How Design Systems will Survive the Vibe Coding Era

With vibe coding on the rise, design systems struggle to be followed. How can consistency be maintained? In this article, I will share my insights and experience in tackling this contemporary challenge.

What is a design system

I assume most readers are familiar with the concept, but let’s quickly recap: A design system is a centralized repository of documentation and assets intended to ensure consistency and promote an optimal user experience across all digital products.Share branding guidelinesLogos, tone of voice, typography, colors, etc.Define UI guidelinesColors, iconography, spacing, typography, UX recommendations, Etc.Makes available live assetsComponents, themes, screen templates, icons, etc.

What is Vibe Coding

The term “vibe coding” was popularized by OpenAI founder Andrej Karpathy in February 2025 on the social media platform X, with the following post:https://x.com/karpathy/status/1886192184808149383Today,vibe codingis understood as codegenerated by AIthrough user prompts and interactions. In short, it represents thefuture of programming: instructing an AI to generate functional code based on our guidelines.

The Current Stage of Vibe Coding

While we can assume that vibe coding is still in the early stages of adoption, nearly everyone has either tried it or is using it already.

However, the speed of technological adoption is faster than ever. Consider that ChatGPT — the tool that first introduced easy, widespread AI interaction through prompting — is only three years old!

Therefore, being at the “beginning” of vibe coding adoption does not carry the same meaning in the digital realm as it once did.

Key Usage Data

Based on recent reports from Gartner and various technology news, the adoption of vibe coding is accelerating rapidly:

87% of the 500 largest companies are currently using at least one vibe coding platform;
Teams report releasing sprints 29% faster and achieving a 42% improvement in code quality;
63% of active developers utilize at least one vibe coding tool daily;
48% of developers with over five years of experience are now replacing more than 50% of their repetitive tasks with AI;
77% of freelancers consider vibe coding a core competitive tool;
Junior developers report being 70% faster in delivering their work and experiencing 40% fewer code errors.

The challenge

Given that vibe coding is rapidly becoming our primary way of developing software, how do we ensure that design system guidelines are consistently followed? I first encountered this conflict while building a landing page for a Hi Interactive product. I was astounded: I built an incredible, fully responsive landing page with rich interactive animations and content in just four hours. However, when I attempted to enforce our brand standards and incorporate specific code patterns, I quickly became frustrated. I realized that adhering to our guidelines was impossible without developing the page almost entirely from scratch. Since that day, I’ve been dedicated to solving this problem. I have focused my daily routine on this Vibe coding challenge, testing multiple AI agents, implementing solutions to identify and close the gaps, and ultimately developing a complete solution for our clients.

Let’s define the key points for code generation:

Need to follow are UI guidelines (design);
Follow our name and code conventions;
Include our UI libraries;
Only use our components;
Generate HTML the correct way;
Ensure accessibility.

These key requirements must be achieved without sacrificing the core benefits of the vibe coding experience: speed, live testing, and agility for change.

How to solve it

Integrating the Design System into the AI Agent

The vibe coding agent must be explicitly trained on the design system guidelines.
This integration ensures that the code the agent produces accounts for all visual and functional guidelines, guaranteeing that the output is compliant with your defined rules from the very first line.

How integrate

The approach depends on LLM (Claude, Gemini, OpenAI, etc.), but the core process is identical.

Establish a Robust, Live Style Guide
It’s crucial to have a well-maintained, live documentation for your UI components and style guide within your design system.
In my experience, this is the hardest, yet most critical, step. Everything contained within this live style guide will be used by the AI agent to generate code. While this process guarantees the design system is 100% followed, you must understand the caveat: any mistakes or inconsistencies in your documentation will be instantly replicated in the generated code.
Incorporating the Data Source
This can be accomplished in several ways, but the simplest method is to share the live style guide URLs with your AI agent.
You must then instruct the agent to use this documentation as the foundation and base rules for all code generation.
Testing and Refinement
Like any software development process, this integration requires a rigorous testing phase. The goal here is to make adjustments and fine-tune how the AI-generated code conforms to our standards.
I can guarantee that your initial tests will reveal numerous mistakes or missing guidelines. These issues are invariably tied back to the quality of your first step — the live style guide. The most challenging task isn’t the AI integration itself, but rather having perfectly compliant documentation to teach the AI everything it needs to generate the correct code.
At Hi Interactive, we are experts in this process.
Maintenance and Continuous Improvement
To ensure vibe coding remains both efficient and scalable, it’s essential to establish a continuous feedback loop with the delivery team. This allows you to quickly address errors and implement necessary improvements.
Your agent will need to be updated in the following common scenarios:
– Core Technology Updates: When underlying technology versions change (e.g., framework updates), these must be immediately incorporated into the AI agent’s guidelines.
– Design System Evolution: Integrate new components, patterns, or updated guidelines as soon as they are finalized in the design system.
– Feedback-Driven Refinements: Implement improvements based directly on the valuable input and insights received from the development and delivery teams.
Optional: Live Preview Capability
While its necessity depends on the specific task the AI agent is solving, a custom live preview application is crucial for effective prototyping. This allows you to instantly see and test the generated output.
To support this, we must develop a dedicated user interface (UI). This interface should allow prompting requirements, validate the AI’s results, and iteratively make changes and retest until the desired outcome is achieved.