Production-Quality Experiences in Days with AI

PROBLEM DETAILS

Why traditional approaches failed

The technical complexity alone—multiple hero videos, performance optimization, contact forms with CAPTCHA and email integration—typically requires specialist developers. I was working solo with 3 days.

APPROACH DETAILS

Four strategic design decisions

This mental model changed everything. I wasn't outsourcing design execution—I was collaborating with a partner who could instantly show me whether my ideas worked.

Bridging the Content Gap with Generative Video

A cinematic site with no work to show is a hollow promise. To solve this, I replaced static images with a series of high-fidelity background videos. Since the studio was just starting, I generated all of these visuals using Veo 3.1, Google's latest generative video model. This allowed me to:

• •Establish a "high-budget" cinematic aesthetic from day one.
• •Maintain consistent lighting, color grading, and mood across all assets.
• •Show what the studio is *capable of* producing, rather than just what they had already finished.

DESIGN PROCESS

Four iterations from concept to polish

VISUAL DESIGN SYSTEM

Motion as brand identity

Motion carries meaning. Each animation element references filmmaking craft:

Typography Hierarchy

Typography follows film credit conventions:

• •Display: Custom "cinematic-text" class—tight tracking, massive scale, high contrast
• •Body: Light weight (300), generous line-height (1.8), maximum readability
• •Labels: All-caps, extra-wide tracking, classic credit aesthetic

Color Palette

Restrained palette maximizes impact. The red accent appears sparingly—buttons, progress indicators, hover states—which amplifies its impact when used.

Human + AI Collaboration

A new model for design execution

What This Eliminated

• •"Can we build this?" negotiations — AI shows feasibility immediately
• •Multi-day review cycles — Iterations happen in minutes
• •Technical compromises — AI knows current best practices
• •Handoff documentation — No handoff needed
• •Developer availability delays — AI is always available

What This Preserved

The workflow change didn't eliminate design thinking—it accelerated its application:

• •I still decided what "credibility" should look like
• •I still chose dark + red for cinematic mood
• •I still designed the motion language
• •I still quality-controlled every pixel
• •I still made taste decisions AI couldn't make

AI eliminated latency. Design judgment remained human.

Final Solution

Production-quality, cinematic website

A complete, functional website featuring:

01

Video-First Hero

4 sequential background videos with automatic crossfade transitions, Mux CDN integration for adaptive bitrate streaming, 40% opacity with gradient overlays, graceful fallback to local files.

02

Scroll-Driven Narrative Structure

Five distinct "scenes" with snap scrolling: Hero, Social, Featured Film, Mission, Contact—each crafted as a story beat.

03

Interactive Motion System

Custom crosshair cursor with spring physics (desktop only), floating geometric crosses that drift and pulse, scroll progress indicator filling as user navigates, section entry animations with staggered reveals.

04

Functional Contact System

Cloudflare Turnstile CAPTCHA, Resend email integration, comprehensive state handling (idle, loading, success, error), auto-dismiss success after 5 seconds.

Outcome & Impact

Validated AI-native workflow at production quality

Strategic Insights

• •Validated AI-native workflow: Demonstrated that AI can maintain design quality while compressing timelines 10×
• •Challenged designer-developer separation: Designers who specify precisely can own full implementation
• •Established new craft standards: Quality isn't about time—it's about decisions, taste, and iteration speed
• •Proved AI as force multiplier: Design thinking stayed human; AI accelerated execution

Personal Growth

• •Expanded technical vocabulary: Learned to specify at implementation level, not just visual level
• •New collaboration model: AI as thought partner, not automation tool
• •Confidence in rapid execution: Can now prototype and validate in hours, not weeks

Key Lessons

What this project taught me

01

AI doesn't eliminate design thinking—it eliminates design-to-code latency

The project still required strategic problem framing, visual design decisions, interaction design, and quality control. What AI eliminated: the days/weeks between having an idea and seeing it work.

02

Specificity unlocks AI capability

Vague prompts generate generic output. Specific requirements unlock sophisticated solutions.

// Ineffective
"Make the contact form work"

// Effective
"Contact form needs: Turnstile CAPTCHA, Resend email integration, 
success state with green checkmark and 5-second auto-dismiss, 
error state showing specific error message in red alert, 
loading state with disabled submit button and spinner."

03

AI excels at implementation, not strategy

AI could implement any interaction I specified. But it couldn't decide what brand identity should feel like, what hierarchy serves the narrative, what motion language conveys filmmaking craft, or what technical complexity is worth the UX benefit. Those decisions required design judgment—the core of staff designer craft.

04

Rapid iteration enables higher quality, not lower

Traditional workflow: Make all decisions upfront (because iteration is expensive). AI workflow: Make decision → see result → refine → repeat. I refined spacing, motion timing, color opacity, and responsive breakpoints 10× more than typical projects. Higher iteration count = higher quality.

05

Constraints reveal opportunities

Without the 3-day deadline, I might have followed traditional process. The constraint forced experimentation with a workflow that proved more effective than traditional approaches. Constraints aren't obstacles—they're catalysts for innovation.

REFLECTIONS

This project changed how I think about craft

Excellence isn't about time spent—it's about decisions made. A 3-day project can exhibit higher craft than a 3-month project if the decision-making is better and iteration is faster.

On Tools: AI isn't replacing designers. It's giving designers superpowers. The designers who thrive will be those who can precisely specify what they want and relentlessly iterate toward quality.

On Collaboration: The designer-developer handoff may become optional for many projects. Not because developers aren't valuable, but because the gap between "what I imagine" and "what I can build" is narrowing.

On Speed: Fast isn't the enemy of good. Fast iteration enables good. The ability to try, evaluate, and refine in minutes instead of days changes what's possible.

Technical Appendix

Stack & Implementation

Key Implementation Patterns

Spring-Based Cursor Tracking

const mouseX = useMotionValue(0)
const mouseY = useMotionValue(0)
const springConfig = { damping: 25, stiffness: 150 }
const cursorX = useSpring(mouseX, springConfig)
const cursorY = useSpring(mouseY, springConfig)

Sequential Video Transitions

const handleVideoEnd = () => {
  setCurrentVideo((prev) => (prev + 1) % heroVideos.length)
}

Mux with Local Fallback

const heroVideos = [
  { muxId: MUX_VIDEOS.heroBg1, fallback: '/videos/hero-bg-1.mp4' },
  // ... graceful degradation pattern
]