era where iteration is instant, ideas move directly from mind to browser, and programming becomes more about creative direction than raw typing.
If you embrace it, you become unstoppable. If you resist it, you fall behind.