> For the complete documentation index, see [llms.txt](https://docs.genomeprotocol.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.genomeprotocol.com/gamefai.md). # GAMEFAI Gaming meets AI to unlock performance, automation, and new revenue. Genome introduces GameFAI, *merging AI with GameFi ,* to create smarter, more dynamic gaming ecosystems. Whether you're a developer or a player, you can utilize AI agents. As a developer you can enhance player engagement, development capabilities, and economic opportunities. As a gamer you can optimize your gameplay by analyzing your performance and refine your strategies. AI driven agents optimize gameplay by analyzing performance, refining strategies, and automating tasks like resource farming and P2E mechanics. Players can also deploy AI in tournaments, prediction markets, and competitive battles, expanding the scope of gaming competition. GameFAI introduces new revenue streams by allowing users to rent, sell, or deploy AI agents as virtual coaches, analysts, or autonomous players. This transforms skills and strategies into tradable assets, enriching the gaming economy and building on the Axie scholar system with something more tangible and sustainable. To ensure fairness, Genome integrates Trusted Execution Environments (TEE) to verify AI interactions, ensuring transparency and security in competitive settings. GameFAI enhances gaming across genres, from AI driven coaches to real-time esports predictions. By combining AI with GameFi, Genome pioneers a smarter, scalable, and sustainable future for gaming. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.genomeprotocol.com/gamefai.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.