The term “vibe coding” gets a lot of eye rolls. It sounds like something between a TikTok trend and a parody of Silicon Valley culture. But behind the name, something real is happening — and it’s changing how software gets built.
What vibe coding actually means
Vibe coding is the practice of building software by describing what you want in natural language and letting AI tools generate the code. You guide the direction, review the output, and iterate — but you’re not writing every line by hand.
Tools like Cursor, Claude Code, and GitHub Copilot have made this practical. You can describe a feature, get working code, test it, and refine — all in a fraction of the time traditional development takes.
What it’s good for
Vibe coding shines in specific situations:
Prototyping. Going from idea to working prototype in hours instead of days. When you’re exploring whether something is even feasible, speed matters more than perfection.
Boilerplate and glue code. Setting up API routes, database schemas, form validation, auth flows — the stuff that’s necessary but not novel. AI handles this well because it’s been done millions of times before.
Learning new stacks. Working in an unfamiliar language or framework? AI can generate idiomatic code and explain patterns as you go. It’s like pair programming with someone who’s read every doc.
Internal tools. Admin panels, dashboards, scripts — things that need to work but don’t need to be works of art. Vibe coding gets them done fast.
What it’s not good for
Vibe coding has real limitations:
Complex architecture decisions. AI can generate code, but it can’t make good architectural choices across a large system. That still requires human judgment and experience.
Security-critical code. AI-generated code can introduce subtle vulnerabilities. Auth systems, payment processing, and data handling need careful human review.
Performance-sensitive paths. When every millisecond matters, you need to understand exactly what the code is doing. Generated code tends to be correct but not optimal.
Novel algorithms. If you’re building something genuinely new — not just assembling known patterns — AI is less helpful. It’s great at recombining existing solutions, not inventing new ones.
How we use it
At ThanksDev, vibe coding is part of our workflow, not our entire workflow. Here’s how it fits:
- Kick off with AI — we describe the feature or component and let AI generate a first pass
- Review and refine — we read every line, fix issues, and restructure as needed
- Test thoroughly — generated code gets the same testing rigor as hand-written code
- Optimize where it matters — for critical paths, we rewrite by hand with full understanding of what’s happening
This approach lets us move fast on the 80% that’s straightforward, and spend our human expertise on the 20% that actually needs it.
The real shift
The important thing about vibe coding isn’t the tools — it’s the mental model. Instead of thinking “I need to write code that does X,” you think “I need to describe X clearly enough that code can be generated.”
That turns out to be a different skill. It rewards clarity of thought, good problem decomposition, and the ability to evaluate code you didn’t write. Those are skills senior engineers already have — which is why vibe coding tends to make experienced developers faster, not replace them.
Want help getting started?
If your team is curious about incorporating AI-assisted development into your workflow, book a session. We help teams adopt these tools effectively — from tool selection to workflow design to hands-on pairing.