I have been monitoring a phenomenon over the past few weeks: Kite seems quite stable, but internally it is actually undergoing a deep adjustment.

The more I look at it, the more I feel something is off—what it is addressing is fundamentally not a performance issue, but rather "system latency". These two concepts sound similar, but are completely different in essence.

Many people evaluate AI projects based on a few indicators: Is the response fast enough? Are the results accurate? Is it smooth without lag? These are indeed important, but to put it bluntly, they are all superficial efforts. Want to improve? Add servers, adjust models, optimize algorithms; the technical team can always figure it out with some time.

The real trouble is "system delay"—the time from user input to the system truly processing this behavior, from the launch of new features to the formation of user habits, from data influx to solidifying into effective feedback, there is a natural gap in between.

The delay of AI systems is not due to technical hiccups, but rather the invisible gap between ecology, cognition, user behavior, and data cycles. The core challenge that Kite currently faces lies within this gap.

I want to elaborate on this matter a bit more, as it directly relates to the direction Kite will take next, and this is precisely the part that is easiest for the outside world to overlook.

**First, let's address the first cognitive misconception: surface performance and system digestion capacity are fundamentally two different matters.**

According to conventional logic, the stronger the system's performance, the more users there will naturally be. However, AI projects do not follow this logic. Their growth is not linear, but comes in segments. Even if you maximize the speed, the ecosystem may not necessarily keep up.

For example:
Surface performance is like speed, while system latency is like road conditions.

You drive a sports car on the highway, theoretically, a speed of 300 kilometers is no problem. But if the road is bumpy, there are toll booths one after another, and a big truck is blocking the way ahead, you won't be able to go fast no matter how hard you try.

Kite is currently facing this situation - the technical capabilities are strong enough, but the ecological infrastructure, user awareness habits, and data flow efficiency have not fully caught up. This is not something that can be solved by optimizing the code; it will take time for the entire system to gradually adjust.