Runway ML for AI-powered web prototypes
Manage episode 507188534 series 3634769
Andrés Díaz에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Andrés Díaz 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Summary: - The episode introduces Runway ML as a tool to accelerate AI-powered web prototyping while prioritizing user-centered design. - It explains how Runway ML can generate and edit visuals (hero images, icons, short videos) from clear prompts, helping even small teams or freelancers produce polished assets quickly. - To get started, define your prototype idea (site type, tone, colors, audience) and craft asset prompts. Example prompts cover a hero image, icons, and a short header video. - If hosting is needed, the episode uses Hostinger and points to a link in the description. - After generating assets, integrate them into the prototype with recommended export sizes (e.g., 1200x630 for hero, 600x600 for icons) to maintain a coherent look and professional feel. - Runway ML is evolving with more models and tools (text-to-video, style-controlled editing, refinement tools) to speed iteration and allow real-time identity variations without starting from scratch. - Practical approach: create a small set of prompts and variations so you have ready options for headers, features, testimonials, and CTAs for client presentations. - AI-based UI experiments become easier without heavy coding; generate images for mockups, then tweak typography, styles, and interactions in your editor. Decide what to automate with AI (backgrounds, icons, animations). - The host prompts reflection on comfort with AI-generated assets, the trade-off between bespoke look and stock imagery, and how to combine Runway ML with other prototyping tools. - A note on narrative coherence: AI can generate thematically linked visuals to tell your product’s story, while licensing and usage rights should be considered since ownership of outputs for commercial use is being clarified. - A fast prototyping flow: define objective for each asset, generate 3–5 variants, pick the best fit, test small variations in size/color/composition, then export and integrate. Consider mobile vs desktop variants. - Keep UX fast by optimizing assets (e.g., webp images, compressed videos) and organizing assets with Runway dashboards. There’s curiosity about a future template of prompts for an AI-powered ecommerce prototype. - Runway ML is accessible to freelancers and small teams, not just big studios, enabling rapid image generation, video editing, and creative control. - Closing takeaway: use a practical action plan—define, generate, integrate, test, adjust—and consider which AI prototype to pursue first and which asset to prioritize to validate the concept. The host invites feedback and further engagement. Remeber you can contact me at [email protected]
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45 에피소드