Jay Kreps: Yes. That’s probably the hardest one to forecast. What was shocking to me was how prevalent this pattern had become and how much work it was for customers to do it. So despite the fact they were doing a lot of this by hand with kind of custom code, they were writing, they- just across every industry that seems to be popping up. And that was what made us really feel strongly enough that we needed to invest in productizing it, even in a time period where we’re operating relatively leanly. The opportunity is really to drive the spread. And so if you see what happens in a lot of these industries is there’s a whole ecosystem of data flow. And once the mechanism for that gets set up, it really doesn’t change and tends to drive any new entrant or provider or spire that taps into that to also adopt the same layer.
And that kind of network effect, that’s certainly something we would see within a company as we spin up and get to scale. At a certain point of time, you have to ask for permission not to use Confluent instead of two years Confluent. That’s obviously a really good point to get to. Being able to do that within an industry or within a sector is even better because that can drive the acquisition of new customers. And that to me is the thing I’m most excited about, more so than the kind of direct monetization, which is obviously an opportunity as well but that ability to kind of become a standard for the exchange of data in different sectors and industries.
Gregg Moskowitz: All right. Makes a lot of sense, thanks Jay. And then a bit earlier in answer to another question, Steffan talked about some of the AI-oriented use cases that are occurring for Confluent. Along with this, are you also seeing an uptick in GenAI POCs is that something that’s really building or is it a little too early for that yet?
Jay Kreps: Yes. Yes, we’ve definitely started to see that come up a lot more in our customers, kind of more traditional machine learning was there as one of the driving use cases for a long time. And now this has become a very significant topic of interest for customers, a lot of experiments happening. So yes, I think that’s very promising for us.
Gregg Moskowitz: Perfect. Thank you very much.
Shane Xie: All right, we’ll go to Mike Cikos with Needham next, followed by Bank of America.
Michael Cikos: Hi, thanks to the team for getting me on here. And I’ll pass on my comments, too, Steffan, we’ll miss working with you, but congratulations to Rohan in stepping up to the CFO role here. Two questions, first, on the cloud guidance that we have today for Q3, I think in the prepared remarks, management alluded to maybe a smaller set of customers who drove some of that 2Q outperformance and that’s why we’re seeing the incremental revenue growth in Confluent Cloud declining in Q3 versus Q2. Again, the incremental growth it’s still growing, but it’s at a lower pace versus what we saw in 2Q. So my question is really, can you help us think about the volume of those customers that drove that Q2 outperformance and anything else that you can allude to, whether it’s a particular vertical or what a specific use case or maybe more onetime in scope that drove that sizable beat that we’re looking at in Q2 here, just for context, when we think about how it’s flowing through in Q3?
Jay Kreps: Yes. There was a set of customers that drove a portion of that we alluded to different events in each case, but yes, some streaming services that we’re kind of ramping up large sporting event in the Asia Pacific that was bringing stuff online. So there’s a bunch of different factors that kind of led to a ramp-up that we didn’t think necessarily made sense to project forward an alternative, but we thought it was a great uptick in the business.
