PracHub
QuestionsPremiumLearningGuidesCheatsheetNEWCoaches
|Home/ML System Design/xAI

Design agentic workflow to generate a 1-hour movie

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's ability to design agentic, multimodal ML workflows for long-form content generation, covering orchestration of multiple LLMs and tools, state and memory representations for continuity, narrative pacing, and quality/failure handling in an ML System Design context.

  • medium
  • xAI
  • ML System Design
  • Machine Learning Engineer

Design agentic workflow to generate a 1-hour movie

Company: xAI

Role: Machine Learning Engineer

Category: ML System Design

Difficulty: medium

Interview Round: Technical Screen

## Prompt You’re asked to design an **agentic workflow** (multiple LLM/tools acting as “agents” under an orchestrator) that can generate a **~60-minute movie** from a short user request (e.g., genre + logline + a few constraints). ## Requirements - **Input:** a short prompt plus optional constraints (genre, target rating, language, art style, key characters, must-include events, target length ~60 minutes). - **Output:** a full movie package: - screenplay / dialogue - storyboard or shot list - generated video clips (or scene-level renders), audio (speech, SFX, music) - final edited timeline (~60 min) - Maintain **consistency** across the whole film: - character identity (appearance, voice, personality) - world facts and timeline continuity - visual style / cinematography constraints - plot coherence (no contradictions) - Maintain good **narrative pacing / rhythm** across 60 minutes. - The system should support iterative refinement (regenerate a scene without breaking continuity). ## What to cover Describe: 1. The high-level workflow and the agents involved. 2. What state/memory representations you would use to enforce consistency. 3. How you would manage pacing and hit a target runtime. 4. Tool/model choices at each stage (LLMs, video generation, TTS, editing). 5. Quality evaluation and failure handling (automatic checks + human-in-the-loop).

Quick Answer: This question evaluates a candidate's ability to design agentic, multimodal ML workflows for long-form content generation, covering orchestration of multiple LLMs and tools, state and memory representations for continuity, narrative pacing, and quality/failure handling in an ML System Design context.

Related Interview Questions

  • Implement a trie-based tokenizer - xAI (hard)
xAI logo
xAI
Feb 11, 2026, 12:00 AM
Machine Learning Engineer
Technical Screen
ML System Design
8
0
Loading...

Prompt

You’re asked to design an agentic workflow (multiple LLM/tools acting as “agents” under an orchestrator) that can generate a ~60-minute movie from a short user request (e.g., genre + logline + a few constraints).

Requirements

  • Input: a short prompt plus optional constraints (genre, target rating, language, art style, key characters, must-include events, target length ~60 minutes).
  • Output: a full movie package:
    • screenplay / dialogue
    • storyboard or shot list
    • generated video clips (or scene-level renders), audio (speech, SFX, music)
    • final edited timeline (~60 min)
  • Maintain consistency across the whole film:
    • character identity (appearance, voice, personality)
    • world facts and timeline continuity
    • visual style / cinematography constraints
    • plot coherence (no contradictions)
  • Maintain good narrative pacing / rhythm across 60 minutes.
  • The system should support iterative refinement (regenerate a scene without breaking continuity).

What to cover

Describe:

  1. The high-level workflow and the agents involved.
  2. What state/memory representations you would use to enforce consistency.
  3. How you would manage pacing and hit a target runtime.
  4. Tool/model choices at each stage (LLMs, video generation, TTS, editing).
  5. Quality evaluation and failure handling (automatic checks + human-in-the-loop).

Solution

Show

Comments (0)

Sign in to leave a comment

Loading comments...

Browse More Questions

More ML System Design•More xAI•More Machine Learning Engineer•xAI Machine Learning Engineer•xAI ML System Design•Machine Learning Engineer ML System Design
PracHub

Master your tech interviews with 7,500+ real questions from top companies.

Product

  • Questions
  • Learning Tracks
  • Interview Guides
  • Resources
  • Premium
  • For Universities
  • Student Access

Browse

  • By Company
  • By Role
  • By Category
  • Topic Hubs
  • SQL Questions
  • Compare Platforms
  • Discord Community

Support

  • support@prachub.com
  • (916) 541-4762

Legal

  • Privacy Policy
  • Terms of Service
  • About Us

© 2026 PracHub. All rights reserved.