Vibe coding is here.

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It’s fast, productive, and empowering. With the rise of AI-driven feature generation, entire vertical slices of functionality can be created in hours instead of weeks. For many organizations, this feels like a revolution—finally, a way to deliver value at the speed of imagination.

But there’s a hard truth beneath the excitement: producing good code is about much more than simply producing working code.

Good code is:

• Readable → so that the next engineer understands it.
• Testable → so that future changes don’t break it.
• Extendable → so that it can adapt to the needs of tomorrow.

To achieve this, we need principles that have guided software engineering for decades: SOLID, KISS, YAGNI, DRY. These aren’t buzzwords; they’re the difference between a codebase that thrives and one that collapses under its own weight.

The Role of Lead Engineers in the AI Era

As we move deeper into AI-assisted development, the role of senior and lead engineers becomes more important, not less.

Lead engineers aren’t just writing code—they’re guardians of the codebase. They ensure every AI-generated feature aligns with engineering best practices. They spot when something is “clever” but brittle. They protect against technical debt that future teams would otherwise drown in.

In short, they make sure vibe coding doesn’t become vibe chaos.

The Emerging Problem: The Next Generation

Here’s the challenge: what happens to the next generation of developers?

Traditionally, junior engineers learned by writing lots of code, making mistakes, and absorbing feedback during reviews. Over time, they developed an instinct for what “good code” looks like.

But in a world where AI generates much of the code, new developers may never get the same exposure. They may review code, but without knowing what “good” is, they won’t know what to look for. The pipeline of engineers capable of managing and safeguarding this new AI-driven process risks shrinking.

This is the paradox: AI accelerates delivery today but could erode the engineering skill base of tomorrow.

The Way Forward

So what do we do?

1. Keep humans in the loop – AI can generate code, but lead engineers must review, approve, and mentor.
2. Teach principles, not just syntax – New developers need to understand why we use SOLID, KISS, YAGNI, and DRY.
3. Use AI as a tutor, not just a generator – Tools should explain their decisions, not just produce output.
4. Build apprenticeship into the process – Juniors should shadow code reviews and gradually take responsibility.

If we get this right, vibe coding won’t just change how we build software—it could change who gets to participate. The risk is real, but so is the opportunity.

The future of coding isn’t just about speed. It’s about ensuring that the craft of engineering remains strong in the age of AI.

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