End-to-end infrastructure for training and inferencing open weight models

# Introduction - AC2 Source: [https://docs.appliedcompute.com/](https://docs.appliedcompute.com/) End\-to\-end infrastructure for training and inferencing open weight models\. Applied Compute Agent Cloud \(AC2\) is a researcher cockpit for end\-to\-end model development, inference and continual learning\. ## Onboard with your coding agent The fastest way to get started is to let your coding agent set AC2 up for you\. Paste this prompt into Claude Code, Cursor, Codex, or any coding agent: The agent installs the CLI, logs you in, wires up the AC2 MCP server, and walks you through your first project\. Prefer to run the steps yourself? Follow the[Quickstart](https://docs.appliedcompute.com/quickstart)\. ## Packages - **`ac2\.sdk`**— platform client for datasets, workloads, sessions, traces, and secrets\. - **`ac2\.runtime`**— agent framework for agents, environments, orchestrators, tasks, graders, and episodes\. - **`ac2\.tracing`**— OpenTelemetry\-based observability SDK\. Add`@traced`to any function to capture timing, inputs, outputs, and nested spans\. Exports to ClickHouse and Langfuse\. ## Choose a workflow