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.

An AI trader runs in paper trading (demo) mode by default. It's an excellent way to evaluate its behavior before any live deployment.

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

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."

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."

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."

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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

The two approaches are complementary. You can absolutely have several agents running in parallel, each with its own mandate.