gpt-taste

Automate UX/UI design and GSAP motion engineering by applying a deterministic pipeline that generates hero architectures, gapless Bento grids, and scroll effects for marketing sites and portfolios. This yields unique, premium layouts while preserving system parity across pages.

Generate unique Bento grid layouts using Python-driven deterministic randomness. This approach ensures repeatable, asset-rich outputs for each build, producing varied dense grids while maintaining a cohesive design system across product stories.

This design pipeline supports editorial pages and product stories, not just hero sections. It generates varied, asset-rich layouts and integrates advanced GSAP motion paradigms tailored for marketing sites, portfolios, and editorial content.

No specific dependencies are required to build GSAP-driven scroll effects and ultra-wide hero sections. The pipeline encapsulates the structured workflow and motion paradigms internally, enabling engineers to break default templates without external plugins.

Deterministic randomness matters for frontend design automation because it guarantees unique, repeatable outputs for each build. This allows teams to generate varied layouts and asset-driven compositions while preserving a cohesive design system.

Start building a hero-driven page by following the provided design_plan instructions and utilizing the randomization seeds. This process renders a complete layout with ultra-wide hero sections and GSAP-driven interactions automatically.