72 Hours to Full Pipeline: Building the AniKuku AI Animation Engine

Recently, we conducted a 72-hour intensive sprint with one goal: to transform AniKuku from a "demo-ready" prototype into a "production-ready" engine capable of running full episodes. This article reviews how we connected script parsing, asset generation, timeline editing, and automated rendering into a reusable pipeline—and the product decisions that were validated along the way.

Why the 72-Hour Stress Test?

• Proving End-to-End Viability: Brands and studios are asking: "Can we produce a consistent 2-min episode quickly?" We needed to prove that the entire workflow—not just isolated demos—is feasible.
• Validating our Tech Stack: We needed to ensure that our stack—Next.js 15, React 19, Drizzle/Postgres, OpenAI-compatible LLMs, and grsai (Nano Banana / Sora2) generation links—could work together seamlessly under pressure.
• Aligning the Team: By focusing on a single creation path, we unified product, design, engineering, and operations around a practical, shared workflow.

What We Accomplished in 72 Hours

1. Script-to-Shot Analysis: The LLM now parses raw scripts into a detailed shot list, tagging characters, scenes, and props. These shots are automatically placed onto the timeline as a "to-do" list.
2. Consistent Asset Management: Character and scene definitions are stored in Cloudflare R2. Every generated prompt, version number, and preview image is traceable, ensuring that switching styles doesn't mean losing existing progress.
3. Automated Visuals & Voiceovers: Using grsai's Nano Banana model, we can batch-generate storyboards with customizable styles. Voiceovers are generated via Text-to-Speech (TTS) and automatically aligned with the shot duration.
4. Resilient Timeline Editing: Built on React 19, our collaborative timeline flags pacing issues and duration overflows. It supports localized rendering, undos, and shot replacements to prevent "edit fatigue."
5. One-Click Rendering: Once shots are locked, Sora2 generates the final clips, merges them with audio, and outputs the result to R2 for sharing or downloading. Failed segments can be retried individually without affecting the whole project.
6. Production Infrastructure: We integrated BetterAuth (Magic Links + OAuth), Resend for emails, Stripe for payments, and Drizzle migration scripts to ensure the platform is ready for private beta testing and monetization.

The End-to-End Workflow

1. Upload Script: Automatically receive a shot list, character cards, and scene cards.