the observability space is is actually changing massively right now. Why is that? Well, observability used to be for humans. Used to be a UI you click, a graph you click, something you look at. Um and and today it's I would argue it's a lot of 2.0 which is like this combination of coding agent. Those of you who built skills skills for um Pyroscope, Google Cloud or or whatnot, that these these skills help you with your your human debugging these systems. Um and and really telemetry is like this smoke uh thrown off of your system that can allow these agents to go make fixes. It tells you what path in the code it took. Without that, you're guessing and there's a million paths it could have taken. the the data thrown off by your system allows um allows you to to go go use agents to go debug your software. Evals add another layer to this. Um but really what we're at here is is how do I build systems that autonomously fix themselves? Really that that is what we're after. Both both AI agents, I put AI into my my my system. How do I have this thing just improve itself? and and today we're kind of in the 2.0 which is a human making fixes and reviewing things. Um but there's a future we're all driving towards and throwing off traces, throwing off logs, throwing off way more than you normally would and having agents run at this for a continuous loop is where we're going. You can build at agent speed, but today you can't improve your systems really at this agent speed. So those of us feel this this kind of governor happening within our our our our products. um and and the bottleneck is actually not the fix anymore. So those of us who've used these systems and and use used um coding agents with with skills, the the the bottlenecks, a lot of the the confidence in in do I have it right? You know, a lot of this is is about is this fix the right one to push? Um and and so these are kind of the challenges here. And then how do you how do you build this loop in a way that just moves faster? Um