Eric Siu breaks down how AI feedback loops work: set a target (like 50ms page load time), measure where you are now (150ms), calculate the gap, then let the system iteratively close it. The loop learns and improves on each cycle toward your goal.
And a loop, again, is a workflow that compounds, a workflow that learns. The first part with the loop is you, you might have the first step where you have to define what your target is, and then it goes all the way down and it observes what the target is and it learns over time. And this is actually a better diagram over here. On the very right side of the loop, you have your target state. So that's what you're trying to hit. So let's go with the example again. You want every page on your website to be 50 milliseconds. Okay. That's the target state on the right side. Right below it, observe the current state. So let's say every page on your website, maybe your average is around 150 milliseconds right now. Then you have the gap. So 150 minus 50 is what? 100. So that is the gap. And then what happens is the loop learns over time. That's all it is. And it gets better.
