Not Every Problem Needs a Human

Key Takeaways

Engineers often come to us and say, "Okay, so you're going to be better at solving these problems than me." And they spent years at these companies and we don't claim that. We just see there's so much low hanging fruit in terms of automation that we could automate away for you with these agents and then just lay up or tea up like all the key things you need to make the decision. So we want to lean into their domain expertise. They are the experts and we just want to make it easier for them. Um, so what they should be assessing is the findings and metrics and the logs and the dependency graphs and all those things that they already know. Well, we don't want them to have to understand the internals of our product. I think that's a failure. But also because we're not a synchronous flow, you're basically looking like it's the AI is leading itself to an answer and it'll bail if it can't find something and continue up to certain point if it is on the right path. Um, but for the most part, you're just producing artifacts that they can understand and intuit it already. The stuff that takes a long time is just maybe switching from one tool to the next tool, gathering the data, trying to put two and two together, and then once you have a picture, you can start to really use your expertise. But all of that before you get to the place where you have that picture, that's where you're saying, "We can automate the out of." Exactly. Often engineers are just like dreading dropping into a console or a terminal and keep cuddling and it's the same thing every single time. And there are of course black swan events and like really tough problems that maybe even an AI can't even solve for you. But there's so much gunk and like base mechanical wrote work that engineers have to do. And remember they have a full-time job in a lot of cases to write software to actually make the business successful. It's not just debugging and routine investigations in the background,