Iterative UI Refinement for SaaS Hero Sections

The Refinement Process

Improving a baseline AI-generated hero section requires moving beyond single-prompt results toward a hybrid workflow. The author demonstrates that achieving a high-quality before-and-after visualization for a landscaping SaaS requires aligning image perspectives, manual asset cleanup, and custom shader-based transitions rather than relying on generic AI outputs.

Iterative Asset Preparation

To ensure the before-and-after images aligned perfectly for a seamless transition, the author followed these steps:

• Perspective Correction: Used iterative prompting to move the house further from the camera (from 50ft to 70ft) to ensure enough ground space for a full-width hero layout.
• Asset Standardization: Generated consistent house models in two states (new construction vs. landscaped) to ensure the geometry remained identical during the transition.
• Manual Cleanup: Exported the AI-generated images into Figma to remove backgrounds and manually align the house positions within a shared frame to prevent shifting during the reveal animation.

Implementing Reveal Effects

Rather than using basic CSS transitions, the author experimented with various shader-based reveal effects to enhance the user experience:

• Shader Selection: Tested multiple effects including pixel dissolve, diagonal swipe, and shutter, ultimately settling on a wave-based distortion effect for the most fluid transition.
• Performance Optimization: Optimized images to keep the total hero section weight around 600KB while adding subtle, CSS-based animated elements like clouds and butterflies to increase visual interest.
• A/B Testing: Emphasized that despite the aesthetic improvements, the final design must be A/B tested against the original version to verify if the added complexity actually improves conversion rates.