The next thing that I think is where you really see the big unlock is when folks are now starting to identify opportunities to automate work that you weren't doing before. These are when you're now solving net new problems. This is a problem that either you couldn't do it because there's just no way we could hire that many people and do it reliably enough, or it's just something at your scale where you feel like we just don't have the resources to go tackle that. And this is where I think folks start to really get a bunch of leverage.
Welcome to the Exponential Scale podcast, the show where we talk about how tiny teams with big ambitions are doing more with less, scaling smarter not harder, and building big businesses without building big teams, unless you count the bots. I'm your host, Ron Schmillzer, and today's episode we're talking with Wade Foster, co-founder and CEO of Zapier. So now before we jump in, I need to mention to everyone listening that today's guest and his company is responsible for more accidental employees than any founder in Silicon Valley. Not human ones. I'm talking about the army of invisible workflows working quietly throughout your business while you sleep, shower, or pretend to be productive on LinkedIn. And Zapier is basically the unofficial HR department for micro teams. You hire no one and Zapier corrals 8,000 apps and tells them how to behave. So if the core idea behind the five laws of scale maxing, and if you haven't heard that please do listen to our podcast on that, is don't hire more, multiply more. Wade and his company Zapier are the folks handing out the multiplication tables. So micro teams everywhere are stitching together million-dollar operations powered by one actual human and a bunch of zaps held together with hope, caffeine, and Google Sheets or Airtables if that suits your fancy. And if you've ever said, 'Oh wow, I thought a real person was doing that,' only to learn it was Zapier, congrats, Wade is already part of your company. So today we're going to be talking to the OG here, the real source, to talk about automation, AI, and what it means to build a business where the bots outnumber the humans, which according to the manifesto is not a bug, it's a strategy. So if anyone was here before AI became everyone's second language, it's Zapier and Wade. So Wade, really thrilled to have you on the podcast here and would love to share your insights with everyone.
Yeah, thanks for having me, Ron. Yeah, so I'll just quick intro and then you can introduce yourself as well. So Wade Foster, for those of you that don't know, is co-founder and CEO of Zapier, the most connected AI orchestration platform. Zapier connects teams, tools, AI, and agents across more than 8,000 apps to automate critical workflows with flexibility, scale, and control. And prior to Zapier, Wade worked in marketing at Veterans United and Idea Works. He has degrees in industrial engineering and business administration from the University of Missouri, Columbia. So Wade, thrilled to have you here.
Yeah. Thanks, Ron. Yeah. So first, maybe introduce yourself a little more and tell us what you're working on and of course why we're all here.
Sure. So yeah, I'm Wade. I'm one of the co-founders, CEO at Zapier. Zapier is now helping over 300,000 customers automate their work. Some 10 million plus users. It has been 14 years in the making. So to your point, it started as helping people with integration. About 5 years in, we started working on workflow and helping people automate these more deterministic workflows end to end. And in the last couple years, it's all been about agents and AI and how do you sort of mix probabilistic workflows into the equation. So we are having fun helping folks do more with less, I guess, as the proverbial saying goes.
Yeah. Exactly. And I think that's something that's been a repeating topic here that we've talked about. There are these deterministic tasks, the things that must happen in the exact same order every single time in a reliable way, which is sort of what we thought about traditionally programmatic or automated or rules driven. There's lots of ways of thinking about a process oriented. But of course, AI adds all that variability, the things that required human cognition or creativity or variability, right? So let's talk a little bit about the automation component because I think people don't realize still how core a lot of those repeatable tasks are. So maybe for you, as you've seen especially in small organizations, teams that are under 20 or so, how are you seeing them specifically using automation to outperform organizations that may be significantly larger than them?
Yeah, we have a number of these companies in our customer base that have 20 or less employees that are doing, you wouldn't be able to tell from the outside looking in. You would think this is like an army of people getting this work done. Now, what I think separates these companies is they figured out how to operationalize automation for their core product and the core value prop they deliver. So it usually starts with a founder or an owner operator or maybe an early employee who's kind of like a project manager or a COO or operations lead. And what they tend to do is they take every single task that comes their way and they get really good at breaking it down and saying, 'Okay, what if we actually automated this?' That mindset is pretty different than what you saw in Silicon Valley in the 2010s where it was an era of blitz scaling and hire more people, figure it out later. These folks don't take that approach. They say, 'Hey, we're not gonna hire till it hurts. We're going to put automation in through and through.' I'm thinking of one company who even in their core product line, every single prototype that goes out the door starts with a zap. They're like, 'We're going to build a zap for this every single time.' And then that'll test, 'Hey, is this idea even a good one?' A number of those ideas scale on Zapier forever. Some of them, they go rebuild in their own codebase at a certain scale after they've proven out its value. Some of them don't work and then they're just happy that they didn't waste the time building it in a production way. And they've got this big old table where they're keeping track of all these automation experiments that they could go run. And so the end result is that they're scaling by just launching automations over and over and over again instead of hiring people at the end of the day. So it's almost hard to come up with a name for this type of organization because they sort of look and feel like an evolved species. It's not something I think most companies would recognize when looking at them because they do look and feel and operate quite differently compared to most.
Yeah, that's actually something that we've been struggling with here or grappling with, in that the existing terminology for entrepreneurship and for scaling doesn't really fit well with this new model. That's why we started using the term micro team because it's not really a small business. It's not really a startup in the traditional venture-backed high growth mode. And it's definitely not like a large enterprise. It's entrepreneurship. So for now, micro team seems to stick with the idea that it's much smaller than expected, but this idea of scaling through the power of leverage is this idea we're calling scale maxing, which comes from a bit of a Gen Z term, the looks maxing, grind maxing term, right?
Yep. Yeah. Yeah. And it's like this idea of, well, let's how much can we push the scale with the team that we got, maximizing, squeezing every little bit of value out of it. So it's cool that you're thinking about that as well.
Yeah, it is. You're right, these folks are odd. Like you look at them and they might have 20 folks in the org or something like that, but the revenue that they're pulling through, the customer bases they're pulling through, they're actually just much much larger. But they don't look like it when you actually go look on the inside. You're like, this doesn't look like a classic enterprise scale company. But in many ways, they're punching in that weight class.
Yeah, it's interesting. And I think because of that, every member of the team that they do have is highly critical and highly valuable, which I like. It's sort of felt in this Silicon Valley rapid growth, hire fast, and then fire fast phases that people felt a little more dispensable. We felt replaceable. But when you have these micro teams where everybody is really squeezing the value, everybody truly isn't replaceable. And I like that, that adds the value back to the human. Interestingly enough, I think also it's more fun to work on these smaller teams. Everyone just knows each other on a more intimate level. There's a deeper sense of ownership and responsibility. I think all of us have been on teams at some point that just got too many cooks in the kitchen and there's this diffusion of responsibility. There's not enough work to really go around and what happens is imaginary work starts to spin up. It's like it's not the most critical thing but you got to go find something important to work on and so you kind of go invent more things whether that's actually going to help the organization or not. So I do think constraints, like keeping the team small, makes all the work you're doing impactful.
I like that. So let's talk a little bit about some of those patterns that some of these organizations might use. You said one of these is the skill of identifying the high value repeatable tasks that they can optimize and squeeze. Maybe the first iterations or two or three aren't the best, but they're working quickly towards that. So this is a pattern maybe that you've seen because you've seen a lot of automations and you see a lot of things that work. So for those founders that are drowning in these repeatable tasks, when you look at these high performing users, maybe what patterns or systems do you see that others haven't quite yet figured out?
Sure. There's a couple ways that folks coach on identifying automation. The most basic one, which does work but I think limits your upside, is to simply look at your personal daily tasks. So you can go look at your calendar over the course of the last couple weeks and see what are the things I do every single day, every single week, and which of these tasks might possibly be either partially automated or fully automated. Then you can start to systematically go automate those bits. That'll probably help you with your own personal workflow and you'll improve that way. The second way is to then apply that for your team or your organization. Go look at the things that are tasks that maybe sit across individuals or teams and say, 'Hey, where are these handoffs that are happening and how do we actually go automate those end to end?' In both of these cases, you're automating work that you're kind of already doing. The next thing that I think is where you really see the big unlock is when folks are now starting to identify opportunities to automate work that you weren't doing before. These are when you're now solving net new problems. This is a problem that either you couldn't do it because there's just no way we could hire that many people and do it reliably enough, or it's just something at your scale where you feel like we just don't have the resources to go tackle that. And this is where I think folks start to really get a bunch of leverage. This process is more like what you would think an entrepreneur goes through. It's being very observant of their environment, paying attention to where there are customer problems or needs that are being unmet, where there are novel ways to go solve that problem. A lot of it is just about having lots of ideas and being very observant of the problems around you and then figuring out, 'Hmm, if I built a little thing, I could probably solve that problem in the shortest distance possible.' It includes this set of automation or this tool in and around it. The way I would coach folks on that is just get better at observing things. Get better at paying attention to the things in your world where you're like, 'If only this thing sucks, if only we could do X, wouldn't it be incredible if we could solve this problem, but by golly, there's just no way to do it.' And then instead of saying, 'By golly, there's just no way to do it,' step back and say, 'Well, what if we did this?' That aspect is harder to coach and teach people on, but the teams that figure it out are the ones that I think have the biggest opportunities.
Yeah, that's interesting. It's kind of funny. A lot of these ideas come full circle. We were back in the day when we were doing integration tasks, we're talking about business process management, business process re-engineering. You used to have to hire consulting firms to come in there and untangle your systems and figure things out. But a lot of what you're talking about is more of like these are soft skills. These are things that people need to learn how to do. It's ways of thinking. And it's something you're definitely not taught this in school by any means. And maybe this is inherent talent. Maybe just some people are more talented at being observant and distilling these things. Maybe that's what separates the high performers from the lower ones. Who knows? But I think you're definitely on to something here. And this is sort of a question I've asked a number of technology leaders like yourself, which is a related idea around planning. The world is moving so fast. It's really hard to come up with a one-year plan let alone a two-year plan. And the funny thing is, of course, technology firms like yourself, we're just so used to moving quickly that we don't think in those long terms. But then you go to an insurance company or a bank and they're talking about their two-year plan like, 'Wait a second, the world is going to be a completely different place.' This kind of ties into the idea of identifying these opportunities for automation. Really, it's about squeezing this time frame considerably down. So maybe from your perspective, how do you even think about planning in this environment where even if you ask some of these technology leaders what they're going to do in a year, honestly, they're not so sure either.
Yeah, spot on. So, yeah, getting into that. So, like, AI is really trending. AI is adding to the automation piece. We haven't even really talked too much about AI here, but what capabilities did you once assume were too complicated to automate that are really now suddenly possible?
Yeah, I think the biggest thing we benefit from with AI and specifically large language models is we can work with unstructured data in a way that you couldn't before. In the past, if you had big blobs of text, if you wanted to categorize things, if you wanted to make decisions based off of that with reasoning and logic, it just wasn't really possible or you had to have a fairly simplistic approach to even begin to attempt. And even still, you didn't get great results out of that. Nowhere is this more obvious to me than meeting recorders. We've seen the rise of meeting recorders in the last couple years. They're everywhere now. In the past, there was hardly anything that happened with meeting recorders other than you'd get the transcript back or the recording back. And then it was up to you to figure out if you want to do anything with it. But for most of us, meetings were these ephemeral things. You'd sit down, you talk to people, maybe someone would take notes. If you were particularly diligent, you had one or two action items, you went and followed up on those things. But beyond that, the discussion, the dialogue, any insights, they were kind of just left to human memory. But the reality is your meetings are chock full of great information that are highly actionable. So here are a handful of ideas that I have learned from our customers you can do with a meeting recording. One, you can use meetings to create coaching bots. So if you are a sales rep and your meetings are recorded all the time, you can have an LLM that's maybe trained on a particular sales methodology and after every single meeting, you can get notes: did you do good discovery? Did you do a good demo? Did you do this and that? And it can coach you on that stuff. Infinitely patient, available for every single one. Fantastic. Similarly for internal meetings, you can do something similar. There's this great book, The Five Dysfunctions of a Team. I run that on all my meetings to be like, 'Hey, how did you do against the five dysfunctions of a team?' Coming back to that sales call, well, similarly, if you're talking to a customer, one of the things you can generate on the other side perhaps automatically is a case study. If they're talking about why they value the product, you could again have an LLM say, 'Hey, structure this conversation in the form of our case study template.' It's a great way to get stuff out there. If the customer talks about your problem or solution in a new way, maybe they're using particular keywords, new vocabulary, new vernacular. You could automatically go generate a landing page that is using those keywords and then you could generate ads against those on Google or Facebook. So as you can see, there's all this context that sits inside of there that in the past would get lost over time. Most people just wouldn't do much with that. And if you did, you were probably in the top 1% of the 1% in operational efficiency. But I find that most of us are just too lazy to actually be that efficient with it. So that to me is where the most exciting new use cases are: being able to go work with this unstructured data and create interesting things from it.
Yeah, it's really interesting. I still think even now making effective use of these recorded meetings will still probably put you in the top 1%. For right now, but I do think that's going to change as people start to wake up and go, 'Hmm, there's more that can be done with this information.' That's good. Well, good. I'm hopeful because you want meetings to be productive. So outcomes like that make it more than just we all got together and said things and nobody can remember the next week what we just said. I'm hopeful as well. So let's talk a little more about these tiny teams that are punching above their weights. What do you think in terms of a capability that every micro team should adopt within the next 12 to 18 months? It's hard to think that far, but that you think maybe very few people are really doing today, but again, you see some of these outliers and you say, 'Oh, these folks are doing something really interesting and unique here.'
