Rob Davis
Wild Loop Games
Rob Davis is a Design Director and Creative Director with over 20 years of experience across AAA, mobile, PC, and console. His recent work at Wild Loop Games focuses on the intersection of AI and game design — using AI tools for prototyping games and researching approaches to runtime AI. As Studio Design Director at TreesPlease Games, he integrated AI tools into design and content pipelines, as Design Director at Take-Two he designed Lucasfilm-approved AI systems for a Star Wars title, and as Creative Director at Playniac he created games for the BBC and Channel 4, as well as indie games on Xbox and PlayStation. Rob has directed gameplay on titles ranging from Star Wars: Hunters to the award-winning Longleaf Valley, founded indie studio Playniac, and has been a BAFTA Games Awards juror and top-rated speaker at GDC. He lives in London.
Rob Davis is speaking at the following session/s
AI Wants to Play: A Game Designer’s Guide to AI in Every Stage of Development
The latest wave of AI is reshaping game development — but what actually works in practice? This talk is a hands-on tour through the stages where AI can help, from initial prototyping to runtime gameplay, drawn from the speaker's recent work as a Studio Design Director owning the AI roadmap and a Creative Director using AI to prototype and ship games.
We start with AI as a design tool. Using platforms like Lovable, Claude, and Gemini, the speaker prototyped a suite of games in weeks rather than months — rapidly iterating on everything from mechanics to UI. We'll cover how to get the best from these tools when used together, and provide an honest comparison of AI tools that actually matter to game teams. We'll then dig into a structured methodology for AI-assisted development — demonstrated on a live project — that prevents common pitfalls such as hallucination and context drift.
Next, we look at AI in the game itself. A custom card game system — inspired by DeepMind's Agent57 — trains a neural network to master multiple card games using universal strategic features; NPCs with generated personas that affect how they respond to player actions; and a game that misuses AI as a core gameplay mechanic.
We also examine some shipped games that use AI in interesting ways, and the design issues they faced. Every example comes with honest results — what worked, what failed, and what's worth your time. Attendees leave with a practical framework for adopting AI in their own studios.
Session Takeaway
- A practical decision framework for choosing the right AI tool and techniques at every stage of development — from prototyping with Lovable and Claude, to choosing between RL, LLMs, and heuristics for your runtime AI.
- How to use AI to radically accelerate game prototyping — with an honest comparison of tools (Lovable, Claude Desktop, Claude Code, Gemini), real case studies showing what each is best at and how they can work together, and a reliable development framework that is transferable to any tool.
- How a single lightweight AI model can learn to play multiple games — a concrete architecture that's smaller and faster than brute-force approaches, including the evolution through different RL techniques and the practical lessons from training failures.
- Design principles for AIs that players actually enjoy — drawn from shipped games and the speaker's own prototypes with clear guidance on what's ready for production, what's experimental, and what's still hype.
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