[Volume.10 AI-Enhanced Design Engineering Platform - Figma]

Figma main screen for DockMaster-SONGDO DX design

The Engineering Dilemma: From Backend Complexity to Frontend Intuition

The boundaries of traditional frontend engineering are crumbling. Moving beyond simply implementing UI, AI-driven DX engineering solutions that simultaneously revolutionize user experience and developer experience (DX) are presenting a new paradigm.

Looking back on the most challenging moments faced during the development of personal projects DockMaster-Songdo and PATH OSONG, the sense of achievement when the meticulously designed algorithms and data processing logic in the backend were completed was short-lived. The real challenge began afterward. How could this complex backend logic be transformed into a frontend interface that users could experience intuitively, as naturally as breathing?

Concerns about how users will perceive the experience are like 1-pixel optimization. Sometimes, I would adjust button positions dozens of times a day, fine-tune menu spacing, and repeatedly increase and decrease text size by 1 point. The truth is, endless contemplation remains the same even now. If users feel a delay of even 0.1 seconds when clicking, they perceive it as "slow," and if buttons are misplaced by just 2 pixels, they recognize it as "awkward." However, as a solution owner, there is a sense of mission to perform the best DX optimization at that moment.

Immediate responsiveness when clicking menus, layouts that maximize the use of limited screen space, logical button placement considering user gaze flow, text size changes that don't compromise readability when selecting from dropdown menus, intuitive hierarchical arrangement of sub-menus - all these details ultimately determine whether end users will "continue using this software or switch to a competitor's product."

This is the true value of frontend engineering, and at the center of this transformation, we examine the future direction of software development that revolutionarily solves all these concerns and repetitive tasks through Figma's AI integration strategy.

Research Overview

Company: Figma, Website: figma.com

Domain: AI-powered collaborative design platform, design-to-code automation, real-time multiplayer tools

Key Solutions: Figma AI Suite, Figma Make (AI prototyping), FigJam AI (collaborative whiteboarding), Dev Mode with MCP integration

Core Technology: Multi-modal AI (text, visual, code), real-time collaboration engine, AI-assisted design-to-production pipeline

Headquarters: San Francisco, California, USA

Founded: 2012

CEO: Dylan Field

IPO: July 31, 2025 on NYSE (Ticker: FIG) at $33/share, valued at $19.3 billion

Key Investors: Index Ventures, Greylock Partners, Kleiner Perkins, Sequoia Capital

Notable Integrations: OpenAI GPT models, Google Gemini, Adobe Creative Suite compatibility

Figma's AI-First Approach: Beyond Simple Tools to Platform

1. Multi-Modal AI Integration

Figma has integrated AI across its design platform, from small tools like auto-naming layers to Figma Make, which can turn a text prompt, image, or design frame into production-ready code. This is not a simple feature addition, but an approach that redefines the entire workflow of design-development-deployment.

Core AI Features:

• Auto Layer Naming: Context-based automatic layer naming for project structure optimization

• AI Image Generation: Instant visual creation through OpenAI DALL-E and Google Gemini integration

• Intelligent Text Generation: Real content-based mockup generation, reducing dependency on Lorem Ipsum

• Background Removal: One-click background removal to streamline image editing processes

2. Figma Make: From Prompt to Production

Figma Make is our new tool that transforms text, screenshots, and Figma designs into real interactive prototypes. This tool is completely changing the concept of traditional prototyping.

Key Differentiators:

• Rich Context Preservation: When you copy a Figma frame, we're not just bringing the image. We're giving AI the rich, structured data layers, metadata, and styling details

• Real-time Collaborative Editing: Team members can simultaneously edit and improve AI-generated prototypes

• Production-Ready Output: Direct conversion from prototypes to actual deployable code

3. Developer Experience Innovation: Dev Mode + MCP Integration

Dev Mode gives developers structured data from design files: CSS snippets, design tokens, and component details — reducing the friction of turning designs into working interfaces.

DX Innovation Points:

• Structured Handoff: Automated design-to-code conversion without manual copy-paste

• Model Code Prototypes (MCP): Coding agents with full context generating production-ready frontend code

• Cross-Modal Workflow: Integrated working environment spanning code, design, and language domains

User Convenience and Efficiency Innovations Brought by AI

1. Breaking Down Accessibility Barriers

One HR staffer with no coding background built a "Who's Who" game in two hours using data from the company's HR system. This case demonstrates the biggest change brought by Figma's AI features - the ability to build functional software without technical background.

2. Maximizing Collaborative Efficiency

Figma is multiplayer first, and tools like Figma Make and code layers are built to support real-time collaboration—even with AI. Two people can work in the same file, see each other's avatars, and co-create with an AI assistant.

3. Simultaneous Achievement of Quality and Speed

AI is going to help humans explore much faster, go much further in their ideation, but I think all the human judgement, empathy, craft, taste, is what it means to be the pilot not the copilot. Figma's "Pilot not Co-pilot" philosophy is an approach where AI increases speed while preserving human creativity and judgment.

Technical Innovation: From Infrastructure to Experience

Evaluation Framework: Human-Centered AI Quality Management

Every night, a team of contractors evaluated different versions of Figma Make — whether that was different system prompts or model choices like Claude vs. OpenAI — and log the results. Figma manages product quality through four types of AI evaluation systems:

1. Human Craft Assessment: Quality evaluation by human experts of creative work

2. Functional Validation: Verification of functional completeness of generated prototypes

3. Cross-Modal Consistency: Consistency checks between text-visual-code

4. User Experience Metrics: Performance measurement within actual user workflows

   
   

Infrastructure Innovation

Sites allows you to publish a Figma design as a public website. To do this, Figma had to bridge the gap between design tools and web publishing — developing entirely new systems that could translate design elements into functional web code. This infrastructure became the foundation for Figma Make.

Future Prospects: New Standards for DX Engineering

1. Complete Dissolution of Design-Development Boundaries

Figma's AI features are making traditional role distinctions between designers and developers meaningless. designers can often prompt interactions so precisely that engineers copy the code directly—making it start to become a handoff artifact for engineering.

2. New Definition of Prototypes

A prototype is worth $1000, and the cost of prototyping is rapidly decreasing. Prototypes have evolved from helpful supplements to the gold standard for design artifacts. Prototypes are no longer auxiliary materials but are becoming primary design deliverables.

3. AI-Native Development Culture

great design will increasingly be a key differentiator. But design isn't just pixels; it's craft: empathy, workflow understanding, and problem-solving. As technology becomes democratized, human creativity and problem-solving abilities become even more important.

Developer's Perspective: Practitioner's Viewpoint

As a solution owner responsible for data analysis and AI technology development, Figma's AI integration strategy is highly impressive. What's particularly noteworthy is not technology for technology's sake, but practical AI utilization that solves actual development workflow bottlenecks.

Figma's AI features systematically solve the challenge I experienced in DockMaster-Songdo and PATH OSONG projects of "converting backend logic into intuitive frontend experiences." While AI automatically optimizes detailed UX elements like menu responsiveness, spatial layout, and text size adjustments, it provides a structure where developers can maintain complete control over the final output.

This goes beyond simple tool evolution to become a paradigm shift that allows developers to focus more on business logic and user experience.

Conclusion: New Standards for User-Centered Software

Figma has reinterpreted the immutable law that "difficult-to-use solutions are rejected" for the AI era. They are creating an environment where AI absorbs technical complexity, allowing humans to focus on creativity and user experience.

Future successful software will not simply be feature-rich, but solutions where AI solves complexity and humans can focus on value creation. Figma is playing a pioneering role in making this future a reality.

ⓒ 2025 Intellectual property rights for this information belong to Sung-il Oh (author) and the respective companies.