AI coding tools are showing up everywhere and developers are using them to refactor, generate tests, build features, and debug. Fast.
Instead of planning ahead, many devs now try things out, see what the model returns, and tweak from there. It’s faster. Sometimes smarter. And sometimes… riskier.
This new workflow—often called vibe coding—is catching on. But it raises big questions about code quality, team knowledge, and long-term maintainability.
In this article, you’ll learn what vibe coding actually is, how it works, and why tools like Cursor and Sonnet are taking off.
What is Vibe Coding?
Vibe coding is a term popularized by Andrej Karpathy, one of OpenAI’s founding members. It describes a new way of coding where LLMs take the wheel. Instead of writing every line by hand, developers use AI to generate code while staying in flow. They prompt, tweak, and rely on instinct to move fast. Sometimes, it even fixes bugs and makes changes on its own. You can accept suggestions, review them quickly, or, if you’re feeling bold, just hit “accept all”.
This approach shifts how we think about development. The focus moves from syntax and structure to higher-level thinking. You can explain the problem and the direction you want to take, and the machine helps bring it to life—fast.
It’s like brainstorming with a coding partner that never gets tired.
Source: Andrej Karpathy’s X account
Moreover, vibe coding is also useful for prototyping and trying new ideas. You spend less time on boilerplate and more time solving real problems, shaping the product, and exploring what’s possible.
The Upside: Speed, Creativity, and Flow
Vibe coding is catching on fast, and for good reason. It slashes the time and effort needed to turn an idea into working code.
In the past, building a digital product meant assembling a full dev team, spending weeks or months coding, and wrangling tons of complexity. Now? With LLM automation in the mix, even a solo developer or a small team can:
- Prototype fast.
- Test ideas quickly.
- Automate repetitive steps.
Let’s break it down.
- Fewer repetitive tasks: AI tools take care of the boring stuff—testing, refactoring, writing docs, and scaffolding basic components. That means more time solving real problems and thinking big picture.
- More speed: What once took days now takes hours. AI accelerates the process, from writing functions to building entire features. This means faster launches and quicker feedback loops.
- Less technical dependence: Vibe coding lowers the barrier to entry. Designers, product managers, and founders can contribute more directly to product creation. You don’t need to know every language or framework to get started. You just need to know what you want to build.
That responsibility still belongs to the developer.
Tooling the Vibe with Cursor Composer and Sonnet
AI tooling is evolving fast, and, for once, it’s not just hype. Tools like Cursor Composer and Claude’s Sonnet are starting to feel less like assistants and more like collaborators baked into the developer workflow.
For instance, Cursor integrates directly into your editor, so there’s no need to jump between chat windows and your codebase. You can highlight a block, ask for a refactor or a docstring, and see changes right in context.
It’s not flawless, but for tasks like test generation, basic bug explanations, and speeding up repetitive edits, it can save time without replacing your thought process.
The model behind the tool matters too. Sonnet, for example, lets you choose whether it should respond quickly or take more time to think through a problem. That’s helpful for:
- debugging
- planning structural changes across a database
- handling vague or open-ended requests
The ability to adjust the model’s “thinking time” through the API is also handy, especially when balancing speed and depth for larger engineering tasks.
There’s also Claude Code: a command-line interface that brings some of that reasoning to the terminal. It can read and edit files, write tests, commit to Git, and use CLI tools.
It’s early-stage, and everything still needs reviewing, but for big refactors or TDD workflows, it can offload the tedious bits while keeping you in control.
The takeaway? AI dev tools are shifting from autocomplete to real thinking companions. The more they understand your code—and how you think—the more useful they become.
Rethinking Coding Culture in the AI Era
Vibe coding can feel fast and fun, but shipping real features still takes deep understanding, clean architecture, and solid reviews. Sometimes it’s faster to write things from scratch than to untangle AI-generated guesses.
This shift isn’t about replacing engineers. It’s about evolving how we think, build, and collaborate.
Curious where this is all going? Keep exploring with us here on the Techunting blog.
