# Deploy an AI trader

## Overview

An **AI trader** is an **autonomous** agent powered by a large language model (LLM). Unlike a bot that follows strict rules, an AI trader **interprets the market context** (price, volume, news, indicators…) and **makes its own decisions** within the boundaries you set.

You define:

* **The assets** it can trade.
* **The risk management** (position size, stop-loss, maximum exposure).
* **The style** (intraday, swing, momentum, macro, contrarian…).
* **The sources** it can consult (price, indicators, news, X/Twitter).

It then decides **when to enter, when to exit, and how much to risk**, based on its read of the market.

{% hint style="info" %}
An AI trader runs in **paper trading** (demo) mode by default. It's an excellent way to evaluate its behavior before any live deployment.
{% endhint %}

## How to phrase your request

Define a **clear mandate**: asset universe, risk constraints, expected style. The more precise the framing, the more consistent the AI's decisions will be with your intent.

## Example requests

{% hint style="info" %}
**Example #1 — Risk-conscious agent**

"Deploy an AI trader that paper trades MNQ and MGC with strict risk management. On each trade, set a stop-loss and take-profit, and size the position so that hitting the stop costs at most 0.25% of capital. Only enter when the reward/risk ratio is clearly favorable. Use only market orders."
{% endhint %}

{% hint style="info" %}
**Example #2 — Momentum hunter**

"Deploy an AI trader that paper trades TSLA, NVDA, PLTR, MSFT, COIN and SMCI, focusing on stocks showing strong intraday momentum and unusual volume. Risk at most 0.5% of capital per trade. Use tight stops and trail profits with the move. Exit any position by end of day."
{% endhint %}

{% hint style="info" %}
**Example #3 — Macro agent**

"Deploy an AI trader that paper trades MES and MGC, based on macro catalysts and news. Watch economic releases, central bank announcements and major geopolitical events. Take positions when a clear directional thesis emerges. Risk 0.5% of capital per trade and hold positions 1 to 5 days."
{% endhint %}

***

## AI trader vs trading bot: when to choose what?

|                     | **Trading bot**             | **AI trader**                                 |
| ------------------- | --------------------------- | --------------------------------------------- |
| **Logic**           | Strict, deterministic rules | Contextual decisions                          |
| **Reproducibility** | Identical on every run      | Variable depending on context                 |
| **Backtest**        | Relevant and reliable       | Limited — the AI exploits the present context |
| **Best for**        | Systematic strategies       | Reading the market and adapting               |

{% hint style="success" %}
The two approaches are complementary. You can absolutely have several agents running in parallel, each with its own mandate.
{% endhint %}


---

# Agent Instructions: 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:

```
GET https://docs.obside.com/obside-chat/automate-your-trading/deploy-an-ai-trader.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.