A netizen demonstrated an automated trading portfolio: a web crawler connected to Jev and Grok bots, and he just went to sleep. Over 3 nights, $100 turned into $12,161.

When tweeter @0xMarioNawfal shared this case, he commented: "The crawler isn't the advantage. The AI that only answers Yes/No is."

The division of labor in this system is very clear:

- Crawler: Scrapes data of new tokens, social posts and position information

- Jev: Gives a Yes/No answer within 1 second to decide whether to execute a trade

- Grok bots: Execute buy and sell orders

On the third night, the system ran through the following process:

→ The crawler scanned 88 new tokens, and Jev only kept 1

→ The bots bought low and sold high, then reinvested the profits

→ 5 profitable trades, 1 losing trade, total gain of +145%

Code repository: https://github.com/blsssdsavip

This design compresses market decision-making into a binary judgment. The crawler only handles monitoring, Jev is responsible for making the final call, and trading is executed by robots. The advantage is that the decision chain is extremely short, and no manual monitoring is required; the risk is also obvious: the data only comes from 3 days, the sample size is extremely small, and only one person's result is shown. This setup itself does not constitute investment advice, but what is worth noting is this division of labor model: humans design the question, AI makes the judgment, and robots execute the trade.