Q context? And then maybe if you can talk a bit about long context and whether or not that's something useful to you or, you know, I think there's always this question of like, if you could put all the data in, would it be better? Like I think here you have definitely more data than can fit in the context window. So I'm curious like where the sweet spot is.
A So Context. So I think there are a few ways people do add context, you know, which teams, which services, which alerts they are looking at, which dashboards they are looking at. So I think those nuggets are definitely helpful in making the investigation faster. One of the things that we have shied away from is asking too much from the user, because then what is the value add of traversal, right? That if you have to find all the context and give it to The AI to go do the last mile delivery. So the onus is on us. So let me just run it and show you what is happening. So when, when the user asked this question, now Traversal is going and figuring out what all contexts should be pulled in for this particular issue that the user is describing. And in the background, it's leveraging who is asking the question at what time the question is being asked. And its own understanding of the knowledge base or the system architecture in the background. Based on that, it's making queries to, you know, the, of course, the live data, the logs, the metrics, the traces, and it's building that context, and it's doing this sequential hopping as it's building this context to hop from service to service, as you can see, from index to index, and finding these three services impacted. Okay, but they are also connected like this, so let me go hop There. So this kind of context building is being done by AI,…
AI assessment note: “So this kind of context building is being done by AI”