Case Study: 7-Agent Game Development Team

The challenge

An indie game developer needed a team of AI specialists — not one generic chatbot, but seven coordinated agents covering the full pipeline from design documents to Godot prototyping. Each agent needed domain knowledge deep enough to make expert-level decisions and give expert-level feedback, not generic advice. The agents also had to work together: handoffs between GDD Writer and Mechanics Designer, between Mechanics Designer and Balance Simulator, between Godot Developer and Juice Designer.

The approach

Each of the 7 agents was built individually through our 9-phase methodology:

Research

Domain knowledge from established literature

Fullerton, Burgun, Schell, Nystrom — extracted from primary sources, not paraphrased from memory. 619+ research findings logged.
Synthesis

Cross-referencing all sources

Caught 4 errors in initial specs and filled 7 critical knowledge gaps. Sources do not always agree — synthesis resolves contradictions explicitly.
Playbooks

Step-by-step decision procedures

Each agent received playbooks for its core workflows — structured decision trees, not freestyle instructions. Agents with playbooks score ~17% higher on structured tasks.
Testing

12 tests per agent

Smoke tests, adversarial tests, edge cases. If an agent passes the adversarial tests without breaking identity — it's ready. 84/84 tests passed across all 7 agents.

The team

Agent	Domain
GDD Writer	Game design documents (Fullerton + Burgun frameworks)
Mechanics Designer	Formal mechanics analysis and design
Balance Simulator	Numerical balance modeling (damage, economy, progression)
Godot Developer	Godot 4.x prototyping with pattern-based architecture
Playtester	Evidence-based gameplay problem investigation
Juice Designer	Game feel consulting (screen shake, ADSR, audio feedback)
Game Architect	System architecture (6-layer patterns, SOLID for Godot)

All 7 agents deploy via .cursorrules in Cursor IDE with file-based handoffs between them.

The results

Metric	Value
Agents delivered	7
Deliverable files	81
Lines of structured content	~16,400
Research findings integrated	619+
Uncertainties tracked and resolved	667
Tests passed	84 / 84
Personality drift	0

Every uncertainty was logged and resolved — 667 doubts tracked across the project. Every claim traces to a verified source — 619+ research findings, not LLM-generated knowledge.

The GDD Writer alone caught 4 errors in its original spec during the synthesis phase. Without the cross-referencing step, those errors would have propagated into all downstream agents.

Want similar results?

We're accepting 5 agents for free training. Tell us about yourself and what you want to learn.

Apply for free training