Zapier Co-Founder & CEO on Building the Agentic Enterprise | Wade Foster

So you guys, I'm really excited to have a leader at this moment who was at the forefront of a lot. Actually, Paul, why don't you share why are you like, you know, like you feel like you've met your tech crush?

One of the things that we see again and again are companies looking to transform their employee base to an AI-first AI-forward company here, and one of the companies I believe is doing top 1% is Wade's company here. So tell us a little about your company and what you guys have done in terms of your competencies, your approach, what you've done.

But just before you do that, maybe just frame it why you are so excited about this company.

So one of the things we see again and again are companies that want to move to a blended workforce, 5,000, 10,000, 1,000 people, but how do you do it? A lot of resistance. How do you get the change? How do you roll out the technology? What do you do with the people who aren't adopting here? And how do you get the mindset both in the leadership and the frontline workers to really make AI not a parlor trick, but actually part of the social norm and fabric? And that change management's really, really hard. And we've been talking to a lot of different companies, a lot of different boards, a lot of different CEOs, and a few companies do it well. And Wade, you guys do it really well.

Yeah, thanks. So Zapier, for those of you who are not familiar, we're the most connected AI orchestration platform. We really help you connect all your tools into your AI systems, which is really important because these AI models, if they don't have access to your data, they don't have access to your tools, you kind of get a vanilla experience. But if it has access to the content that you use, so your CRM data, your, you know, your ticketing data, things like that, it's a totally different experience. The value of these models gets immense when you use it in that way. And for us, the transformation was really important when we saw ChatGPT come out, really actually GPT-4, which came out 6 months later. It was a real sort of wake-up moment, in part because GPT-4 was so much better than 3.5. The models were cheaper, and it came out just 6 months later, and we felt like, wow, there is a, there's a slope here that if this continues is going to be really important for what we are working on. We're helping people automate their work and it feels like AI is going to be an enormous ingredient in that. And so we called a code red internally and said, we gotta go figure this out, both in terms of the products we sell, but also how we operate internally. And I think the thing that we've learned in the 3 years since is that there's a couple ingredients that really do help organizations change. The most important ingredient, the one that I see most common, both that worked at Zapier and has worked at many other companies, is just workshops, hackathons, hands on keyboard. So much of what we talk about with AI stays way up here, stays at the 30,000-foot level. But when you see the leaders all the way down to the front lines, putting their hands on the keyboard, saying, I'm going to build an agent, or I'm going to build a workflow, or I'm going to build some sort of automation, however basic, all of a sudden, the discourse starts to get a lot more practical and tactical. And you start to see some of the fear fade into the background, and humans' natural curiosity starts to lean in. I don't wanna claim a hackathon is like a panacea for solving all your problems, but once you get more of the organization just a little leaned forward, a little bit more engaged, all that other friction that you start to have and resistance you start to have, it just gets a little easier.

So, yeah, just so, so Paul, I know you have another panel. I just want you to, you know, you know enterprise. I want you just to share why that he's so significant. So, you know, the leader in no-code, is there anything you would add to that before you got to hop?

Yeah, just one other thing. How do you justify the cost? So many other companies, oh my gosh, 800 employees, Copilot license, ChatGPT license. Is that a no-brainer, or how do you even think about that? That's the biggest resistance I see in executives who are trying to get to where you are.

I mean, I think the alternative sounds way more expensive to me. To not do this feels like it would potentially mean that you're going to get out-innovated, out-competed by others. And so the marginal cost of using these tools, it's not that much. Yeah, it almost feels like a non-decision to me.

Great. All right, so Zapier helped automate workflows between apps. Now AI agents can execute workflows end-to-end. What does Zapier become when the Zap is no longer a trigger action but an autonomous decision maker?

Well, I think the real opportunity that we're thinking about is how do you give access to tools to these AI agents? This week we launched an SDK. Which is a powerful way where you can authenticate any of your tools. So CRM data, help test data, email, calendar, things like that to Zapier in a governed way. And now an AI agent can go interact with it in a powerful way. So for example, you know, I have a tool that after every meeting goes and fetches the transcript out of my meeting note tool, and then it takes all those action items, it drafts emails, that needed to go out, so if I said, "Hey, I'm gonna follow up on this, this, and that, I'm gonna introduce you to this person," those things are automatically drafted. The context to update the team, that happens in Slack. Great, it's created an update for me that goes out into the right channel, into the right thread. All those things are work that I would have historically had to have done myself. I'd spend hours at the end of the day just triaging little bits in here. Now I've got an agent that just goes and handles all that stuff for me. and that leaves me more time to work on product development, work on, you know, new marketing campaigns, things like that. And so that's the power of what happens when you give these AI systems access to your tools in a governed way.

All right, so you, Zapier as the operating system for AI agents. Zapier already connects thousands of apps. Do you see Zapier becoming the operating system for AI agents? And if so, what layer of the stack do you want to own?

The, I think the key place where Zapier operates is that action layer. You know, if the AI is the brain, you know, Zapier is the arms and legs. It's the thing that's out there interacting with your tools, doing it in a governed way. I think that governed part is really important. You know, you don't want, you know, every agent to have just like unlimited access to these tools. So you want something that can say, this group of people has access to Salesforce, read access. This group can have write access. You need that. Governed piece that sort of allows it to happen in a way that represents the organizational trust system. But we're there to sort of help facilitate all that reliably.

So if AI agents can execute workflows across tools, which job functions disappear first and which become more valuable in an Agentic workplace?

Yeah, I think the most important skill set that is going to endure is human curiosity, like entrepreneurial spirit. The one thing that these AI systems don't do is they don't think for themselves. They're still inert systems. And so you do need to prompt it and kick it off. And that requires, you know, a human to have judgment and to push on those things. The thing that's going away is all that like munging work in the middle. So many organizations, as they get bigger and bigger, there's a big internal coordination tasks. Takes this bit of context, retranslates it for this team, retranslates it another way for this team, retranslates it for another team. Turns out AI is very good at that work. It can take written context and put them in different formats for different groups of people. So the human labor that sort of sits in the middle of those systems, I think those jobs, which candidly a lot of people don't love that work, they don't love writing all the status updates, they don't love retranslating all that stuff, increasingly that can get delegated to a human and/or to an agent. And now the humans can get pushed to the more creative endeavors, product development or sales and marketing, the things that like really actually do matter for the future.

So no-code tools turn millions into builders. Do AI agents eliminate the need for builders or create a new class of mega builders orchestrating agents?

I mean, definitely the latter. You know, the organizations that are moving the fastest right now have builders in all disciplines and domains. And that's what's really powerful is that you now can have your accounting function has someone who can build inside of it. Your HR function has someone who can build inside of it. Your marketing function has something that can build inside of it. And that is very powerful because most of us have been in organizations where you get rate limited by engineering or IT. And so you sort of end up adopting these third rate solutions to these problems. But when someone in that function who understands the discipline, who understands the domain, who understands the workflows can now say, I want to go make this better myself. That is a massive unlock for those disciplines to go solve their own problems. So I do think we're going to see the rise of just more people building in all these functions. And it may not be every person, it may not be every job, but, you know, even if there's just a 5 or 10% increase in those functions, that is a huge benefit to how various functions in an organization work, especially the non-technical disciplines.

Great, so we're 9 minutes in. I got 2 more questions and then I'm gonna unleash Paul. All right, trust and security. When AI agents, and I love this question, can access email, CRM payments, and internal systems, what are the new security models we need and where are we most exposed today?

Yeah.

You paused.

Well, I think this is a thing that everyone is struggling with. [FOREIGN LANGUAGE] You know, most organizations are caught in a really difficult choice. You can be scared of giving access to these tools, and if that's the choice you make, to say, "Hey, we're gonna restrict access," oftentimes you're now trying to compete with your arms tied behind your back, because somebody else is gonna be willing to do this, and they're gonna take more risk, and they're gonna be able to innovate faster than you. The alternative is you give access to all these tools, you turn these systems loose, and we're gonna find ourselves in, you know, a big security vulnerability. We're gonna find ourselves, you know, failing a compliance check. And that also feels very risky. So there does need to be a third way. And I think one of the most important things is permissions to these systems needs to get far more granular. You don't want to give all or nothing access to the CRM to every agent. You don't wanna give all or nothing access to do these, to take actions in these tools. But you wanna get a lot more granular. Lemme give you an example. I mentioned that workflow at the end of the day where I have my agent draft follow-ups for me. The key thing is I'm having it draft them. I'm not having it send those in an automated way.

So the human's still in the loop.

They land, yes, human's still in the loop for that workflow. They land as drafts in my Gmail inbox. I pop it open real quick, I take a look at it, I press send. Now over time, as I build confidence in that system, maybe I will let it go, eventually send those in an automated way, but I'm not gonna do that on day one. I'm gonna build the right system that allows me to monitor that and feel trust in that. And that is where there's a lot of investment, both at Zapier, but across vendors across the space, is trying to figure out how do we make sure to provide that type of governed access to those tools? Because if you do it well, that is the real unlock. That is the third way that I think organizations need to be able to really feel like they can invest fully in these AI systems. You know, if you don't have like a proper governed setup, you know, it's, it's pretty terrifying. I think I've heard a lot of OpenClaw mentions this week. OpenClaw has shown the way, but I think one of the big failures is that it, you know, you have to give all this access to a tool and it doesn't provide some of those governance mechanisms out of the gate, which makes it great for personal use, but to use inside of an enterprise, it fails that test.

So, you know, this is the visionary who kind of saw the benefit of a no-code system. Who's impressed with him? All right. Founder insight. Looking back, what did you fundamentally misunderstand about how people would use automation? And what are we misunderstanding today about AI agents?

Yeah, I think one of the biggest challenges that humans face with automation is we We often just don't know where to start. I think this was true in 2011 when we started the company. It's true now in the age of AI. When I go talk to our customers, when I go talk to folks that are getting started with AI, it's not that people don't want to use this stuff. People are excited about this, but there's a cold start problem. I heard the prior speaker talking about this where he said, hey, every UI is a chatbox. That doesn't help you know what use cases should I do? Where should I start? And I think more people in the space, whether they're vendors like us, they're educators, the biggest thing we can do is to put practical examples in front of people and say, this is something valuable that you can start with. This is how you can kick that learning curve off. And once you get that learning loop going, that's when I think humans' creativity starts to kick in and you start to get a, a feel for this where you start to go, oh, if I can draft follow-ups to my emails, what else could I do? Maybe I could also take that same transcript and maybe I could have it generate a case study. Maybe I could repurpose it for social in this way. And once you get that creative loop happening, it makes it a lot easier. But I think the biggest thing that is often holding companies back, individuals back, is not that they aren't excited about this stuff. It's not that they don't have access to tools. It's just simply, what should I do when I sit down in front of my laptop and I want to get started? What is the first thing that I'm going to go build? And I think that's where there needs to be a lot more investment, is to just get people understanding the art of the possible.

One of the things that our AI analysts at GA Insights were so impressed with was that last week or so you guys released an update to your AI fluency. What exactly is that and how do you use that with your 800 employees? It's really impressive. I might be the first one out there.

Yeah, we have an AI fluency framework and we use this to assess candidates who are looking to get a job inside of Zapier. And we shared this with the world in part because we felt like a lot of companies were imposing these AI mandates. We must be AI first. We must do this. But when we went and talked to people and said, hey, what do you think it means to be AI-first? You'd get a lot of stares back. Generally, you'd get a lot of people that, again, were excited to do it, say, hey, we actually do want to be AI-first. I'm not opposed to this effort. I just don't know what it means. What are you talking about here? And so we thought, well, hey, that's reasonable feedback. This should be more concrete than just, hey, we should be AI-first. And so the exercise we went about is we found the power users in every single function and we just sat down and talked to 'em and said, hey, what do you think makes somebody, what's a non-starter in your discipline? If someone's not doing these things, you're telling they're just not AI-first at all. What's sort of the baseline? What's like what you would expect anyone in this discipline to be doing? What's advanced look like? And then what does cutting edge look like? And so we have a simple framework. We broke it down into every discipline inside the company. So engineering, product, sales, marketing, finance, you name it. And we released this AI fluency framework and now we use it as part of our hiring tests. So when we go assess people, we assess them on all these dimensions as part of, you know, performance reviews. They're a part of this as well too. But I've heard from, shoot, I've probably heard from hundreds of companies now that have adopted this as well. I'm sure it's maybe even into the thousands, and it's just a helpful framework to take it from this high concept of like, we must be AI first, to something just much more practical and tactical to say, okay, this is a good starting block for us. Now one challenge with it is it quickly goes out of date. This stuff moves fast. So this week we launched our V2, or I think 2 weeks ago we launched our V2 of it. I suspect 6 months from now, a year from now we'll have a v3, a v4, because the space just moves so fast.

Really great. Best practice. You talked a lot earlier, Wade, passionately about these workshops. Do you have the same learning on different types of workshops, or how do you think about the workshops, and how much time do you invest in the workshops?

Well, so at Zapier, we run hackathons probably 2, 3 times a year across the whole company, where we just invite people to build. And, you know, it's protected time where they can set aside the daily work that they're doing and come back and say, "Let's relook at old problems. Let's look at new technology, and let's see if we can solve problems that we couldn't 6 months ago." And that keeps everybody's skill sets fresh. It keeps everybody up to date on what the state of the art looks like. Now, I see that pattern reflected in a lot of— enterprises as well, where they'll do these hackathons every so often. And these hackathons are not just for the engineering org, they're for all functions. Maybe once every 6 months is probably good. You know, I think for companies that are just getting started, they often will do a workshop with a smaller group of people. They'll maybe choose a slice of leadership, you know, the people who are gonna be responsible for rolling this out to the whole company. And they want to get them up to speed. Because these are the people that are gonna go have to bring it to the masses. And so they'll usually start in a pocket and then try and get it to go from there. But the best companies that I see are generally thinking, how do we get this from a small group of people to everyone in the company? I think there is a mindset in some companies that it's gonna just be a centralized group of people that go figure this out. And I understand that impulse, but for whatever reason, the companies that are at the cutting edge are pushing it and having more success pushing out to most, and those are the ones that seem to be going the fastest.

All right, I have a lightning round. I got a few short questions, just react. One workflow every executive should automate tomorrow.

I think the daily brief is just a real basic starting spot. You wake up in the morning, you should just get a well-drafted brief as if you had the world's best, you know, assistant.

Most overhyped versus underhyped AI capability.

Well, gosh, I mean, there is so much hype right now. You think that, you know, it's hard to point to any one thing, but there's like so much hype is out there. So, you know, in the short term, it definitely feels like things are probably across the board overhyped. What is underhyped is, I do think that we're gonna look out 5 years from now, 10 years from now, and all the stuff that feels overhyped today, we're probably gonna be far surpassing that. So I think the timelines are maybe what's being misunderstood.

Yeah, profound. What you said is profound. Right, biggest mistake companies make with automation?

I think the biggest mistake I see folks continuing to make is they, they tend to, they tend to resist just getting started. You know, it stays at the theory level. You know, they have an AI committee, they have an AI transformation leader, they have slide decks. Things look nice, but then when you actually get boots on the ground and you see like what's getting built, you know, these teams don't have access to tools, they don't have access to, models. They don't have access to actually the things that practically will change. And so, you know, I think the biggest mistake is to kind of keep it in this like committee land versus like, let's actually just start building.

Human skill that becomes more valuable in an AI world?

High agency, like creativity, entrepreneurialness, curiosity. Like, I think a lot of these words are kind of synonyms for the same thing, but just that can-do attitude.

Is AI taking our jobs?

No, uh, it's definitely changing our jobs. Uh, it's taking tasks away for sure. Uh, you know, the— some of you may have heard Jensen out there on the tour lately, uh, and he talks about this with radiologists. Radiology was the first job that was predicted to go away, and, uh, it turns out the demand for radiologists is higher than ever. Uh, AI has made that radiology job easy.

Like Xerox. Paperless office. We got more paper.

The task got easier, but the job of radiology was never to read scans. The job of radiology was to diagnose, to treat, to come up with plans, etc.

So they go upstream.

Exactly. And I think that's what happens in every job, is that we find a way to move to the next highest value bit.

How will AI affect competition?

Uh, I mean, it's at least in our space, it feels fiercer than ever. I think companies are able to move a lot faster, and I think that's really, really good for consumers. I think we're gonna see people who wanna buy software to use software are gonna have just more options than ever, and I think that's pretty exciting.

How will AI impact entry-level jobs?

I think it just moves up the stack again. I do think there is this moment in time where You know, what our school systems have been like prepping our entry-level folks for is maybe a little bit out of whack. That will adjust, that will course correct. But you know, when I was through school, you know, there was no such thing. Like I came up during the social media boom. You know, I started college when Facebook came out. And the idea of a social media manager like didn't even exist when I was in college, and now there's YouTube creators and content creators, like a whole thing. And so there's gonna be these new jobs, and the next generation will be great at those skill sets, and they'll figure out how to teach us where to go next.

[Speaker] Right, so Paul, you bring us home.

Wade, we're sitting here in April. Next May, 30 days from now, tens of thousands of college graduates walking out there. Many parents and grandparents here are really concerned about them. What's your advice for a college graduate now in this age of AI?

Yeah, I think I've got good news and bad news, I think, for them. Yeah, I'd start with the bad news, which is that there are a lot of companies that are taking pause of their hiring plans, and they're instituting hiring freezes and saying, hey, we need to take stock, and we need to assess, like, what is our future workforce going to look like? And that does mean that all these entry-level programs, these systems that feed in lots and lots of jobs, they may not be as vibrant as they were, at least for a moment in time. Again, I think it will course correct, but for a moment in time, it is gonna be a little trickier. I think the school systems, they've been preparing for one version of the world, and especially if you're a junior or senior in college, you may not have been prepped perfectly for that. I don't fault the teachers. I think it's really difficult to try and figure out how do you teach a kid for a world that maybe you don't understand yet. I think that's a really difficult job right now. So there are these hurdles that I think these students are going up against. I think the good news, though, is that it's not just the students that are going up against this. I think there's many folks that are 10, 20 years into the workforce who are used to working a particular way, and the world changed on them too. And those skill sets may not be fresh. Those skill sets may not be relevant for the future. And oftentimes, it's really hard to pivot midstream. You've got all these habits around how work should happen, and you have to relearn these tricks. These kids coming into the workforce, they don't have those habits. This is the world they're coming up in. And so they can just learn it all from first principles. And I think if you're a student today, you can pour every ounce of energy into learning how to wield AI better than anyone else. And you can compete with folks who are 10, 20 years into their career faster than ever. And so if you really embrace this stuff and you really lean all in, you're going to be better situated than almost anyone in the workforce. And I think that's the really exciting news, is that the playing field is level. Even if there are these other obstacles that you're facing, I think you have a really exciting moment in time to enter the workforce. And you have— because there's not many people that know how to do this, you can jumpstart your career if you are willing to put the effort in and be that type of person. And so I think in a lot of ways, it feels like one of the best times to be entering the workforce.

Really good advice, John.

So for decades, the path from idea to realization with software has been arduous. You know, Project Whirlwind started here. Elements of that ended up going to Silicon Valley. And so you get the personal computer, but there were punch cards, machine code, then C, Java to Python libraries, and now LLMs. It has gotten easier and easier. You were ahead of this curve. With your vision for no-code systems. The rest of the world, I think, has caught up. What do you see happening in this next phase?

I think the exciting thing is that as every innovation you've talked about has come along, there's been an order of magnitude more people who are invited in to build. It's gotten less complex, less technical, more human. You know, now The programming language of the future is English. It's talking. And I think that is really exciting because that's a skill set that all of us learn, you know, from when we're this tall. And so that capability to be available to all of us means that we're going to see that much more innovation happen in our lives. And so I think it's a really exciting—

Should young people still learn to code?

I think it's pretty useful. As someone who is a poor engineer myself, I wish I would have been better at it. There's a lot of value in understanding under the hood how these systems work, especially right now. Now maybe we'll get to a point in time where these systems will be so good that you never have to look under the hood. But right now, it is still pretty valuable to be able to understand computer science fundamentals and to understand how these systems work, you know, I think it's maybe you can still build a lot of impressive things without understanding it.

In the last 30 seconds, this isn't an infomercial for your company, but how many people work there now and what's the headcount do you think gonna be in the future given the trends?

We're at 800 people now.

Remote?

All— Totally distributed.

Hyperlocal, everyone comes in?

Total distributed company.

Do you have a headquarters?

No headquarters. Headquarters of the internet. You know, I think our headcount will grow. It may not grow at the same rate it would have in the last 10 years though. I think a lot of it just depends on how the company grows.

Great. Ladies and gentlemen, you know, meeting a CEO up close like this is rare. This is a very special guy, and we need leaders right now because, you know, who knows which way is up, and I think you certainly have a good head on your shoulders and are leading proudly and boldly and with a lot of heart. Ladies and gentlemen, Wade Foster.

Thank you, John.