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Don't worship AI, work with it


Artificial Intelligence is no longer the future — it’s here, and it's reshaping how we think, work, and build. But for many people, especially those without a background in coding, AI can feel intimidating. Here's the good news: you don’t need to be a software developer to use AI tools like ChatGPT.

In fact, if you understand problems and have ideas — AI can be your most powerful partner.

LLMs: The Mind That Has Read Everything

Imagine this: you’ve studied 10 books on a topic. Your friend has studied 30. Clearly, your friend might know a bit more.

Now imagine a model that has read millions of books, research papers, and internet pages across every field imaginable — from quantum mechanics to philosophy to architecture to car repair manuals. That’s what a large language model (LLM) like ChatGPT has been trained on.

This is why it can answer questions, generate code, write summaries, translate languages, simulate conversations, and even explain tough engineering concepts in simple terms.

But don’t get carried away.
LLMs are not knowledge bases.
They are statistical models of knowledge bases — built on probabilities.

Which means: they predict likely answers based on the patterns they’ve seen during training — not based on truth.
So yes, there’s always a probability of the output being wrong.

But That Shouldn’t Stop You

Even with that caveat, AI is immensely useful when used wisely.

Here are some examples — straight from my own workflow:

  • I don’t know how to code fluently, but I’ve written Python scripts by prompting AI — from sensor simulations to GUI dashboards.
  • I can integrate domain knowledge: ask questions about TFETs and automotive electronics together — and AI helps make the connection.
  • I can get technical explanations simplified for non-technical audiences, or translate complex documentation into email-ready summaries.

This is intelligence enhancement — not replacement.
It’s like having a super assistant who is always available and rarely tired.

Don’t Forget the Human Factor

AI can suggest, draft, explain — but it can’t build trust. It can’t manage teams. It can’t negotiate with stakeholders or lead a cross-functional workshop.

In large-scale engineering — whether in hardware, automotive systems, or software design — you need human coordination, empathy, and judgment. AI has none of that.

So don’t outsource responsibility. AI is a sharp mind, not a wise one. It can assist, but not decide.

Cognitive Offload Isn’t Always Bad

There’s a concern that too much AI will lead to a cognitive decline — that we’ll forget how to think.
But think back: our grandparents calculated everything on pen and paper. Then came calculators. Then Excel. Then cloud tools.

Did we become dumber?
No — we became faster. We shifted our focus to higher-order thinking.

AI is the next step.
It offloads repetitive tasks, so your brain can focus on design, strategy, integration, and human impact.

AI Is an Axe, Not a Vehicle

Think of yourself in a forest. AI is your axe. It helps you cut paths through dense undergrowth. But you still need to walk. The axe won’t carry you — that’s your job.

If you expect AI to “take you somewhere” while you do nothing, you’ll stay stuck.
But if you walk — even slowly — the axe will help you move faster.

AI helps. You lead.

So What Does AI Really Mean for You?

It means your mental bandwidth is now freed.
You don’t have to get stuck writing syntax from scratch. You don’t have to remember every detail of socket programming or VHDL modules.
You can focus on your ideas — the ones you’ve been carrying for years but never got time to explore.

If you can visualize a problem and imagine a rough solution, tools like AI will help you shape it into a POC — a Proof of Concept.

And maybe that’s the most meaningful definition of Artificial Intelligence today:

A tool that gives your natural intelligence more room to breathe, build, and break boundaries.

From the Engineer’s Desk

As an engineer, I use AI not because I want to replace my skills — but because I want to amplify them.
I still review every output. I still decide the final logic.
But now, I do it faster, better, and with more clarity.

In a world full of complex systems, tight timelines, and multi-domain collaboration — AI helps me stay in the game and push further.

Because in the end, it’s not the tool that defines the engineer — it’s how the engineer uses the tool.


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