Dan Usedom

Generic AI tools are smart advisors. But running a live service game requires operators. Tools that understand your retention curves, your LiveOps playbooks, your patch cadence, and your players. Most off-the-shelf LLMs can't do that, and stitching together a fragmented analytics and LiveOps stack to get there is costing your team more time than it saves.

ThinkingAI spent 10 years embedded with the world's top grossing mobile studios, building the skills, workflows, and institutional knowledge that now power the Agentic Engine: a coordinated team of AI agents purpose-built for live service games. In this session, learn how to:

• Close the entire live service growth loop autonomously: detect signals in real time, decide on the right response, execute it, and verify the outcome, with your team in control at every step.
• Give your agents the full picture, connecting player behavior, user feedback, community signals, and internal knowledge so every decision is grounded in context, not just dashboards.
• Deploy on your own infrastructure, with your own models, so your player data never leaves your walls and your team stays sovereign