Tianyi Jiang: Yes. Great question, Jason. So I called out our Cloud Records product. It’s something that continue to gain more traction. Not only does it save our customers from a storage cost perspective from archiving optimization, but also leading to leveraging machine learning and AI to actually do much better data classification and life cycle management. That’s a high-performance product. The other one is tyGraph, we talk about sentiment analysis and employee engagement management. Every C-level today worry about that from a hybrid work scenario perspective. And third one, I would call out as interest, which is basically entitlement management and operations management of your cloud deployments, again, goes to in terms of the optimization cycle, right? Customers want to know how are these licenses being used, how can it reduce cost on operations?
Jason Ader: Great. Great. And when you talk about Gen AI, I understand that there’s an element of incorporating it into your products and maybe even having separate SKUs around Gen AI going forward. But can you talk at all about how internally you’re using some of the Gen AI technologies out there, things like Copilot from GitHub and other tools that related to Gen AI that might help you guys kind of accelerate development and lower costs.
Tianyi Jiang: Yes, absolutely. So I think we mentioned even in the last earnings, we already utilize GitHub Copilot on the Dev side. We are using more for the senior developers who see material efficiency boosts up to 30%. The newer developers who are still learning the ropes are less so. So — because to be a sophisticated user, you actually need to know whatever is generated is actually truly efficient and useful for the segment of the feature that you’re working on as a developer. But for the other side, again, it’s not just for Dev Gen AI, we’re leveraging and deploying across customer success across customer support across marketing — content marketing to actually make things more efficient. So for example, in customer support, we have decades of user — use case support, Tier 1 through 5 — Tier 1 through 3 and then go into premier support.
And of course, we can also ingest all of our user guides into Intelligent ChatBot that can actually interface and do even Tier 1 support for our customers to alleviate the load to level up the Tier 1 responsiveness. And of course, on the content side as well, be able to generate much more intelligent content as a drafting tool to make our content markets and product marketing folks much more efficient. So overall, leveraging generative AI allow us to bring up the overall quality of work as well as shorten the time line to deliver results. So these are various aspects of our company we think we can really level up, ultimately, it’s to improve the bottom line.
Operator: And the next question comes from Brett Knoblauch with Cantor Fitzgerald.
Brett Knoblauch: I guess a lot of software companies have reported in the back half of June has been kind of like a material slowdown. It appears that’s something that you guys didn’t see given the strength that you’re talking about in the quarter, am I right in how I’m framing that?
Tianyi Jiang: That’s right. We don’t see a slowdown.
Brett Knoblauch: And I guess, you guys talked about being a very uncertain macro year, but 2Q was stronger than the first quarter. And I guess the full year ARR growth guide about 21%. You guys held up AR growth pretty nicely in 1Q and 2Q at 26%. So I guess, what’s baked into the guidance that we’re going to expect to see that, call it, over the coming quarters to 21%? Is it just, call it, larger numbers or conservatively.
