Wade Foster & Carilu Dietrich • How to Transform Your Org with AI 3

Um, you know, one of the reasons I, I think a lot of companies rely on you for integrations is because if they build their own integration, uh, and those vendors change their software, then that underlying process breaks. And so the whole build versus buy, you're kind of between build versus buy. It's like someone could build it all themselves from scratch inside or or have like a fully complete, much more expensive system. And you kind of sit between those two saying like, hey, we'll take away this burden of keeping up these connections because you have what, over 8,000 and 30,000 pre-built applications or something already. But you also give people so much autonomy to build their own thing because it's kind of like building blocks that they can use. As you look ahead, you know, you're trying to keep up with the different LLMs, you're keeping up with different integrations. That seems like where it's going breakdown for a lot of people who try to build their own. How do you guys stay across so many different vectors to keep all of these things working? I mean, obviously you've been doing it for years, but LLM adds another layer, I think.

Yeah, you know, this is what we, we bang our heads against the wall on this so you all don't have to, like, is the end result. But I think there's ingredients that are really impactful. One, You know, we have just tons of monitoring set up for all of these situations. So we're just spotting this stuff early to be able to fix a lot of this stuff. With LLMs, that monitoring has gotten better. Those fixes have gotten faster. You know, it allows us to just move at a speed, a pace that we couldn't before. The second thing we benefit a lot from is just our scale. You know, we, we have a relationship with these 8,000 vendors we work with. And so when they go make updates, when they go make changes, they're thinking about how's that going to impact the relationship we have with Zapier and all those people that are consuming and using this stuff. And so because we have that trust, people know that we're being used. There's a level of care that these folks give to us. And, you know, that wasn't— that didn't always— that wasn't always the case, but that just has happened as we've grown and gotten more popular over time. So and then the third thing is like we just have like really good engineering teams that are really good at doing this stuff. There's not like a secret sauce to it. It's just something we spent almost 14 years getting good at.

Yeah, I mean, it feels like in this land of AI and agentic, your build is never quite done because you're going to keep optimizing as you have new information to feed your agent, new systems you want to connect to, new outcomes you're trying to drive. We have only 3 minutes left. So if people are just getting started with agents, what is your advice to them to help them be successful and understand what's going on in the agentic world?

Yeah, I think one of the easiest ways to start is to set up a Zap and instead of setting up like a full-blown, you know, probabilistic agent, just add like an OpenAI step in the middle of your Zap. Oh, here's a really simple use case for a marketer. You got a form on your website. Okay, great. Send that over to— send the email address and the company domain over to OpenAI and say, hey, tell me what you know about this stuff and then add it to Salesforce or add it to HubSpot. That's not like a full-blown agent, but it starts to give you a taste of like what is possible with these things. And it's super simple to get going. And then over time you can start to figure out like, oh, how do I combine more and more of these things to actually get like a full-blown agentic system that has a lot more autonomy to go, you know, do a task at the end of the day. So that's probably my recommendation for a simple starting spot.

That's great. Thank you so much. I really enjoyed this. I don't see the other people on our, on our line yet. Oh, there's Erin. She must be joining. And I just wanted to again mention that I've written up a case study just this morning on a great Zapier example And last week did a prioritization list of a number of different places where I'm seeing the most processes being deployed successfully in marketing. So I'll put a couple of those links there into the chat. Thank you so much for having us, Julia. Or do you want us to do one more question while we wait for whomever is next?

Thank you so much, Carolu and Wade Foster. Such a treat. I share your link with the community. And yeah. I guess we had a lot of concerns about transitioning to agentic AI in our CXO land. So what's your advice to all VPs and CXOs who are considering the next step, but they are not quite sure where to start?

I think, I think the best thing is to start. Yeah. Like, you know, it's so easy to be fearful of it, but to me, that is a surefire way to not reap any of the rewards. Whereas like the upside is so incredible here that you have to find a way to get to start dabbling. So you can, you know, mess around with Zapier by adding like a little bit of AI into the mix of your workflows. You know, sign up for ChatGPT or Claude and start playing around with it for these different areas. And as you create space for others in your employees, run hackathons to do some of these things. You don't have to deploy everything to production. Find the best ideas and go, oh, okay, that's where we're going to start. We're going to start doing it for this, this, and that. And as you experimentation, you're going to start to, you know, just walk down the transformation path to reinventing your organization. I find that this sort of like fear-based approach, a surefire way that you will probably get—

And I would just add that you don't have to do it alone. So I've done some experimenting by myself, but I also hired this guy who's a like great process optimizer to like work on a specific AI process for me that I couldn't do myself. And then we worked on it together and optimized it. And then I took it over and started using it. And I'd also say one of the more innovative examples I've seen is of a sales leader who's done an automation inside of Salesforce where it automates— I think I talked about at the beginning— an evaluation of the sales rep sales call and their account planning and everything that he would have done for each sales rep every couple of days, but they can do it on demand immediately. And he just partnered with someone else that was technical on his team, and they hacked it out together in like a long weekend and a couple days. And so I think that having a partner where you're talking through how you're thinking about it and can plug at it together also makes things move a lot more quickly. And in the end, it's not the AI that's the intelligence, right? You need the people who really understand the business process and know what good looks like to both create what's good, You know, create the automation and then, and then test and evaluate the output because every, all of these systems, these, the AI processes and agents need to be continued to be optimized and they need to be optimized by people that know and understand. And sometimes that's done really well in a team instead of isolated by yourself.