> ## Documentation Index
> Fetch the complete documentation index at: https://docs.trymonte.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Your first loop on a laptop, no GPU needed

Off the GPU box, every Run mocks: real CLI, real Ledger, fake scores. That makes a laptop the safe place to learn the loop. You need Python 3.12+, uv, and a clone of `monte-nemo-platform`.

<Steps>
  <Step title="Install dependencies">
    ```bash theme={null}
    uv sync
    ```

    This creates the project `.venv`. All commands below run through `uv run`.
  </Step>

  <Step title="List the installed Environments">
    ```bash theme={null}
    uv run monte env list
    ```

    `demo` appears as mock-only. It exists to exercise the loop itself.
  </Step>

  <Step title="Create a Measurement">
    ```bash theme={null}
    uv run monte init hello --env demo
    ```

    This freezes the Splits, the eval settings, and the Environment fingerprint. The name `hello` is yours to choose.
  </Step>

  <Step title="Run the Baseline eval">
    ```bash theme={null}
    uv run monte eval hello
    ```

    The CLI prints the Run plan and asks `launch?`. The mock Run takes about 30 seconds. This is `eval@0`, the score you compare every later Run against.
  </Step>

  <Step title="Train a smoke chunk">
    ```bash theme={null}
    uv run monte train hello --smoke
    ```

    A smoke Run is a capped sanity pass. It is never evidence: it cannot be a Baseline, a chain parent, or a promote source.
  </Step>

  <Step title="Read the Ledger">
    ```bash theme={null}
    uv run monte status hello
    ```

    You get the Run rows and the Lineage's Baseline line. Smoke rows carry a `[not evidence]` marker. There is no delta yet: a delta appears after a real training chunk and its follow-up eval.
  </Step>
</Steps>

<Note>
  A real score needs a real box. When you are ready, read [Run on a real box](/real-box).
</Note>