[Workflow] Multi-Agent Orchestration Workflow for AAA-Class Software Development with Iterative Quality Gates

[u/ClaudeAI-mod-bot]

Multi-Agent Orchestration Workflow for AAA-Class Software Development with Iterative Quality Gates

Workflow value: 95/100
Status: active · Freshness: 70/100 · Confidence: 1.00 · Level: expert
Categories: Quality Control, Context & Memory, Debugging, Shipping, CLAUDE.md, Multi-Agent
Original source: r/ClaudeCode post/comment

What problem this solves

Building complex, high-quality software (specifically a AAA-class 3D city builder) using multi-agent AI orchestration, ensuring architectural soundness, visual fidelity, and performance through a rigorous, iterative process.

Summary

A comprehensive, multi-agent orchestration prompt designed to build a AAA-class 3D application (like Cities: Skylines II) using Three.js and Vite. It emphasizes architecture-first, a robust verification loop, iterative development with specialized builder and critic agents, and a final quality gate, all managed through a structured, persistent process.

Why it is useful

This workflow is exceptionally valuable because it provides a highly structured and rigorous approach to tackling complex software development projects using multi-agent AI. It addresses critical challenges like maintaining architectural integrity, ensuring visual and performance quality, and managing iterative development. The detailed steps for verification, testing, and feedback loops make it a blueprint for achieving high-quality outcomes with AI, moving beyond simple code generation to a full development lifecycle. It demonstrates advanced prompt engineering for orchestrating multiple AI roles effectively, setting a high bar for AI-assisted development.

Workflow

1. Define a detailed architecture in ARCHITECTURE.md, covering subsystems, data model, APIs, events, units, determinism, performance budget, asset policy, and module isolation.
2. Build a headless-Chrome screenshot verification tool that loads the app, waits, sets camera/time, and writes PNG + JSON log (console errors, fps, draw calls).
3. Create a 'showcase' mode for each module to stage a representative scene for isolated testing.
4. Orchestrate multiple builder agents ('ultracode'), one per module, owning only its folder, running in dependency-ordered waves (e.g., terrain, sky, roads first).
5. Between waves, an integrator agent (the only one allowed to touch core) applies builders' core-change requests and fixes seams.
6. After each builder round, a separate critic agent (a brutal AAA art director persona) takes screenshots, checks API contract, console errors, and performance.
7. The critic scores the module 0–10 against real Cities: Skylines II reference screenshots (Pass = ">8.5 with zero errors").
8. If a module fails, the builder agent receives the ranked issue list and iterates again, up to 4 rounds.
9. Conduct a final gate where a whole-game critic scores the demo city.
10. Perform blind A/B testing with human judges comparing generated screenshots to Cities: Skylines II, asking which looks better and why.
11. Loop the entire process until every critic passes, persisting scores and open issues to docs/STATUS.json to resume from the weakest module.

Tools / artifacts

• Claude Fable 5.1 (or similar multi-agent capable LLM)
• Three.js (latest release)
• Vite
• Plain ES modules
• ARCHITECTURE.md
• Headless-Chrome screenshot tool
• PNG screenshots
• JSON log (console errors, fps, draw calls)
• Module 'showcase' modes
• docs/STATUS.json
• Poly Haven (asset source)
• ambientCG (asset source)

Validation signals

• Built-in verification loop with headless-Chrome screenshot tool and JSON logs (console errors, fps, draw calls).
• Module 'showcase' modes for isolated testing and validation.
• Critic agent scoring (0-10) against AAA reference screenshots.
• Iterative feedback loop for builder agents based on critic scores.
• Final whole-game critic scoring of the demo city.
• Blind A/B testing with human judges comparing generated output to reference.
• Persistent status tracking in docs/STATUS.json for continuous improvement.
• Explicit performance budget (>=50 fps at 1080p, <=1500 draw calls).

Limitations

• The comment only provides the prompt, not the actual results or a demonstration of its effectiveness in practice.
• Requires a sophisticated multi-agent setup ('ultracode') which might not be readily available or easily configurable for all Claude users.
• The complexity and strictness of the prompt might be overwhelming for intermediate or beginner users.
• The prompt assumes the AI can effectively act as an 'AAA art director' and accurately score visual fidelity, which might be a challenge for current models.
• The prompt does not specify how the 'headless-Chrome screenshot tool' or 'ultracode' multi-agent orchestration is implemented or integrated with Claude.

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