From Junior to Senior in the Age of AI: The Right Way to Level Up

A conversation on LinkedIn caught my attention recently. Someone asked a developer about her AI coding setup.

"None," she said. "I don't think I'm at the level yet where I can let a model generate 1k lines of code per iteration, review them and be confident I'm not introducing a mess at a massive scale. I'll use it when I have more experience building software."

The response resonated with a lot of people. "We need more developers like her and less AI slop," they said.

I understand the concern. But I think this sets the bar in the wrong place.

The Real Problem Isn't AI—It's How We Use It

Here's the thing: you shouldn't trust AI to dump 1,000 lines of code. Agreed. But you also shouldn't trust 1,000 lines from a human without understanding them either.

The problem isn't the source of the code. The problem is accepting code you don't understand.

Waiting until you're "experienced enough" to use AI feels backwards. Used correctly, AI is a tool for becoming experienced—not for skipping the work.

The Pattern That Actually Works

The useful pattern isn't "generate large, ship fast." It's:

• Generate small pieces — A single function. One component. A few lines.
• Interrogate them — What does this do? Why this approach?
• Ask why — Why a Map instead of an object? Why this error handling pattern?
• Ask for rewrites — "Show me this without the ternary." "What's the imperative version?"
• Ask for simpler versions — Complexity is easy. Simplicity is hard. Make the AI work for it.

AI can explain code—including human-written code—better than most humans have time to. That legacy codebase nobody wants to touch? AI will walk you through it line by line, patiently, at 2 AM, without sighing.

What Seniors Actually Do

Here's what separates a senior developer from a junior:

• Juniors write code. Seniors know when not to.
• Juniors solve the problem in front of them. Seniors ask if it's the right problem.
• Juniors trust code that works. Seniors ask why it works and what happens when it doesn't.

None of these skills require you to type every character yourself. They require judgment. And judgment comes from seeing many approaches, understanding trade-offs, and making decisions.

AI accelerates the "seeing many approaches" part. The judgment is still yours to build.

The Danger of "Waiting Until You're Ready"

There's a version of being careful that becomes an excuse. "I'll use AI when I'm senior" often becomes "I'll learn Kubernetes when I have time" or "I'll write tests when the codebase is cleaner."

The truth is: you learn by doing, not by waiting.

The developers who will thrive aren't the ones who avoid AI. They're the ones who develop a rigorous relationship with it:

• Question everything it produces
• Understand before shipping
• Use it to explore, not to avoid learning
• Treat it as a teaching assistant, not an oracle

How We Approach This at vensas

At vensas, we believe in hands-on learning. Our founders still write code daily. Our trainers are practicing developers, not theorists. When we work with teams—whether through code reviews, training, or embedded development—we focus on building understanding, not just delivering features.

This philosophy extends to how we think about AI:

In Code Reviews, we don't just identify problems—we explain the why. The same approach works with AI-generated code. Don't just run it. Understand it. Ask: would this pass review? If not, why?

In Training, we emphasize Clean Code, refactoring, and testing. These skills become more important with AI, not less. When you can generate code quickly, knowing what good code looks like is the differentiator.

In Architecture Consulting, we help teams make technology decisions they understand. AI can suggest patterns, but knowing which pattern fits your context requires judgment that only comes from practice and mentorship.

We've seen junior developers grow faster when they use AI as a learning accelerant—asking it to explain concepts, compare approaches, and simplify solutions. We've also seen developers stall when they use it as a crutch, generating code they can't debug when it breaks.

The tool isn't the variable. The approach is.

A Challenge for Junior Developers

If you're early in your career, here's my challenge to you:

Don't avoid AI. Don't blindly trust it either.

Instead:

• Generate 10 lines, not 1,000. Small enough to truly understand.
• Ask it to explain. "Why did you use recursion here?" "What's the time complexity?"
• Ask for alternatives. "Show me a different way." "What's the trade-off?"
• Compare to production code. How does this differ from what your team writes?
• Break it. Give it edge cases. See where it fails. That's where your understanding grows.

A Challenge for Senior Developers

If you're mentoring others, don't dismiss AI as a shortcut for the lazy. Help your junior developers use it correctly:

• Review AI-generated code together. Make it a teaching moment.
• Ask them to explain what the AI produced. Understanding beats avoidance.
• Show them how to interrogate suggestions. Model the skepticism.

The juniors who learn to work with AI thoughtfully will become seniors faster. The ones who avoid it entirely will eventually face a codebase full of AI-generated code anyway—and be less prepared to navigate it.

The Bottom Line

Her caution isn't wrong. Trusting AI with 1,000-line dumps is a recipe for disaster.

But the answer isn't abstinence. It's discipline.

Small pieces. Deep questions. Genuine understanding.

That's how juniors become seniors—with or without AI. AI just makes the iteration loops faster.

At vensas, we help developers grow through code reviews, training, and real project experience. Whether you're using AI or not, the fundamentals remain: understand what you build, question what you ship, and never stop learning.

The age of AI doesn't change what makes a great developer. It just raises the stakes for getting there deliberately.

Need Support?

Want to accelerate your team's growth while building real AI fluency? We offer training programs that focus on the fundamentals—Clean Code, architecture, testing—that become even more critical in the AI age. Get in touch and let's talk about how we can help your developers level up.