Coding Is Not the Job Anymore. Engineering Is.

Honestly, I've been hearing about AI every single day for the past year. And I mean every single day. Twitter, blogs, Slack channels, team meetings. It doesn't stop.

Some engineers are scared. Some just don't care. And some are using AI to do 10x of what they were doing before.

I'm in that third group. And if you're reading this, you probably are too. Or you want to be.

Here's the thing though. We are genuinely lucky to be engineers right now. We are living through something that doesn't happen often. A complete shift in how software gets built. Not a new framework. Not a new language. A fundamental change in the role itself.

And most people haven't fully realized it yet.

The Shift Nobody Talks About

Tech as we knew it until a few years ago is gone.

I don't say that lightly. I say it because I see it happening around me every single day. Senior engineers, people with 8-10 years of experience, using AI extensively. Not as a novelty. Not as a side experiment. As their primary way of working.

This isn't just a junior developer thing anymore. The best engineers I know have fully integrated AI into their workflow. They're not threatened by it. They're leveraging it. And the gap between them and engineers who haven't adopted AI is growing fast.

Every single day, that gap gets wider.

The AI-Native Team vs The Traditional Team

Let me give you a scenario.

Take two teams of five engineers each. Similar skill sets, similar experience. Equip one team with AI tools and let the other work the traditional way. Hand them the same product to build.

10 out of 10 times, the AI-equipped team comes out on top. Speed, system design, testing. Everything.

I'm not saying this theoretically. I see this playing out at my workplace every single day.

My team is an AI-native team. We ship features on a daily basis and we keep getting better at it. Sure, we're still figuring some things out. Sure, we miss some steps along the way. But we're closing those gaps. And we're closing them fast. Faster than you'd think.

Honestly, if you're a founder right now and your team is not using AI, you will be left behind. It's not a question of if. It's a question of when.

From Writing Code to Designing Systems

Recently, I was talking to a friend of mine at Razorpay. Our entire conversation revolved around one thing: how our jobs have completely shifted.

We're not writing code anymore. We're designing systems and reviewing code.

"If you've designed the system well and you know every inch of what needs to happen, the implementation is just about prompting now."

That hit me because it was exactly what I was experiencing at work.

In the last year, LLMs have gotten so much better. The quality of code they produce, the understanding of context, the ability to follow architectural patterns. It's genuinely impressive. And it's only getting better.

The job of a programmer, someone who sits and types out code line by line, is over. What's left is the job of an engineer. The one who thinks about the system. The one who designs. The one who reviews. The one who makes sure every piece fits together the way it should.

You're more of an engineer now than ever before. The curious one. The one who actually thinks.

AI Is Not a Replacement. It's a Multiplier.

Now let me be very clear about something. I'm not saying you should blindly trust Cursor or Claude Code and call it a day.

You still need to know what every line of code does. You need to know why it's written that way and not some other way. You need to know how you would optimize it if you had to. You need to understand the trade-offs, the edge cases, the failure modes.

All of that still matters. Maybe even more than before.

Because here's the thing. When AI generates code, it looks right. Most of the time, it even works right. But "works right" and "is right" are two very different things. If you don't understand the code deeply enough to catch the difference, you're shipping bugs with more confidence than ever before.

The part that's changed is the how. You don't have to type everything out character by character anymore. The mechanical act of writing code is no longer the bottleneck. Thinking is. Understanding is. Designing is.

The sooner you realize that, the better.

What My Workflow Actually Looks Like

People keep asking how I actually work with AI on a daily basis. So here's the full workflow. This is literally how features get shipped on my team right now.

1. Discuss the feature. Sit in meetings, understand what needs to be built, why it matters, and what the expected outcome is.
2. Design the system. How will it work? What components are involved? Any dependencies on other teams like data, design, or infrastructure?
3. Discuss the design with AI. I take my system design to Claude Code and talk it through. Does it catch something I missed? Can something be optimized? Is there a better approach I haven't considered?
4. Get approval from the team lead. Walk them through the design, get buy-in, and align on the approach.
5. Implement using Cursor. With a solid design in hand, the implementation becomes about clear prompting. The AI knows what to build because you know what to build.
6. Self-review every single line. Go through each line of code that was changed or newly written. Multiple times. Understand it like you wrote it yourself. Because at the end of the day, it is your code.
7. Run an AI review. Use the AI to review your code for edge cases, potential issues, and things you might have missed.
8. Filter the noise. This part is important. The AI review will flag a lot of things. Many of them will be hallucinations or non-issues that don't actually apply to your codebase. You need to know your code well enough to tell the difference. This is exactly why step 6 matters so much.
9. Create the PR, resolve comments, and ship. Put up the pull request, address review comments from your team (and there will be comments), and take the feature live.

That's it. That's the loop. Design, implement, review, ship. Every single day.

The Takeaway

The role of a software engineer has changed. Not slightly. Fundamentally.

If you're still thinking of your job as "writing code," you're already behind. The engineers who are thriving right now are the ones who've shifted their focus to designing systems, understanding trade-offs, and reviewing implementations with a critical eye.

AI handles the typing. You handle the thinking.

You don't need to call yourself a "builder" or whatever the latest buzzword is. You're an engineer. A real one. The kind that designs, questions, reviews, and ships. The kind that understands not just what the code does but why it does it that way.

The job as a programmer is over. The job as an engineer is just getting started.

And honestly, it's never been a better time to be one.