βπ Problem Statement & Strategy: Lumina
βπ Problem Statement & Strategy:
Lumina Case Study β Problem & Design Goals
The Problem:
Existing AI video generation platforms suffer from high friction and poor UX:
βOverwhelming Settings: Users are faced with dozens of technical parameters before seeing a result.
Hidden Credit Costs: Lack of upfront clarity on token and render costs.
Rigid Editing: Difficulty in tweaking or editing AI-generated clips like standard video tracks.
Design Goals:
Speed to Value: Enable users to generate their first AI video clip in under 2 minutes.
Transparent Costs: Display precise credit cost estimates upfront prior to generation
Timeline Familiarity: Interface AI video generation directly into a standard multi-track editor.
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βπ Problem Statement & Strategy: Lumina Case Study β Problem & Design Goals The Problem: Existing AI video generation platforms suffer from high friction an...
