Recently, I came across an interesting concept that inspired me: a true AI quant system is fundamentally different from most "AI trading tools" currently on the market.

To put it simply, many quantitative strategies are still stuck at the "hardcoded logic" stage—appearing to use AI technology, but in reality just wrapping automation scripts with a bit of artificial intelligence. This isn't called an Agent; at best, it's a hybrid of "automation script + AI features."

So, what should a genuine autonomous quant system look like? My idea is: the quant strategy team is responsible for producing the core ideas, while risk control and execution departments ensure implementation. The key is to introduce an "optimization feedback loop"—continuously reading execution data through AI + data analysis tools, iteratively refining the strategy itself, forming a self-upgrading quantitative life form. Only then can it be considered a true intelligent agent.

We have already completed the initial version and are currently running and optimizing it. Compared to "pure script-based" quant solutions, this framework's advantage is that it can learn, evolve, and self-improve—this is the future direction of quant trading.