> For the complete documentation index, see [llms.txt](https://gameterminal.gitbook.io/gameterminal-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gameterminal.gitbook.io/gameterminal-docs/agentic-infrastructure/agent-to-inference-loop.md). # Agent-to-Inference Loop ## Autonomous Development Loop GT Protocol enables autonomous agents to execute complete game development workflows through a continuous orchestration loop. Rather than performing isolated inference requests, agents collaborate across planning, generation, evaluation, refinement, and deployment while maintaining a shared execution context throughout the lifecycle. A standard execution workflow within GT Protocol follows the sequence below: ``` Creator submits prompt ↓ AI Orchestration Engine analyses intent ↓ Workflow is decomposed into specialised tasks ↓ Tasks are assigned to autonomous agents ↓ Agents consume GT Protocol AI services ↓ Creative assets, gameplay systems, and code are generated ↓ Evaluation & Critique Agents validate quality ↓ If required, selective regeneration is triggered ↓ Production-ready game is published ↓ Execution history, asset metadata, and agent reputation are updated ↓ Workflow continues for future iterations ``` Unlike conventional AI pipelines that terminate after producing a single response, GT Protocol operates as a continuous execution system. Every generation cycle contributes additional context, reusable assets, execution history, and collaborative knowledge, enabling agents to progressively improve game quality while reducing redundant computation. Throughout the workflow, orchestration, agent collaboration, creative generation, asset management, publishing, and settlement remain connected through GT Protocol. Every execution is traceable, reusable, and composable, enabling autonomous development pipelines that can continuously evolve alongside creators and future AI agents. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://gameterminal.gitbook.io/gameterminal-docs/agentic-infrastructure/agent-to-inference-loop.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.