You have this intuition that you've built up, but when you hook an AI up that has the ability to sprawl across everything, it starts making not just two or three connections, it makes four, five, six, seven, eight, nine, ten connections. You can have another set of eyes, AI eyes, looking at your workflow.
I've got all of my work tools, Gmail, Calendar, Slack, Granola. Go look at all of this and pay attention to how I did my job. This thing actually knows my business. It actually knows it better than any individual in my company. One person can do all of those tasks. This changes the entire software industry.
The Nick Stanley Show. Wade, welcome to the show. So excited to have you on here today. I thought an interesting starting point might be discussing your journey from Missouri to tech entrepreneur because it's an unusual path.
Yeah. I didn't grow up as a child entrepreneur. You know, you hear these stories of people who sold candy bars on like the school, you know, at recess at school and stuff like that. That was never me. I grew up in a pretty typical Midwest town. It was a pretty conservative state capital and you know, there was three jobs. It was like you're going to work for the state, you're going to be a school teacher or you're going to be a doctor. That was what my exposure was. And so I kind of just grew up doing my thing, played music, was into sports, that was sort of the perspective I had.
When things really started to shift for me though was in school. So, I was graduating around the time of the great financial crisis and you know, I'd been a good student and went to go apply for jobs, internships, things like that, but everyone had stopped hiring. Just wasn't, you know, even good students, they were like, we're not interested in that. And that was like the first time I thought, oh, I'm not just going to be able to cruise through this thing. I got to go make my own way of this stuff. And was fortunate enough to find a small software startup in Columbia, Missouri where I was going to school. They were hiring somebody for marketing and I had an engineering degree and you know, I started to study some online marketing stuff but I was not a marketer and the good news was they didn't know what a marketer was either. So, for whatever reason, they thought I was a good fit and they hired me.
And that was like my first real upfront close seat to what entrepreneurship actually looked like. It was, you know, less than 10 people that worked at that company. Super entrepreneurial. We were all just trying to figure out how do we make a product that can sell? How do we get people interested in this thing? And I fell in love. I remember learning that we had people in Australia that were finding the website, signing up for the product, paying us and never ever talking to us. And my mind was blown. I was like, whoa, you can make money that way. That's insane that that works. And you know, I figured from that point forward, I was like, I got to figure out how to start my own software company.
Now I came across Zapier in 2017 early on. I had an IT guy with a company that I started and he came to me and said, 'Hey, you know all those things you've been asking me if there's a way to automate some of these repetitive tasks.' He was like, 'I figured it out.' And it was a real turning point for our firm in just becoming so much more efficient. And I wanted to just take a moment. What has Zapier been and what is it now as you seem to be cranking out new AI tools on a monthly basis? Let's just walk through that.
Sure. We started as a simple way to integrate your tools. So, you know, if you're using things like gosh, in 2011, it would have been stuff like Dropbox and Evernote and Gmail and Trello and more B2B oriented tools like Mailchimp or Zendesk or Jira or whatnot. And you could set up integrations between these and that's where it started. It was a very simple trigger action-based system where an event happens over here, do this action over there. That's it.
We quickly realized that folks wanted more than just one action. They want to do workflow. They want to do end-to-end automation. And so that was act two of Zapier. Hey, let's actually build full-on workflow. And that came out in 2016 and demand skyrocketed. That's probably where your IT guy got really excited about, oh man, I can automate this stuff end to end, right?
Where and just an example of that would be?
Well a great example was hey I am running advertising on Facebook okay great when I get a lead I want to hit an enrichment API and get more information about the account and if it has this characteristic I want to save it to this list in Salesforce but if it has this other characteristic I want to put it in this other spot and if it's a hot lead I want to go text the sales rep and the sales rep should get notified right away to follow up instantly. So stuff like that, you can sort of just think through in your head like what do I actually want to happen when I get a lead and how do I just make that just happen by default?
So that was the next big shift of Zapier. I would say now we're kind of in the third era or maybe like 3B, which is the AI era. And it turns out both integration and workflow were phenomenal starting spots to build useful stuff in the age of AI.
Integration has been really valuable because for those of you who use agents and push these tools to the max, you will understand this. But for those of you who maybe just use vanilla ChatGPT, you haven't yet experienced the magic of what happens when you hook AI up to your tools and to your data. If you just talk to vanilla ChatGPT, you get kind of a generic response, a very intelligent response, but somewhat generic. But all of a sudden, if it understands, here's my business strategy, here's my customer ICP, here's what's going on inside my account. Now answer questions based on that context. The experience goes from vanilla to holy cow. It's like this thing actually knows my business and it actually knows it better than any individual in my company because it's got access to everything. So it's not just talking to this one person who knows sales really good or this one person who knows engineering really good. It's like wow this thing has context on everything. So in some ways it's like a better version of you know if you assume the CEO has the best perch of the business.
The AI is even better because it can go all the way to the ground truth and read every last little bit. So the integration part is super valuable to AI. And then the second piece, the workflow side of the house, well a lot of what these agents are are actually just workflows under the hood. They're going through these steps. I got a lead from the website. I need to enrich it this way. I need to save it into Salesforce. That's what people are doing with agents anyway is they're building workflows. Some of them are entirely deterministic. Some of them have a little bit of AI inference for certain tasks inside of them. But it turns out all that infrastructure we built along plays so well in the age of AI. And so when you come to Zapier today, you mostly see Zaps, which is the old workflow product. You see agents, but you also see tools like Zapier MCP or Zapier SDK, which allows you to hook up your tools to your other agent platforms. So, if you're using Claude Code or if you're using Cursor or if you're using Codex, you can bring all those integrations that Zapier provides directly into those tools and do them in a very governed safe way.
Yeah. And to just an example to illustrate all of what you're talking about, there was a video that we did on this channel that used a number of Zapier tools to make this happen where we did an integration with YouTube for this specific show where we built an AI board with some well-known characters Naval Ravikant and Seth Godin as advisors.
And it was incredible what happened with the integration where this ChatGPT where the board was based could read all the transcripts of every episode and was directly plugged into the analytics of the show. And when I started asking it questions about this show that I think I know everything about because I'm doing it every day and involved in it, it had insights into what was going on and what was working and what wasn't that I was not aware of at all. And it was a really incredible experience. And the video really resonated with the audience because people were popping off questions like how did you do this? How did you make this happen?
Yeah. And I mean that experience I think anyone who tries it the first time, that's their takeaway is they're like, 'Whoa.' You know, you have this intuition that you've built up and your human mind has made connections to certain things. But when you hook an AI up that has the ability to sprawl across everything, it starts making not just two or three connections, it makes four, five, six, seven, eight, nine, ten connections across all this different stuff. And it comes back to you and you go, 'Oh, wow. I never looked at it that way. I never thought of it that way. I didn't have the horsepower, the analyst capabilities, the tools. I didn't have any of that to sort of surface that kind of knowledge.' And it does change probably how you think about your show. You're probably like, 'Mm, I ought to be doing more of this and less of that.'
Absolutely. Absolutely. Along those lines, what was the moment for you where it clicked that AI was going to be a real game changer for society, for your company, for you as a CEO?
Yeah, I think the moment where we raised our urgency level would have been the GPT-4 launch. So we were dabbling with AI pre that. In fact, my two co-founders had started to build some AI product prototypes internally pre-ChatGPT. In fact, they built like a little texting bot where they had built a phone number through Twilio and I could go text it and I would ask it questions and stuff and I remember asking what should I give my wife for her birthday? I've got this weird top and you know, it's questions like that and it would respond back and give me suggestions. Of course ChatGPT comes out and that's basically the experience is this chatbot and I'm like ah yes of course it makes sense that that should be a product and yeah we were excited about that but we didn't necessarily pivot the business at that moment in time instead we shared ChatGPT inside of Slack we said hey check this out folks this is a cool product maybe has some implications on our space, see if you can use it for new features or use it to change how you operate. But it was still very suggestive, organic, no commands, no mandates, nothing like that.
But then six months later, GPT-4 comes out and there was three things that were impressive about GPT-4. One is that it took six months to go from 3.5 to 4, so it was fast. Two, the model capabilities were just a lot better than 3.5. Just talking to it, it seems smarter. You could see that wow something different happened here. And then three, the cost had gone down quite a bit. And so we looked at that and we said holy cow if we continue on a trajectory like this, it changes the entire software industry. And so we called the code red internally around GPT-4 and said hey we need to seriously rethink both our roadmap and our operations to take account what is coming with these new AI models.
And what does code red mean at Zapier?
You know it's funny you ask that was what most we had never called a code red before so most of the team which is you know probably 600, 700 people at the time were like great Wade code red what does that mean because we never had one. And so we had to figure it out on the fly. I knew well it means we need to rewrite everything. We need to rethink all this stuff. It is like a sense of urgency, a sense of focus on this. And so we did a bunch of stuff, we changed a ton of things about our product roadmap. We changed, you know, we bought a bunch of tools for people to start playing around with these things. But I'll tell you that there was one singular thing that probably had the biggest impact, which was we paused the company for a week and we ran a hackathon. Everyone in the company, not just engineering, you got to go build some stuff with AI. And now, you know, this would have been still mostly just ChatGPT era. There's not a lot of the tooling that you can find these days. And so for engineers, it was mostly working with the OpenAI APIs. For a lot of the rest of the staff, it was just like getting familiar with ChatGPT and how it works and figuring all that sort of stuff out. But the results of that hackathon were we went from sub 10% of the employee base using AI daily to north of 50% in one week and this would have been in 2023. So that was a huge step function forward at a time when most people were not using AI all that heavily yet.
Yeah. And I find the interface that you've created for building agents is really ideal for the user who doesn't have a lot of coding experience or is not an engineer. It is very easy to use, very intuitive. You're just talking to it and it makes things happen for you. And I think that's kind of the sweet spot where the Zapier agent creator is at right now. Whereas maybe Claude Code can do incredible things, but if you don't have an understanding of software architecture, it is more horsepower than your average person needs. Even someone who has some idea of how tools are built. Zapier's man, it's right there meeting the need where it's at.
Yeah. I mean, that's what we've tried to do is make it really easy for folks who want to build these agents that run autonomously that run in the background. Just describe them in natural language. So, like the one I was describing before, it's like, hey, I got these leads coming in from Facebook. Can you help me enrich them? And then, route leads like this here, route leads like that there. You can just describe what you want and the system will be like, great, got it. Let's go build it. And it builds it out for you. And it does it in a way that is reliable, cost-efficient, which is not always the case for these AI systems. These AI systems are not known for their reliability. They burn a lot of tokens. And I think when you use something like Zapier where we're running it deterministically, we're encoding it in a very specific way. You're going to get more reliability and cost advantages out of it.
Well, one thing I like about it that is underestimated I think right now is that it will also tell you when it would be useful rather than having an agent that is trying to make judgments and decisions to just go with a deterministic automation that just says, 'Hey, when there's a new lead, I want it added to my HubSpot or whatever that might be.' And I found that almost ironic that some of I'm getting on there to use the AI functionality and then it's telling me, hey, just use the old school Zap that will just make this happen automatically. I'm going, why didn't I think of that before?
Well, I'll tell you a secret. So, a lot of the value of working with AI is to help you build the tool. So, you know, when you're trying to figure out like what should my agent do? What should this workflow do, it is really helpful to talk to an AI to an agent system about what you want? Go back and forth, design it, and think through all that stuff. But once you get it working, then you're like, 'Okay, great. I want you to do that exactly that same way 100% of the time. I want you to run a plain old deterministic workflow because that's what I want.' And you know, I think where a lot of folks make mistakes is they actually build it with AI, but then they also run it with AI where the AI's making decisions every step of the way and it's not always running it the same way you want. And so a lot of the times the value of AI is actually in the build process. On the running side, run it with code. That is a way better way to go about it.
Yeah. Now and I've seen with your hiring, you're really putting AI fluency at the forefront with your hiring and I want to understand why that's important to you. And then do you see this AI fluency as something that is lifting up the floor on people that you're hiring or is it really amplifying your top talent or is it doing both of those things at once?
Yeah. So AI fluency is important for us for a couple reasons. One, when folks really understand how to use these tools, we reap the benefits internally from them. So our operations get better, our products get better because we've got talent that actually understands how to get the most out of these tools. So that's really important. The other thing that's really important is it's a signal to the market that Zapier cares a lot about this stuff. We invest a lot in these things and I think right now that helps us attract the best talent to Zapier.
Unfortunately, there's too many people that I come across that are excited about this stuff. They're building cool stuff in their spare time. Maybe they've got an OpenClaw setup. Maybe they've got this that or other. But they get to work, everything's locked down. Everything's shut down. They can't use AI for this, they can't use it for that, they effectively can't do anything. And so these folks who have started to build these skills and capabilities, they can't really, you know, it's like you got a Ferrari in the garage. It's like, why is it in the garage? Get it out there and race that thing. And that's happening in a lot of workforces where they've got this amazing talent internally, but they're not actually letting it get out on the racetrack and go make things happen. And so those folks start to see what we're doing and say, 'Well, if I got this Zap here, I could be out on the racetrack. I could be making stuff happen.' So those are the reasons that I think this AI fluency is so important for us.
Then you ask like, hey, is it raising the floor? Is it raising the ceiling? And the answer is it's doing both. You know, I would say the thing that happens first when everyone builds with AI is certainly everyone's individual productivity starts to go up. So you can see across the company, you can almost ask anybody you can say like hey do you feel more productive with AI and they'll all be like yes I used to do it this way I do it that way etc.
I think where the ceiling raising starts to happen and this is where I think a lot of the organizations that have been fast to adopt AI, this is kind of the next bottleneck that we're all trying to fix is how do we go from individuals being great to institutional productivity going up, right? That's the next big unlock. Just because I'm better, but you are the bottleneck in the org, it doesn't matter that I'm now 10 times faster, 100 times faster. If you're still in the same spot or the system in which we operate is still at the same spot, my acceleration doesn't help the company. And so, you know, I think a lot of folks are trying to figure out, okay, how do we actually reinvent these end-to-end systems? How do we reinvent the org chart? How do we reinvent how work gets done to actually take advantage of that? And this is where, you know, it's people, it's tech, but it's also redoing a lot of the sort of fundamentals. And so, you know, I think that's kind of the next frontier it feels like for a lot of these scaled organizations.
Now, you have a unique viewpoint with your firm to I feel like to see a little bit into a crystal ball that not all of us have because you can see how people are using these things and what they're experimenting with and what they're making with the tools. Where do you think all of this is headed with AI in general?
Well, I think the exciting thing is that an individual can now enact so much more, can solve so much more of the problem. You know, it used to be, the way a company would work or at least a software company like which is what we do is, you'd have a team that goes out and talks to customers, understands the market problem. They would share some of that stuff with the product team. The product team would shape the roadmap, figure out what to do. That would get handed off to engineers and designers who would go build all these systems. And at the end, you would have a test release cycle. And then you would have marketing that would do all these things. And so, there's all these people in this chain of work that sort of has to go through to get something out the door. Now, with AI, one person can do all of those tasks, every single one of them.
And I think that that is super exciting. Like, it's going to be so interesting to see what the impact of that is for society. I think one, we're going to just see a longer tail of products that get built for consumers because the cost of producing it has gone way down. And so that means we're going to solve more problems that didn't used to be economically useful to solve. I think you're going to start to see that happen inside of companies. We're already seeing this now, too, where I've got, you know, I don't know how many agents running for myself that are solving problems that I always wanted to solve, but I never could. I just never could solve them, but now I've got them running and they're super helpful. And so that's very exciting to see.
Ultimately though, I do think that we're going to see a big rewrite in how just companies operate. Probably if I was to point to one particular thing though it would be the shift from code writing code being expensive to writing code being cheap. So much of our workforce or our systems and processes were baked around this principle that code is expensive to create. So you do all this upfront work, you do all these things because once you start writing code, you know that you better get it right. It's gonna be expensive to write all this code.
But now if code is cheap, how is the world different? You don't have to have all this upfront investment. You can do a lot more just like, well, let's just try it. Let's just build it and see. Let's see what happens. So all this upfront coordination, effort, all that sort of stuff. I think a lot of that fades away and now you've got this other thing that's emerging where it's like, well, we're building a lot of stuff. Well, do we ship it all? Should we ship it all? You hear taste come out a lot. You know, some people are like, 'Oh, taste is the new thing.' Maybe you're just shipping a lot of things and you're A/B testing every stuff and the things that win are staying and the things that are losing are getting rolled back and taken out of the product. Maybe that's what it looks like. I don't know. It's just really interesting to think about how the world and the organizations, particularly software organizations, shift when code is cheap versus expensive.
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Yeah, you talk a lot about contact with reality as being a great test for a new idea, a new product, whatever you're working on. And I think if you are an entrepreneurial kid in Missouri, this is a really or wherever you might be an exciting time to be alive because you could just make stuff and put it out in the world and see what happens.
Yeah, spot on. Like I think that this has got to be one of the most exciting times to be a startup founder because there is so few barriers to getting started. So few. You can literally just make something and you can put it online. You just say like hey check this thing out and if you've made something truly useful people are going to check it out and they're going to try it and they're going to tell you and they're going to like it if you've done something truly useful. And if you haven't, you'll learn that, too. And so you can start the feedback loop and go, okay, well, what's the next thing I got to go build? Let me try another thing. And the feedback loops are just so much faster than they used to be. And so it makes it really exciting to build.
Yeah. So if you were, let's take three age points. If you're 13 years old, if you're 23 years old, or if you're 53 years old, what are the things you would be doing at those stages of life to be preparing for what's coming next to get involved in what's happening now, the skills you would want to be building, whether that's a kid or an executive in a firm?
Well, you know, I think all three of those age groups benefit from just using AI, like learning how to wield these tools to do interesting stuff. So certainly I think everyone benefits from building some amount of AI fluency. Now maybe what's different, you know, if you're 13, you still got a lot of education in front of you. And so I still think there's probably a lot of value in building out just a very well-rounded education. Like you ought to be learning math and physics and communications and just all these sort of core foundational skills, those things are going to be
Critical for you no matter what you end up doing in your life. And so, I think in addition to just getting good at using AI and these tools, you want to build your foundation of knowledge and these skills that help you understand the world really well.
Now, if you're 23, you probably developed a lot of those things. You're entering the workforce in a really interesting time. I think probably the bad news for you is that you may not have been prepared for this AI world. You probably went through college and got a degree in a world that didn't know that this technology was going to exist. Or it has existed, but it's been so new that nobody knew what to do with it yet. And so, you probably have an education that maybe is only partially relevant for the world that you're coming into. So I think that's the bad news.
Well, and also the bad news is that a lot of companies are putting hiring pauses in place. They're trying to say, 'Hey, we got to take stock before we go hire people. We need to understand what it is we actually need. So, let's just take a beat real quick.' And so all these orgs that were so used to hiring 22, 23 year olds all over the place, they're maybe saying, 'Ah, let's wait.' So that's the bad news.
I think the good news though is that you're at the very beginning of your career. And so you have a blank canvas. You have all this time on your hand where you can actually go learn how to be the best at wielding these AI tools. And what is unique about this is that the folks in the workforce, the folks that are 30, 40, 50 years old, they are also at the starting block of using these tools too. And so usually when a 23 year old comes into the workforce, someone who's 33 or 43 has that many more years of experience, they have a head start on this stuff. Now not so much. They're kind of at the same starting block. And so the good news is there's never been a better time for you to say, 'Hey, I'm gonna race ahead and get really good at these things.' And I might actually jumpstart my career compared to everybody else in the workforce just by getting really good at using these things. So I think if you're 23, you probably are in the best position of your life to actually go learn how to wield these things and do impressive stuff with it.
Now, if you're 53 or whatever the age 50, I think is what you said. What should you do? Well, I've got about another decade before I get to that age. So, my answer probably is not as good for this because I haven't experienced that quite yet. But, to the extent that you want to continue working, I think you got to go learn how to use these tools. It kind of reminds me of my mom's a pharmacist and she came into the workforce before computers. Then eventually computers showed up. It's like, well, if you're going to work in medicine, you're going to have to learn how to use all these computers. You aren't going to get to do it the pen and paper way anymore. Well, I think this AI era is going to be the same thing. If you want to stay in the workforce, you're going to have to keep your skills relevant. And so, time to reskill and all this stuff.
But you probably also have a really great opportunity to think about what your legacy looks like, what your stewardship looks like. You've got so many great experiences from just being in the workforce for so long that you probably can go look back on all of the things you've experienced and think, how can I actually go solve those things with AI? How could I have done something better? And so you're probably in just a really good spot to have more ideas because you've just seen more stuff than most people. And so if you actually tap into that part of your brain, I think you can probably actually do some pretty incredible stuff. Yeah, I think the folks further on their career, the worst thing you could do is just sort of stick your head in the sand and say, 'Nope, I don't want to see change.' Because I think change is coming whether you like it or not.
Yes. Yes. Along those lines, do you still believe in the value of higher education?
