No more late nights watching stocks and crypto, build a team of AI agents that trades for you

A trading blogger used Grok Bot from xAI (an AI agent that runs in the cloud, still in beta) to build an "AI trading desk." Six bots split the work. They watch the charts, read the news, write strategies, backtest them, and place orders. He only reads two messages a day and clicks approve a few times. According to his own public account, the whole setup costs about $30 a month in subscriptions and takes no code. What makes it reliable is permissions: only the risk bot can say no, and only the trader can place orders.

The desk at a glance

Put six bots in one group chat. You only talk to the top one, the chief of staff.

Bot	Job	What it does not do
Chief of staff	Assigns work and summarizes. Puts the decisions that need you in front of you	Does not trade on its own
Scout	Finds what is moving and why. Watches news and announcements on X	Does not make buy or sell calls
Chart analyst	Turns news into chart patterns and scores each opportunity	Does not write trade plans
Strategist	Writes trade plans and backtests them on historical data	Does not place orders
Risk	The only bot that can say "no" to anyone. Checks positions and risk	Does not propose trade ideas
Trader	Places orders from approved plans, sets stop losses, records fills	Does not change plans

The tools come in three parts. TradingView is the eyes. It reads market data, runs screeners, and manages alerts. The broker Alpaca is the hands, and you start with its free paper trading account. A trade journal is the memory. Every decision is logged with who made it and why. For crypto, the author hooks the scout up to GMGN and Fomo, two on-chain crypto trading platforms, to track new tokens and where the "smart money" is moving. Timing runs on scheduled tasks. The desk sends a morning report before the market opens, acts on alerts during the session, and sends a summary after the close.

The details above come from the author's own public account. That includes the claims about TradingView's official API and the subscription prices. We have not verified them, and we have not traded with this setup ourselves. The "day on the desk" timeline in his post is an illustrative scenario, not a real track record. This is not investment advice.

Why it works: three habits

• An idea must pass every stage before it becomes a position: The scout finds it, the chart analyst scores it, the strategist backtests it, risk approves it, and then the trader executes it. If any stage says no, the trade does not happen. A "universal trading bot" just squeezes those five checkpoints into one guess.
• Permissions are locked in the tools, not in the prompt: A prompt is only a request, so a bot can still step outside its lane. That is why every bot except the trader has its order tools turned off and keeps read-only access. The broker also sets a loss limit on its side.
• Move to real money one step at a time: Paper trading first, then small real positions, then manual approval for each trade, and only then loosen the rules. Each step needs a clean record before you move on.

Build it yourself: a six-step SOP

Give this to your AI agent. Have it check each step against its "done" standard, and have it stop and wait for your confirmation after each step.

Safety rules

• This is not investment advice. Bots make mistakes, and a good backtest does not guarantee future profits. Only use money you can afford to lose, and never use borrowed money.
• Give real-money keys only to the trader. Every other bot stays read-only. Set per-trade and per-day loss limits in the broker's account too. What the prompt cannot enforce, the broker's wall will block.
• Never paste passwords or API keys into the chat. Use the tool's built-in credential storage instead.
• Approve every live trade yourself. Do not consider loosening this until a clean record has held up for several weeks.

Common pitfalls

• One bot doing both research and trading: With no one to say no, it's just automated coin flipping.
• Treating the prompt as a lock: Bots are eager to act, so a bot told "never place orders" may still do it. Turn off the tool actions it doesn't need.
• Going live after a few days of paper trading: Run paper trading for at least two weeks, and make sure the results fall within the range the backtest predicted.
• Looking only at backtest returns: Small samples and over-tuned parameters make a backtest look better than it is. The better it looks, the more you should question it.
• Scheduling tasks too densely: According to the author, Grok Bot's usage is metered by a weekly quota, and messages between bots count toward it. Too many scheduled tasks can use up the quota by midweek. The setup is also not suited to high-frequency trading, since the scheduled tasks run minutes apart.

For the general method of building a bot team, see the case study Six bots run a mobile game with one method for building bots.