profiling uh uh data produced. And once uh a prof a an AI agent gets this, what what are the steps that it needs to do in order to get to the potential fix? So, we we we have mentioned that it can identify uh a pattern and say that okay, this is a potential problem to be fixed. What what happens next? Um it could knowing where that method lives, it could do a code search and first of all, before uh I mean, yeah, it could do a code search and find out the code repo where this method is defined uh or this code is defined. And it it needs to extract out the exact commit that is currently running in production, which is typically easy to get. You know which build is running in your production, and you could point that to the LLM to uh check out the Git repo at that same commit. And then uh once it has uh find found out uh and has the Git repo cloned, uh it can look for uh that exact code path, uh skip any internal library details, and find out uh the code patterns. And now that it now once it has the uh full uh uh code repo cloned out, the um the methods uh definition and implementation identified, it can trace the entire call call path of that method. And this uh structured data once it uh has this information, becomes uh like very powerful, and we'll we are going to talk about how uh it leverages