How to transform your org with AI

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Julia Nimchinski: Welcome Wade Foster, co-founder, and CEO of Zapier and Carolyn Dietrich, Cmo. Hyper, Growth Advisor with ticket blessing, public welcome to the show. How are you doing.

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Carilu Dietrich: Good. Thank you. Hi, Goddard and Carrie love your work and company.

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Kerry Cunningham: Thank you.

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Kerry Cunningham: I can’t.

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Godard Abel: Wade.

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Wade Foster: Hey folks.

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Godard Abel: Excited for your session.

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Wade Foster: Yeah. Good to see you.

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Julia Nimchinski: Awesome. Carol. Take it away.

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Kerry Cunningham: Thanks guys.

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Carilu Dietrich: Great. Well, thanks for having us and Julia, thanks to you and the team for hosting another great conference. So much is moving so quickly. So it’s exciting for all of us to keep learning from the best and brightest. And that’s 1 of the things that makes me excited about interviewing Wade today, as many Cmos are. I’ve been digging deeper and deeper into both AI vendors and specific examples of what real world marketing teams are doing today.

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Carilu Dietrich: To use AI to use agents to use automations, and Zapier keeps coming up. In fact, just today, maybe an hour ago I published a blog. I write a blog at

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Carilu Dietrich: carrielou.com. W. 3 doves. carrielou.com. And I wrote about a specific research process that that one really innovative marketer at support logic has rolled out that started as a Bdr research project and has really informed across the go to market funnel how they understand different prospects, personalized messages.

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Carilu Dietrich: and and make their team much more effective. So on Zapier, amongst several that I’ve been looking at recently. So, Wade, you guys, just in the last week have actually rolled out some really big leaps forward in your agentic capabilities. Do you want to give us? Give us the highlights of the news.

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Wade Foster: Yeah. So last week we launched our AI orchestration platform. It integrates AI agents with over 8,000 apps. Zapier is the most connected platform that does this type of thing, and it allows users to add AI agents directly into those workflows. It enables those systems to intelligently adapt and make decisions.

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Wade Foster: rather than just following predefined instructions which that was sort of the world. Pre AI, where you’d have this like if this, then that that that sort of style logic

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Wade Foster: alongside that we’ve added human in the loop controls via slack. I think this is a really important mechanism. If you’re introducing agents into your workforce, especially if you want to do it in a trusted way. You know oftentimes these well, these agents are probabilistics. They’re not. They’re not deterministic. And so that means they may not do the thing you totally expect it to do. And so, you know, as we start to deploy these things, and

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Wade Foster: more and more riskier environments. You’re going to want to have a mechanism to verify that these things are performing the way that you expect them to. So those are the the 2 big announcements that we’ve had in the last week.

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Carilu Dietrich: Well, and there’s a 3, rd too, right.

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Wade Foster: Oh, yes, our Zapier Mcp. Server. We launched our Mcp server earlier this year, and the really exciting thing is it’s available in Claude. So if you are a user of of Claude, which is a product from anthropic.

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Wade Foster: you can install the Mcp server right there and interact with any of these 8,000 different apps directly. So you know, it can be simple things like, Hey, can you tell me what’s on my calendar for today? You know. Okay, hey? I haven’t caught up with this person a while. Can you tell me more about them all the way to like, hey, pull this report from salesforce or pull this data from Hubspot, or do this action in this way.

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Wade Foster: And so it really gives you a lot more. It gives your gives Claude the ability to actually take action for you in the real world. Versus sort of just tell you the instructions for how to go do that thing.

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Carilu Dietrich: And break down. What an Mcp. Server is for people who aren’t at as close to the cutting edge as you are or may not have already be deploying.

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Wade Foster: Sure. So Mcp stands for model context protocol, it’s a standard way for agents to discover and act on external tools. You can kind of. Think of it a little bit like what Apis do for, like Sas servers or Sas. Applications like Mcp does for agents. They can talk to each other in a particular way. So that’s like the most simplistic way to probably describe it.

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Carilu Dietrich: And so one of the things that’s on my mind is just that there’s this proliferation of agents. Salesforce announced their agent strategy last year. It was the basis for their whole dreamforce you’ve integrated now. And so you’re providing the integration layer. It sounds like behind Claude’s agent. Capabilities. Openai, of course, is going to roll out agents. Potentially, all of our different platforms will roll out agents. One of the advantages of Zapier is that you’re really horizontal.

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Carilu Dietrich: You’ve traditionally been this integration layer that cuts across all different companies. But how do you think that leaders are going to pick and choose their agent

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Carilu Dietrich: processes? If if there’s kind of this proliferation of agent capabilities throughout their tech stack.

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Wade Foster: Yeah, I do think that. You know

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Wade Foster: one of the unique things that I think we are.

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Julia Nimchinski: Live, TV.

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Carilu Dietrich: Is that my Internet, Julia, or, Okay.

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Julia Nimchinski: Right, yeah.

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Carilu Dietrich: Okay, we were. Julie and I were worried about my Internet because I’m traveling. But it seems like we’ve lost Wade for a moment. So we will wait for him and talk a little bit more. I guess I’ll just talk for a second. That one of the things that I’m seeing is one of the reasons

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Carilu Dietrich: I’m running into people who are using Zapier is because they are trying to stitch together a lot of different platforms. And so some of the agents within a specific platform are like more optimized for that platform. So again, walking through a type of process that I’ve seen in 2 instances recently. That’s a bit more of the AI. I don’t know where. I guess some of the AI

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Carilu Dietrich: and some of the agents begin. Hey, we’ve got way back.

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Wade Foster: Hey? Sorry about that. Everyone.

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Carilu Dietrich: Yes, no problem. So I was just thinking about some processes that that I’ve seen recently, where people are starting in salesforce and they have a button that, like creates an analysis of a sales call or a sales account planning or starts research for sales in their salesforce instance, but then goes out across a lot of different systems, and it might go out across perplexity. It might go out across Openai. It might do searches on sec

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Carilu Dietrich: databases. So it’s really moving horizontally and moving through a lot of different types of services to bring things back. And then what I’m seeing with a lot of the innovators is that

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Carilu Dietrich: the more stepwise they create their process. If they break it down into smaller steps, they’re finding that there’s a less hallucination. And B, they’re able to optimize different steps with different Llms, so that they find that there’s better results from some of them. So I guess I was saying that my own personal opinion. I think that, like some of the horizontal tools, might work, win the agent war, because

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Carilu Dietrich: because really no one is a single platform company as much as oracle or salesforce, you know. Wish they would be.

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Wade Foster: But give me the official answer.

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Wade Foster: like I think we all have this dream of like, Oh, I’ll just delegate this like super high level task to an agent. It will go figure out everything for. And I think, you know, maybe we’ll get there. But for where we’re at today, folks are getting the most benefit by doing exactly what you described like, break the tasks down into very discrete bits.

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Wade Foster: and then assign agent to each one of those, and then orchestrate those steps as you go, and then to your point. You can, you know, test and tune each bit along the way, and I think this is where, like, you know, we’re having a we’re seeing. A lot of success is helping our customers do that orchestration across all these different tools that they have, because the reality is, you know, they’ve got some data over here that has really important access to information. You need to do a web search over here.

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Wade Foster: You know, you maybe do 2 or 3 different web searches, but each of those need to be their own step, because the agent starts to hallucinate if you try to combine all those things.

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Wade Foster: and so that ability to break it down into chunks is like a really important skill set, I think, for folks who are wanting to go deploy agents in the future.

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Carilu Dietrich: What kind of people are you seeing? Be the innovators in AI and agents within different teams? I know you’ve always been looking for the the builders. Some folks.

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Wade Foster: Like.

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Carilu Dietrich: Slightly slightly technical. I guess technical confidence. They don’t even have to be very technical now in in like kind of the drag and drop worlds. But but what kind of people within a team should leaders be trying to tap, to say like, can you really push on this for us?

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Wade Foster: Well, I you know I think there’s it’s it’s not

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Wade Foster: I don’t see like a particular role that necessarily is like standing out more than the rest. I mean, if I were to pick one. It’s anyone who probably has an Ops title like those folks, probably on the margin, tend to be oriented this way. But the folks that really seem to have this mindset

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Wade Foster: seem to be these tinkers. They’re like intrinsically curious. They’re, you know, they like to break this stuff down, deconstruct it, put it all together, and you know they’re finding a lot of success just by, like, you know, continuing to tinker with this stuff, and the cool thing about

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Wade Foster: AI, is that you get like this knowledge on tap. And so these tinkerers now are augmented by being able to go to chat Gpt, or Claude or Gemini, or any of these tools, and actually build like domain expertise, so they may not necessarily be the expert marketer or the expert sales rep, or the expert product person. But they’ve got the knowledge on tap such that they can then apply their like technical tinkery mindset to actually orchestrate these things. And

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Wade Foster: as a result, they’re often performing better than somebody who maybe was like

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Wade Foster: a career more a career salesperson like that, able to combine these 2 worlds together in a really interesting way.

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Carilu Dietrich: I’m seeing a lot of folks in the marketing sphere or the the go to market sphere in the in the rev. Ops team that are specifically strong, or the growth marketing teams where they’re a little bit closer to to kind of some of the process structures that enable the broader sales team or enable the broader marketing team. And some of those are showing innovation one of the challenges is that

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Carilu Dietrich: agents, especially as you’re building them to be simpler for everyday people to create

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Carilu Dietrich: could be created by anyone in a company. And a lot of Cmos and Ceos are talking to me recently about how difficult it is to get adoption across their entire employee base of of AI. You know, we recently saw the shopify. Ceos Memo leaked about. You know we’re going to put a pause on hiring, unless you can prove that you’re

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Carilu Dietrich: new hire. Can’t be partially replaced by AI Duolingo, I know, sent out a big CEO sent out a big note as well. You had kind of a different approach instead of a stick. It sounds like you guys did a carrot. You, you did like a global hackathon you kind of had like a red week or something where everyone got deeply involved. Did I read that? You guys have 89% adoption of AI across your company.

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Wade Foster: Yeah.

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Wade Foster: a little over 7. Yeah, a little over 700 employees. And it’s actually over 90% folks use AI daily inside their work. But this is not something that like snapped overnight, and I don’t know that our approach was crazy. Different from what shopify or duolingo did. We just started sooner. You know we did this 2 years ago. For us. The impetus was

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Wade Foster: my co-founders, and I had been playing around with, you know. Gpt. 3 Gpt. 3.5 before Chatgpt came out. We were sort of like, expose the team and just saying like, Hey, check this out if you like interesting technology. You might think this stuff is fun, and there might be interesting ways to deploy it. But it was very suggestive

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Wade Foster: in nature. Chatgpt get even more excited. And maybe we’re making stronger suggestions. Hey? This is really important. But again, we’re not really turning the screws on the company to say, Hey, we really got to go. Do this.

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Wade Foster: The wake up call for us was in the spring after Chatgpt launched when she came out, and the 5, th so impressive is that Gpt. 4 was a great model.

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Wade Foster: but even more so was the rate like it came out 6 months later. It was so much better than 3.5. It was cheaper, faster, etc. And the things were approving, but like

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Wade Foster: something that we had to, we had to be paying attention to. It was like a massive wake-up call for us. And so that’s when we said, Okay, AI code red inside of Zapier, we’re going to create.

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Wade Foster: We’re going to do a hackathon for an entire, whether you’re in engineering, or if you’re sales or finance or Hr, we don’t really care. We want you to go just build stuff. And because we want you to build a fluency, we want you to understand these things. Pre the hackathon. We did have to do some prep work.

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Wade Foster: So you know, we had to go procure all these. We had to make sure these things were abiding by our terms of service, our data, privacy, agreements, all our compliance regulations, sort of things. And so we had. And then a little bit of

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Wade Foster: education, because there wasn’t like a crazy amount of like external education at this point in time. So my co-founder, Brian, was recording loom video showing people like, here’s how you hit the you know Openai Api. And here’s some like weird things that you might think it behaves this way. But actually, it’s kind of new and different. So it actually behaves this way. So like expect kind of some of this stuff and that Hackathon definitely created like organic adoption, like spiked pretty quickly

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Wade Foster: after that. Then we really reoriented a handful of key things inside the company. So 1st we shifted from being very suggestive to a little bit more directive in a couple key places, you know. Certainly our product roadmaps were like, Okay, there’s a few areas that have to be much more AI forward. There’s certain features and capabilities that have to be baked in, and so that was like straight from the top. And then.

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Wade Foster: you know, there was. We made a habit of doing show and tell in our all hands about once a month, where we would invite a few key people in the company who built something interesting with AI to just show off what you built. And then we did those hackathons about every 4 to 6 months. So we just kept that repetition going, and as a result, you know more and more people started to see what was possible.

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Wade Foster: and snowball effect happened. So in the early days, if you were using AI, you were kind of an oddball. It was sort of like, Okay, you’re kind of weird, nerdy, early adopter like you go have fun like, have a good time. But once that snowball kicks, and all of a sudden the like. The energy becomes so infectious that folks are like, okay, we got to do it. And now

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Wade Foster: you’re kind of the oddball. If you aren’t, it’s sort of like, wait, what? Why aren’t you doing this stuff like this stuff is so obviously impressive and good? Yeah, you may still be running into bumps like this. Technology is not perfect at the end of the day. But most people see the potential and the promise such that you just get that flywheel starting. But, like I said, it took 2 years to get to this point. This was not a thing where I wrote a memo, and it was like great. You know, everybody’s doing this stuff. There was a lot of other touch points that had to happen to encourage adoption.

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Carilu Dietrich: You know, it’s funny because Atlassian really loves hackathons, and it was such a core success driver for us, especially in the early days, in part because we would do a lot of hackathons that were Cross departmental. And you’d get more technical people, you know, you get a marketing person with an idea and a support person who was interested in that same kind of category, and maybe an engineer and an it person, and they would all work together, and it would both build relationships.

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Carilu Dietrich: It would build the actual hackathon thing. But then it also built these relationships that led people to have collaborators and their ongoing ideas. So I can see how this like ongoing hackathon, would give your employees a chance to like. Be like, I kind of have this idea, but I can’t take it all the way by myself. Are there people I can talk to, either at this time, or, you know, on an ongoing basis, because we’ve started to form these relationships. So

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Carilu Dietrich: I guess I couldn’t endorse hackathons more for all sorts of things. Are you planning an agent, Hackathon.

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Carilu Dietrich: like now the whole.

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Wade Foster: We? Yeah, we will have an agent, Hackathon as well, too. Yeah, I want to add one other thing with the hackathons, too, which is

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Wade Foster: The the challenge. I think your average employee faces in AI adoption is that you’ve got metrics to hit goals to drive, and they have a way of doing things, and they’re good at that way of doing things. And so there’s a little bit of like tunnel vision going on. And so

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Wade Foster: it is beneficial to you to kind of like, create some space for them to be like. No, I need you to just go put your hands on the keyboard and go mess around with this stuff and learn, and

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Wade Foster: you get what you just found, which is that once they do, they get excited, they get it energized. It’s not that they aren’t into this. They actually are excited. It’s just they need a little space. They need a little bit of that to go make it happen. And so that that I think is really important. But yeah, agent hackathons 100%. We’re going to go do a lot of these.

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Carilu Dietrich: Well, and I would say over the last 6 months, as I’ve gotten deeper and deeper and deeper into AI, it seems to me that there’s really this slow down to speed up aspect. You know, when we first, st when Chat Gpt came out, you were like, Give me a marketing plan, or you know, what should the strategy be? And now we can see these people that are including prompts with, you know.

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Carilu Dietrich: dozens of documents, hundreds of lines. I was following one of the anthropic technical folks who said, when she’s optimizing the Llm. She goes back and forth a hundred times and like I used to get frustrated in the beginning, when you went back and forth 4 times. And now, as I’m seeing people build these like more complex AI automations, a lot of it is

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Carilu Dietrich: documenting things that haven’t been documented in the company like exactly what is the best case process? And like, what kinds of exact answers do we want? In what format do you see that same thing happening with the agents? It’s really kind of like a slow down to speed up aspect, because what you put in is so critical, then to letting it do its work speedily on the back end.

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Wade Foster: Yeah, my, my co-founder, Brian had this comment he actually made yesterday, where, you know, we were debating this around like, you know, particular AI effort. We’re working on where you know, folks are like, okay, we’re going to have to like this is going to come in at a cost of this other thing, and he was like, folks are going to have to be comfortable with this idea that you actually do kind of have to put 2 X, the work into this stuff. But you get like 10 x the output. You get 100 x, the output on the other side. And so that’s like a weird.

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Wade Foster: It’s like a weird way to think about it. It’s like, Hey, there is. There’s a level of polish and rigor and attention to detail here. That is really important. If you put it in, you’re going to get outsized returns on the other side. And so I definitely think that is very much true, and you know the folks that are getting stuck are kind of getting stuck with what you said where you’re like. Oh, I kind of put a basic prompt in. And it kind of gave me a basic answer. I don’t really see the value. So I’m going to move on. And it’s like, well.

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Wade Foster: you kind of gotta. You gotta develop some fluency with this. You gotta have a deafness with these tools, and that just comes from, you know, trial and error. It comes from sitting beside somebody who’s done some of this stuff and going. Oh, I didn’t realize you had to do that, that that you are on a whole other level than I am.

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Carilu Dietrich: Yeah, it just takes a lot more upfront. So tell us, then, as you’ve rolled out, how are? How are training the agents? How is training your agents going to be different than than setting up your Zaps and your process, you know. I think agents, of course, aren’t deterministic, but talk us through how people should try to think about approaching their agent projects in in a more complex way than just their automated processes.

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Wade Foster: Yeah, I think the the the main advice I have here is

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Wade Foster: human in the loop steps. So you’re going to want to break these things down. We talked about that already. But as you’re doing, testing, you’re going to want to have a verification step especially early on. And so there’s a few ways you can do this. You know, we have our slack approval steps. That work you can also like, have it create a Gmail draft for you instead of send the email. You can have it like log, a thing inside of a Zapier table or a Google spreadsheet. And then you can go review it in there and then, like Flip, a field to be like, Okay, I’ve approved this. Go ahead.

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Wade Foster: And so I think that’s gonna be really important to help build that trust. Now, over time, as you start to see this thing perform more consistently in the way you want.

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Wade Foster: then I think you’re going to be able to start to remove those verification stats certain points and say, like, okay, I trust this. This is not making the level of mistakes longer term, I think what we’re going to eventually see is

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Wade Foster: what I would call like statistical quality control. You know, you know, in the past.

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Wade Foster: you know, this idea of quality control has kind of been like a side thing in most software companies. But I think it’s actually going to come really, really critical in the same way that, like Toyota, ran the field on American manufacturers in the eighties by getting really good at quality control. I think you’re going to see the same thing happen with agents where you’re going to implement, like statistical statistical process control standards to

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Wade Foster: help you really verify, hey? Are these things working consistently or not. When it doesn’t hit the when your sample is not verified, you’re going to shut the whole thing down. You’re going to revamp it. And then you’re going to go. But I think we’re a bit of a ways from that. That’s going to be really important, I think.

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Wade Foster: for enterprise that are trying to deploy these agents, doing millions and millions of tasks every single day.

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Carilu Dietrich: Are you still seeing a lot of hallucinations? Because to your point, I think there’s the, there’s multiple problems that you would encounter in quality control. But certainly hallucinations is one of them that we know about.

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Wade Foster: Yeah, the models are getting a lot better at this, especially the reasoning models. This would be like, you know, Openai has, like the o 1 series, or the O. 3 series. These reasoning models just behave differently than the pre-trained ones. And so there’s less hallucination with them.

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Wade Foster: The second thing that helps with the hallucinations. This thing we’ve been talking about break it down into smaller tasks that said you’re still gonna have hallucinations. You’re still gonna have it make up stuff. And you’re gonna have to find ways to like, verify some of these things

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Wade Foster: at the end of the day. And so that’s where you’re going to want to have some sort of baked in quality control mechanism, and you’re gonna probably have to define like what your fault tolerance is for some of those things just as you would like, you know, if you delegate something to employee, you’re not expecting that employee to be 100% accurate, but you’re expecting to be like pretty accurate.

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Wade Foster: you know. You’re not going to fire them the 1st time they make a mistake. You’re going to go. Oh, actually like. Hey, you made a mistake on this. Let me show you how to do a better job with it over time, and your agents are going to have some of those same characteristics.

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Carilu Dietrich: 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. 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 2 saying

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Carilu Dietrich: like, Hey, we’ll take away this burden of keeping up these connections because you have what? Over 8,000 30,000 pre-built applications, or something already. But but you also give people so much autonomy to build their own thing, because it’s kind of like

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Carilu Dietrich: 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. It seems like where it’s going to break down 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.

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Wade Foster: Yeah, you know, this is what we we bang against the wall on this. So you all don’t have to like is the end result. But I think there’s a there’s ingredients that are really impactful. One.

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Wade Foster: You know, we have just tons of monitoring setup 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. It allows us to just move at a pace that we couldn’t before.

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Wade Foster: 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?

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Wade Foster: 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 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 3rd thing is like, we just have, like really good engineering teams that are really good at doing this stuff. There’s not like a

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Wade Foster: secret sauce to it. It’s just something we spent, you know, almost 14 years getting good at.

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Carilu Dietrich: 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 min 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?

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Wade Foster: Yeah, go. I think one of the easiest ways to start is to set up a Zap, and instead of setting up like a full flown, you know.

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Wade Foster: probabilistic agent. Just add, like an open AI step in the of yours. App. 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. Send 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.

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Wade Foster: 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 do a task at the end of the day. So that’s probably my recommendation for a simple starting spot.

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Carilu Dietrich: That’s great. Thank you so much. I really enjoyed this. I don’t see the other people 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

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Carilu Dietrich: processes being deployed in 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

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Carilu Dietrich: who whomever is next.

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Julia Nimchinski: Thank you so much, Carolo and Wade. Such a treat. I shared 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 your advice to all Vps and Cxos who are considering the next step, but they are not quite sure where to start.

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Wade Foster: 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 world’s.

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Wade Foster: whereas, like the upside is so incredible here that you have to find a way to start dabbling so you can 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.

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Wade Foster: And as you experimentation, you’re gonna start to, you know, just walk down the the transformation path to reinventing your organization. I find that

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Wade Foster: this sort of like fear-based approach a surefire way, that you will probably get.

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Carilu Dietrich: 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 great process optimizer to 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 in

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Carilu Dietrich: 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 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

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Carilu Dietrich: about it and and can plug out 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, the AI processes and agents

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Carilu Dietrich: need to be continued to be optimized, and they need to be optimized by people that no one understand. And sometimes that’s done really well in a team instead of isolated by yourself.

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Julia Nimchinski: Super helpful. Thank you so much. Again, Wade and Carol.