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Software used to be linear. Developers would write code, test it, then ship it. But today, with AI in the loop, engineers are no longer just building systems — they're shaping them. Output is faster, iteration is messier, and the fundamental role of engineering is shifting.
There's an emerging, creative layer in software development that's less procedural and more collaborative. This is vibe coding, and it's become a reality for the engineering teams Digiits builds and deploys — teams that treat AI as a force multiplier rather than a threat to engineering craft.
Programming by feel
Andrej Karpathy, co-founder of OpenAI and former head of AI at Tesla, noticed this evolving trend early in 2025: "There's a new kind of coding I call 'vibe coding', where you fully give in to the vibes, embrace exponentials, and forget that the code even exists."
With tools like GitHub Copilot, Cursor, and Amazon CodeWhisperer, developers aren't always writing logic from scratch. Rather, they're suggesting direction, nudging a model, describing what they want and refining what comes back. A technologist might not know the final solution when they start — but they know the shape of it. And that's enough to get going.
This mode of working favours speed, ambiguity tolerance, and quick judgment. It also requires a totally different relationship to the codebase — one where not everything is written by hand, but everything still needs to make sense. These are classic human strengths. Vibe coding builds them.
The new development interface
Platforms like Cursor are reshaping the development interface to be intent-first, not code-first. Tools like Codeium and GitHub Copilot are building workflows where coding happens through collaborative prompting, not individual line-writing. The "prompt bar" is becoming as important as the terminal.
At Digiits, we've been tracking this shift closely across our engineering teams. The implications for how we hire, train, and deploy engineers are significant. A developer who can't prompt well — who can't articulate intent clearly enough for an AI to act on it — is increasingly limited, regardless of how fluent they are in any given language.
Our DTaaS teams are now expected to be fluent in both directions: writing precise, testable code and directing AI tools with clarity and purpose. That's the new baseline.
Why everyone thinks they can vibe code now
There's a growing belief that vibe coding is a shortcut to software creation. After all, AI can produce thousands of lines of functional code in seconds. Real-world examples like Base44 — a no-code AI startup acquired by Wix for $80 million with no traditional engineering team — are fuelling the perception that building software is suddenly easy and democratised.
But that narrative is dangerously incomplete. Vibe coding lowers the barrier to starting, not to succeeding. The illusion of accessibility obscures the deeper judgment required. AI makes it look easy. But generating a working prototype is not the same as building production-grade software.
For engineering leaders, the real risk isn't developers overtrusting AI — it's that organisations accumulate technical debt, security gaps, and misaligned systems when they mistake fast output for production-ready value.
The judgment gap: what AI can't replace
Prompting well is hard. While AI assistants can deliver functioning code in seconds, engineering leaders must now ask sharper questions:
Can your team identify hallucinated logic and broken dependencies?
Do you have the review and testing frameworks to validate AI-authored code?
Are you hiring for critical thinking, not just syntax fluency?
The rise of vibe coding is pushing enterprises to double down on QA, code review discipline, and architectural thinking — not because AI is unreliable, but because fast output demands faster evaluation.
At Digiits, we build this judgment layer into every team we deploy. Senior engineers don't just write code; they review, challenge, and validate what the AI produces. That combination — AI velocity with human judgment — is what separates a prototype from a product.
The intuition stack: what it actually requires
What makes a great vibe coder isn't the ability to prompt. It's the intuition that comes from deep engineering experience — knowing which direction to nudge, spotting when the output is subtly wrong, understanding why a particular architecture will cause problems at scale even if it looks clean now.
This intuition isn't built quickly. It comes from years of debugging real systems, shipping under real constraints, and learning the difference between code that works and code that lasts. The engineers on Digiits' teams bring this — and it's why our clients can move fast without accumulating the kind of debt that eventually stops everything.
The intuition stack isn't just a metaphor. It's a real competitive advantage, and it has to be developed deliberately.
What this means for how you hire and build teams
Vibe coding is changing the hiring brief for engineering roles. The question is no longer just "can this person write good code?" It's "can this person direct AI effectively, evaluate its output critically, and integrate it into a production codebase safely?"
That's a different kind of seniority. It's less about memorising frameworks and more about architectural intuition, system thinking, and the confidence to say when the AI is wrong.
At Digiits, we've been refining our team selection criteria around exactly these qualities. Every engineer we place through our DTaaS model is evaluated not just for technical skill but for the judgment that makes AI a force multiplier rather than a liability.