Zapier's CEO Will Grade Your AI PM Skills Live

1. 0:00 – 2:39

   Intro

   1. AGAakash Gupta0:00

      Every PM is about to get graded on AI fluency. Zapier, Shopify, and many others already are.

   2. WFWade Foster0:06

      If AI was important in twenty twenty-six, it's just the standard expectation for every job.

   3. AGAakash Gupta0:10

      Wade Foster is the CEO and co-founder of Zapier. He wrote the viral AI fluency rubric that arguably kicked off this trend.

   4. WFWade Foster0:18

      There is still something to be said about really understanding the customer problem, really having some intuition around how to go solve those problems. And if you combine those, you get excellence. But if you just let AI kind of just do everything, you're probably gonna get mediocrity. You're gonna get what people call AI slop.

   5. AGAakash Gupta0:34

      What was capable last year that's now unacceptable? What does a PM that's transformative actually do differently on a Tuesday?

   6. WFWade Foster0:42

      The line we use at Zapier on slop, you can delegate the work, but you can't delegate the accountability.

   7. AGAakash Gupta0:46

      Looking at Airtable, now it's less than ten percent of that amount. For you at Zapier, you've been around since twenty twelve. Where does Zapier's business sit now?

   8. WFWade Foster0:55

      One thing that's unique about Zapier is the valuation thing doesn't matter as much to us.

   9. AGAakash Gupta1:00

      So if you saw me running a product team like this, how would you grade my output?

   10. WFWade Foster1:04

       So if I'm spotting things, like, are obvious to me and not to you, I'm like, "Ooh, that makes me nervous," right? And, and I'm like-

   11. AGAakash Gupta1:19

       Before we get into today's show, please take a second to check that you're subscribed on YouTube and following on Apple and Spotify podcasts. If you want access to all of my favorite AI tools, I've gotten them to give you an entire year of their paid plans. Check out bundle.aakashg.com for an entire year of Bolt.new, Airtable, Speechify, Descript, Magic Patterns, Linear, Dovetail, Arize, and Mobbin. And now, into today's show. I've been trying to figure out what AI fluency actually means for PMs inside of companies. How do product leaders, how do CEOs measure you? And I could think of no better person than Wade. Wade published what I think was the first AI fluency rubric online. Many companies modeled it. Since then, Zapier has updated their thinking. How did they update their thinking? What actually matters? Day-to-day, how is Wade actually grading employees? In today's episode, he's not just gonna walk through his rubric theoretically. We'll actually show you some AI behaviors, and Wade will give his take on, is this transformative? Is this unacceptable? He'll also talk to you about how these expectations have changed over time so that you can meet the bar at your company or exceed it. Wade, thanks for being on the podcast.

   12. WFWade Foster2:38

       Yeah, thanks for having me.

2. 2:39 – 6:53

   How Zapier measures AI fluency

   1. AGAakash Gupta2:39

      So I have been dying to do this recording. I think we've rescheduled a few times because I think you are the world's best person to talk to us about AI fluency. How do you guys measure AI fluency at Zapier?

   2. WFWade Foster2:52

      Sure. Might be most helpful to actually simply just show. Uh, so we have, uh, an AI fluency rubric. This, published March thirty-first, twenty twenty-six, is our updated AI fluency bar, uh, at Zapier. So this is the V2. Uh, and you can see here, we basically break things down into four categories. You actually don't see. There's a, the, you see three on the scape, the screen here, capable, adaptive, and transformative. We also have an unacceptable one, uh, which is, you know, just simply the bar that we choose not to hire at. Obviously, for any company, you can tweak and tune these to fit your needs. Uh, we felt it was really helpful for us to really name some of the skills and behaviors that, uh, help, uh, help people stand out in terms of, you know, their, their AI, AI fluency. And so maybe, you know, this is a product podcast, so let's maybe, uh, zoom down here to the product one. And, uh, I'll, I'll be the first to, to share, like this is the, the V2 that we've shared externally, but we've even updated some of these things internally since. Like, this space moves fast, and you do have to constantly be tuning and tweaking, uh, what you're doing. And so you can see here, you know, some of the characteristics that make someone unacceptable, capable, adaptive, and, you know, transformative, uh, at, uh, th- this work. And so, you know, in twenty twenty-six, you know, if you're using AI to, you know, do simple tasks, summarization, writing, looking up information, generating basic PRDs, things like that, um, you know, at, that's kind of table stakes, I think, for most companies at this point in time. And so, you know, we're usually looking for somebody that's operating at a, a meaningfully higher, higher, higher level. And so, you know, we want folks that have, like, a really structured appro-- uh, approach for generating specs, prototypes, things that they're gonna u- reuse and refine across projects. Um, you know, we want people using it to really tap into user insights, quant, qual, being able to operate at a scale that maybe was not prior possible with sort of humans. Um, you know, you should be able to generate, like, tons of different working solutions very rapidly. Uh, you know, so those are the types of things that end up being sort of table stakes for these roles. Uh, you know, I think if you're really trying to start to, to push the needle, you're starting to stretch into other types of roles. I think PMs, uh, are, you know, well-suited to become sort of like these generalist, like, super builders inside of an organization. And so that means you can tap into whole new skills, whether that's data analysis or, you know, marketing skill sets or sales skill sets. Like, you know, PMs are usually already decent at some of these things, but now you can get to, you know, eighty, ninety percent is good, and it makes you way more valuable sort of to, to, to be able to sort of like work up and down, uh, you know, sort of the, the, the life cycle of a, a project. Um, you know, I think- You know, a lot of this, as you sort of move up the stack, starts to be about systems building. Like, this is the really critical piece, is you're not just thinking about, like, how's this feature gonna work. You're really thinking about, how do I build this, like, pipeline of agents that takes in customer feedback, generates specs, starts to prototype solutions, ship full features. You know, if you've heard of things like software factories, like, I think this is where PMs start to have, like, a lot of values. You can start to think about, like, how do we, uh, build the system that builds the ultimate system? Uh, and that's where you start to get into this, like, transformative ca- ca- category, where it's like, wow, we've actually built, like, a product factory here. Uh, and we're really changing the way, you know, product works at a sort of, uh, fundamental level. And so, you know, these are the sort of four, like, stages or phases that we've sort of rubrik'd out. Um, but like I said, you know, I think you can adapt these to your company. You know, not everyone is, you know, uh, has the same standards as us. Maybe you have, y- maybe you're not far, far, as far along, and so you sort of have a different state. Or maybe you're even more advanced than us, and you're saying, "Hey, actually, for us, like, we need more people that are in these categories, um, to, to really push the, the envelope."

3. 6:53 – 9:17

   Where most PMs should sit on the curve

   1. AGAakash Gupta6:53

      So what is the distribution that you want to see at Zapier? What should-- Where should the ratings fall?

   2. WFWade Foster6:59

      For our product crew, like, we're, we're generally looking for folks that sort of have, you know, like, uh, you know, sort of the bulk of their skillset is probably here. You know, it doesn't mean that there's, there, they have places where there's gaps, like all of us do. You know, there's so much new stuff happening every day that there's new techniques and tactics that people haven't used. And so there's definitely people that are sort of in this bucket. And then, you know, w- we usually wanna see somebody that's, like, bringing, like, one example of something that they've done here. You know, most people are not hanging out at transformative every day. Uh, in fact, like, it's probably not actually helpful to be, like, here 100% of the time, because if you are, you're not actually getting work done. You're constantly just, like, tweaking your systems and way of working. And so, you know, you, you're probably hitting this on occasion. But I think kinda, like, for our PM org, like, you know, we're kinda hanging out in here, like, most of the time, uh, and occasionally running experiments to sort of, like, push us, push the envelope. And so that, that's kind of where I'd say, like, our bell curve sort of, you know, uh, sits around, is like, this is sort of the fat middle of the curve, and we have, you know, some folks in here and some folks in here. But, you know, not p- It's, it's-- I wouldn't label it as like, you know, as a person, you're this. It's, it's more like s- most of the time I'm this, but I have sometimes I've got some holes here, and I've, you know, sometimes got some things up here. Like, that, that's what it looks like more often than not.

   3. AGAakash Gupta8:16

      Hmm. That's an interesting way to frame it, that maybe you don't actually want to be transformative because you wouldn't have time to do work. What does, like, a transformative-- Do you guys do quarters or halves when you guys give performances reviews to folks?

   4. WFWade Foster8:30

      Uh, I guess our-- Let's see. Our performance review is in halves. Yeah.

   5. AGAakash Gupta8:34

      So what does it... Like, if you recall, or if you can recall, like, a transformative half from PM, what did that look like?

   6. WFWade Foster8:41

      Well, uh, you know, I remember, uh, at the tail end of last year, we had all these new, uh, you know, uh, models that came out, like, uh, the, the latest, like, Opus series, the latest GPT series, the latest Gemini series all came out, and the reasoning power was, like, so much better than before. You sort of went from, you know, hey, these AIs are, you know, kind of writing code alongside engineers to, over the winter break, basically everyone was like, "I'm not writing any code anymore." Like, "I'm very rarely writing code

4. 9:17 – 11:23

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   1. WFWade Foster9:17

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   2. AGAakash Gupta9:17

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   3. WFWade Foster11:22

      So alongside

5. 11:23 – 13:22

   How one PM built Zapier's company brain

   1. WFWade Foster11:23

      of that, an, a thing that we started to see a lot of folks doing, both online, but even inter- in- inside of Zapier, was building, um, these, like, second brains. Uh, and, you know, if you haven't done this, uh, you know, it's a pretty simple thing where you'll create, like, a-- At least it-- The way it started was, like, you create, like, a, a bunch of markdown files that, you know, might say, "Here's- Here's what I'm-- Here's my goals. Here's, here's the way I want you to work with me. Uh, you know, just have like a bunch of context. Um, you know, this is a project I'm working on, et cetera. And then, you know, you'd boot up a coding agent, and the coding agent would have access to all that context, uh, to, to go, you know, build projects with. And so maybe you have your di-design system in there, maybe you have your company strategy in there, maybe you have, you know, coaching files in there where you're like, "Help me be better at this." Um, you know, things like that. And so, you know, one of our product leaders said, "You know what? This second brain concept is pretty interesting, but, uh, it's limited if those are individual s- um, skills. This should be a company brain." And so, you know, he took it upon himself to say, "I'm gonna go build, uh, you know, out the sort of V1 of a company brain, uh, and you know, I'm gonna sort of put together, like, all this context that would help, uh, anyone in the company." But he certainly started with a lot of the product leaders and product managers and said, "Hey, we're gonna get everybody sort of using this, you know, second, second brain or company brain to, to go do the work." And I would say there was like... Y-you could sort of feel this, like, um, phase shift happen, where it was, like, not just him, but, like, every product person in Zapier kinda got like a jet pack put on their back, uh, when he sort of launched this system. And so that's a great example of, like, this moment in time where it was like, you know, the model sort of had this, like, l-lurch forward in capabilities and, you know, product leader said, "Okay, with these new capabilities, I can lurch forward the way we work as well too with it."

6. 13:22 – 24:43

   Grading PRD one, written with ChatGPT

   1. AGAakash Gupta13:22

      All right. So I want to try some PM artifacts. I've actually gathered some that I created this morning, and I want to put you on the spot. And what I really want to do, it's like the, the final rating doesn't matter as much as how does a CEO look at PM work products-

   2. WFWade Foster13:46

      Mm.

   3. AGAakash Gupta13:47

      ... PM using AI, or how might a particular PM who's in a company be being graded on this? So let's start here. What I thought of was, what if Zapier had an IDE harness for Claude Code? [laughs] Who knows if this is a good idea at all. That's why I wrote a PRD on this, and I want to walk you through this PRD as if I were a PM, and I'd love to hear your thought process as you're looking at this.

   4. WFWade Foster14:17

      Mm-hmm.

   5. AGAakash Gupta14:17

      Um, obviously, I've used ChatGPT here, and I've, I've given it a few prompts, so I have iterated on it. It's not, you know-

   6. WFWade Foster14:24

      Mm-hmm

   7. AGAakash Gupta14:24

      ... my first draft or anything. But, uh, I, I've included the overview. I said it's important for automation workflows, and y- we're uniquely positioned to solve this because of our thousands of integrations, right?

   8. WFWade Foster14:36

      Mm.

   9. AGAakash Gupta14:36

      And our deep knowledge about how workflows work. So we combine Claude Code with Zapier's automation platform. That's my pitch here. I feel like the problem is that you might write prompts in Claude Code, configure apps, deploy it. It's all fragmented. Claude Code can make mistakes with the API. And so what I wanted to do was create a better environment for building these Zapier automations. And I feel like the, the target is, you know, software engineers, founders. And so specifically for an engineer, as a developer using Claude Code, I want to build and test Zapier inst- automations without constantly switching. And so that's really the problem we're solving. We have this proposed solution where users can interact with Claude Code. A workflow might be that they have this workflow, and Claude could easily help them build it. We could test it. I've come up with some of the key features that we have here, and I won't go through too much more of the detail, but it'll have AI slop detection.

   10. WFWade Foster15:39

       Mm-hmm.

   11. AGAakash Gupta15:40

       You know, I've come up with a little bit of an MVP. Some metrics that I think, you know, leadership might care about is the number of workflows successfully deployed through the IDE as sort of-

   12. WFWade Foster15:50

       Mm-hmm

   13. AGAakash Gupta15:50

       ... our north star metric. Um, of course, developers might prefer Claude Code directly, but I don't think there's a huge build cost. And sort of my vision is Claude writes your automation, Zapier helps make sure it actually works. So I wrote this with AI. What do you think of my work?

   14. WFWade Foster16:07

       Hmm. Okay. So, uh, you know, it's interesting to think about how you would start to go, uh, evaluate this because, you know, p-part of your prompt to me was, uh, you know, how does this grade in AI fluency? But there's also a part of this that's just how do you grade the overall, like, product thinking that's sort of happening here. And so the first thing I notice is, one, I, I think this is actually a pretty interesting idea. Uh, you know, I think, you know, you sort of like g- like, good product intuition, you know, I would say is like, you know, p-pretty, pretty savvy here. It, uh, you know, recognizes that, like, there's this new way of building automations or this new way of building. There's some value in sort of having, like, the Zapier, uh, you know, connective library hooked up to Claude or Claude Code, uh, to help go build. And then, um, you know, one thing I didn't see you say here, but m-maybe, uh, maybe it was in it. I, I, I suspect it's in here. Uh, I couldn't read quite fast as you were going through this, was, um, there's a lot of value in sort of deploying these things and running them on Zapier, because Zapier can run them in a, uh, deterministic manner, which, you know, allows you to get better costs, you know, better accuracy, all that sort of thing. So there's a lot of stuff in here that I like. Now, where I think, you know, a, a sort of like AI-pilled, AI maximalist like product manager could go further would be in a couple dimensions. I think, one, um, why stop at the PRD? Uh, you know, uh, there's an opportunity to go build out, you know, the first prototype of what this thing looks like. Uh, and so let's go fire up, you know, your favorite, you know, coding agent of choice and start to, like, see what you can prototype and build. And now the point here is not for product managers to build production-level code. The point is that, uh, you know, seeing is believing, and it's a lot easier now for a product manager to, uh, bring some of these ideas to life. Uh, and so, you know, uh, th-there's that sort of, you know, a picture s- you know, says a thousand words. Well, you know, a prototype is, you know, that times 10, right? So I think that would be one dimension I wish I-- this could be, uh, you know, stronger and, you know, an AI-pilled person would sort of, you know, probably do something impressive there. I think the second dimension where I would try and strengthen this and this is... You know, I think you could do this sort of in a, you know, non-AI way, but certainly I would be using AI to help me, which is, uh, you know, let's go start to figure out, um, two things. Like, where is our customer evidence behind this? Uh, so however you sort of can find customer evidence, uh, I would try and find it. So I would look through, you know, the Zapier, um, you know, like Gong recordings or Zendesk tickets. Um, you know, I would go sift through like, you know, subreddits or, uh, LinkedIn or, you know, X and sort of find like, hey, where are people, like, complaining about stuff like this or expressing a desire for a thing like this to try and figure out, like, am I getting the shape of this product right? Um, now, like I said, you could do a lot of this stuff without AI, but AI's probably gonna make it a lot easier for you to sift through a mountain of data sources, um, that, uh, you know, you probably just wouldn't have been able to do in, you know, a short period of time in the past. Um, so I think that is, you know, a second thing you could do to sort of like really beef up, uh, the evidence, um, that like, hey, am I in the right direction here? Uh, like, I think this is a good idea or our customer is gonna think it's a right idea. And like, what is the pain point that they really care about? Um, you know, you pose the question like, "Hey, Claude could maybe just do some of this." So there is a little bit of a question around like, well, what is-- like, where is the unique value that Zapier brings to the table on top of it? And I think, you know, sifting through a lot of those customer details will start to like give, build, strengthen that intuition around like, ah, there is something here that, you know, is uniquely Zapier's to own, uh, and provide value on top of. Um, so those are the two sort of like obvious things that I would use to st- like would encourage somebody to strengthen, and I don't think that either of those things takes that much more time. Uh, in the past, they would've been things where it was like either a product would-- uh, a PM would've just basically, "Well, I can't build a prototype, so I, I just simply can't do it." Or with the customer evidence one, it's like, well, I can do that, but, you know, there's a question of like, before I go spend, you know, like a couple weeks doing it, I kinda wanna get some buy-in that this is like even directionally interesting. Whereas nowadays, you know, that buy-in step can happen way later. You can just go so much farther. And so by the time you're sort of asking, you know, me or somebody else in the company to be like, "Hey, let's go put some oomph behind it," you know, you've built like a mountain of evidence behind it that makes it, you know, a lot more likely that I'm gonna say, "Yes, let's go for it." Or maybe you've already figured out yourself like, actually, this is just a really bad idea. Like I, I, I thought, I thought my intuition was good, but, you know, I put some effort into it, and I just can't find something that I like get super excited about, and so you can shelf it. Uh, and so that's where I think like, you know, an AI-powered PM just has these like superpowers that you didn't have in the past.

   15. AGAakash Gupta21:15

       Did you guys realize you were getting a master class in how to write good PM documents? It's not just AI fluency. I think Wade just brought up a couple really, really important points around it's not just the PRD. And what I tried to do, [chuckles] I tried to engineer this document so you would rate it as like a capable in 2024-

   16. WFWade Foster21:34

       [laughs]

   17. AGAakash Gupta21:34

       ... but almost like an adoptive or unacceptable in 2026. Do you feel like that's fair?

   18. WFWade Foster21:40

       I think so, yeah. Like I think if someone came to me with this like, you know, in 2026, I would sort of feel like, uh, it feels a little old-fashioned, like is sort of the answer that I would have. It'd be like, yeah, uh, you know, some good product intuition, some, some good thinking, but like gosh, you really could have gone a lot further. Like you, you really... And, and I would almost want to-- I'll tell you what my instinct would be. My instinct would be like, just give me the doc, and I'll start go doing some of these things.

   19. AGAakash Gupta22:07

       [laughs]

   20. WFWade Foster22:07

       Like I'll literally just take your PRD and like s- you know, throw it into Cursor and be like, "Hey, bui-build this," [laughs] you know, for me and see what happens. And you know, that feels like, you know, I, I think, you know, the way that I would sort of... H-here's an interesting like rule of thumb. Like you know, you probably want to be, in your discipline, you probably want to be farther ahead than your CEO is. And you know, I, I would say, you know, my AI fluency is like probably, you know, adoptive in most places. But you know, what it means for me to be AI fluent in the PM job or the marketing job or the engineering job, like I should be behind you. Uh, and so if there's things that I know that you don't know, like that, that's probably not a great signal. Uh, you should be further ahead than me because you're-- you wake up and breathe this stuff all day, every day. And so if I'm spotting things that, you know, like are obvious to me and not to you, I'm like, ooh, the, the-- uh, that makes me, that makes me nervous, right? And, and I'm like, "Hmm, h-how do we go fix that?"

   21. AGAakash Gupta23:12

       Okay. So I think we're aligned there. And one other thing I would just pull out as an insight to triple click for everybody who is listening is it's not easy to just separate AI fluency and good product thinking. They almost come together in a sense in this era. Like to do good product thinking, you really need to have gone and looked at the Gong calls. You need to have gone and looked at the Reddit comments. And now AI can help filter half of that for you. And so-

   22. WFWade Foster23:44

       Yes

   23. AGAakash Gupta23:44

       ... you really need to put those two skills together.

   24. WFWade Foster23:47

       Yes. Like we were talking before the call about AI slap a little bit. And so there is a version of this where you could do all the things that I said, which is like, oh, just take this PRD, slap it into a coding agent, have it build the first prototype. You could sort of, sort of have AI do all of those steps. But out- the output you could come away would be just, like, pretty mediocre and unexciting. And so this is where the human, like, a lot of people call it taste, judgment, like whatever, you know, whatever term we're calling it these days, really does matter. And so, you know, there is still something to be said about, like, really understanding the customer problem, really having some intuition around how to go solve those problems. And if you combine those, you get excellence. But if you just let AI kinda just do everything, you're probably gonna get kinda mediocrity. You're gonna get what people call AI slop. You're gonna look at it and go like, "Eh, this is not... Like, I'm not excited about

7. 24:43 – 29:55

   Slop cannon or turbo brain

   1. WFWade Foster24:43

      this."

   2. AGAakash Gupta24:43

      Speaking of slop, I wanna know what your take is on this framework from Dan Hockenmaier over at Fair. If you don't have good judgment and you use AI, you can become a slop cannon.

   3. WFWade Foster24:54

      Yeah.

   4. AGAakash Gupta24:54

      But if you have good judgment and you use AI, you can become a turbo brain. Is this the right way to think about it?

   5. WFWade Foster24:59

      Uh, I mean, it's definitely funny and evocative. I, I think it's a reasonable framework, honestly. Uh, I can't think of why this is not-- I can't think of why I would sort of have an, uh, an objective to, to this. Like, I, I can think of folks that I've worked with who are using AI and have exce- ex- exceptional judgment, and just watching them work, you're just like, "Wow, this is, this is incredible to, like, watch this person work." You're, you're... It's almost like you're, you're witnessing a new species being invented. Uh, and then I've also seen folks that are using AI a lot but do not have good judgment, and you know, it's... There's this old saying, like, kinda like in the social media wars around, like, uh, disinformation, where it's like, uh, you know, "A lie, uh, can go around the two, the world two times before the truth gets out of bed." And I feel like the folks without good judgment who use AI are a little like that, where they can just generate so much stuff that, like, you're just trying to, like... It, you know, it takes so much just to kinda, like, swat it out and be like, "Ugh." Like, get, uh, you know, I, I... That's not, that's not what I'm looking for, not what I'm looking for. And so it actually ends up being, in some ways, more challenging to work with those folks than maybe even, like, the bottom left corner, where it's like doesn't have good gen or doesn't use AI. Well, it's like, well, at least, at least you're quiet, right? [laughs] Like, uh, so uh, you know, it's, it's an interesting framework too. I'd probably have to think a little bit more about some of the pros and cons with it. But on the surface, I'm like, "Yeah, I, I feel this." [laughs]

   6. AGAakash Gupta26:25

      On my own team-

   7. WFWade Foster26:25

      There's a reason it probably went pseudo viral. [laughs]

   8. AGAakash Gupta26:28

      On my own team, I find that, like, when somebody sends me something that might fall in the slop category, they're basically-

   9. WFWade Foster26:38

      Mm-hmm

   10. AGAakash Gupta26:38

       ... they didn't exercise the judgment on their own, and they're passing that responsibility to me. Like, they're like-

   11. WFWade Foster26:46

       Mm-hmm

   12. AGAakash Gupta26:46

       ... saying like, "Oh, this might be good. Can you judge it?" Right? And that's like kind of the opposite of what you wanna do when you're moving up a corporate hierarchy, right?

   13. WFWade Foster26:53

       Yeah.

   14. AGAakash Gupta26:53

       You wanna give people filtered information that is quality versus, "What do you think of this?"

   15. WFWade Foster26:59

       Yeah. I, I think, you know, there's, there's almost like some etiquette that I think the workplace is trying to iron out around this right now. Uh, you know, hang on. I talk to a lot of folks that are sort of dealing with this like, you know, the rise of slop internally. And um, uh, you know, I think some of the things we are starting to do is, like, be really honest upfront around like, "Hey, what's, what level of effort has been put into this yet?" And so, you know, when I share a document, I'll say like, "Hey, um, you know, obviously I have used AI to help draft this. I have done a quick skim through and so, like, I've removed sort of like the most obviously bad stuff inside of here. But you know, maybe I haven't given it, like, a thorough once-over, but I wanna share anyway because I think speed is really important now, and I think I've gotten this, I've gotten some ideas out there, and I want you to take a look at it," right? So that might be one thing I will do. Um, or I might say, "You know what? I think this is excellent. Like, I have really poured, you know... So I w- I stand by every statement, every sentence, like, has been, like, impeccably reviewed by me." And so we, we kinda have, like, these stages of, like, when we're sharing these things to help the reader understand, like, you know, what's the level of, like, effort that's sort of been put into this. Um, and you know, I do think it's okay at times to just share, you know, what might be pure AI slop, but I think you gotta, like, set the expectation to the reader to go like, "Okay, how much, you know, uh, uh, how much should I like... Like, what's the quality level that I should expect out of this?" And I think that helps. So like, I, I don't know. I, and I'm not sure that we've totally perfected this, to be honest. But the, the place that is really painful is when you sort of do try and pass it off as, like, really good, but then the, the reader can just, like, quickly tell, like, you, you're just... You, you literally put no effort into this and now you're making me do the task. And it's like, you should've just asked me to just do the job anyway [laughs] versus try and pass it off as your own.

   16. AGAakash Gupta28:48

       So one thing that really surprised me so far into this podcast that I definitely wasn't expecting coming in was it sounds like it's okay to use some AI. It's okay to have a little bit of slop if you're going for speed. It's okay to not always be transformative with AI as long as you're upfront and transparent about it.

   17. WFWade Foster29:09

       Yeah, I think so. Like, I think these are, these are tools, right? Uh, and you know, a lot of it depends on the context. You know, if you're putting out an external product for your customers, like, there's a different standard for that versus like, "Hey, I got this one quick and dirty task over here," and, like, the level of quality n- required for that is maybe different. Uh, and so, you know, a lot of it comes down to what's on Dan's right-hand side, has good judgment. And so, y- you know, judgment is like, you know, kind of the ultimate, in a lot of ways, it's like one of the main critical skills right now in the AI era, is like you've got, you gotta turn your brain on. Uh, and if your brain is on, you're probably gonna, you know, mostly find yourself in like a good camp. But if you sort of turn, turn your brain off, you're probably gonna find yourself

8. 29:55 – 38:03

   Grading PRD two, prototype plus customer evidence

   1. WFWade Foster29:55

      struggling.

   2. AGAakash Gupta29:55

      Awesome. So let's go review another work product that I've prepared. I think we can safely say the last one, we would probably not give that a very high rating in 2026. Let's go check out another one-

   3. WFWade Foster30:06

      I certainly would not. Mm-hmm

   4. AGAakash Gupta30:07

      ... that I worked on before this.

   5. WFWade Foster30:10

      [chuckles]

   6. AGAakash Gupta30:11

      Uh, and I'm nervous now that it might get a low rating, but that's the point, right? So let's go see what rating I get. I actually decided to use the same feature so that we get, it makes it easier for us to really compare. And so it's, again, it's like a Zapier harness for Claude Code. I predicted [chuckles] we should probably start with a prototype. So-

   7. WFWade Foster30:31

      [chuckles]

   8. AGAakash Gupta30:32

      ... I did come up with a prototype here. Here's what I have for my next layer. I actually did start with a prototype, and I tried to create some Zapier branding even. [chuckles]

   9. WFWade Foster30:43

      Oh, nice.

   10. AGAakash Gupta30:43

       Uh, your agent has the connections, it just can't reach them, is kind of my pitch, right? Since we hold authenticated access to 8,000 plus apps, I think even more now, what would it look like if a coding agent could actually use them? And so the whole idea is we just Claude plugin install Zapier, Zapier Connect. We could approve a Slack message. We'd start to get this exposed area. We could even send out things like Jira delete issue, and all that happens so incredibly fast. And the whole point is that it found six connections, three were selected. It looked at 14 custom Jira fields. It showed us which tools across our CAP, which ones were pre-approved. It gave a preview of the payload. There was this thing that I built in here, it happened really fast, where the Jira delete was refused.

   11. WFWade Foster31:39

       Mm-hmm.

   12. AGAakash Gupta31:40

       So what did we do then, and why? Well, it was a destructive action, and so it was flagged. And so that's one of the things that our harness would be able to add on that, like, maybe a normal Claude Code wouldn't, because we have a lot of enterprise customers. We could even replay it in Zapier history. And so the whole idea here is that this harness would be much more powerful, and this is where I started my PRD. So I'm gonna keep going and just explain a little bit more the PRD behind it too, and then let's get your feedback. So now, if I show the PRD, this is gonna be a markdown file instead of just a chat window this time. So we just went through the prototype. Basically, the whole idea is you just install and connect once. You just saw that. It has a policy file. You just saw where it de- it denied an action. The loop we're talk- we're really talking about it unlocking is, let's say there's some Sentry issue. It can go read it, it can go edit it, it can go create the Jira comment, it can go post a Slack message. All of that can happen using Zapier's connections and Zapier's policies. And so somebody who is super technical can build it or somebody who is not technical. We already went through what this is deliberately proving. And so we'd, since we talked about this hypothesis, I won't talk about it too much, but I've written it in kind of like a slightly tighter way this time, and I tried to use a little more evidence. So I did predict that we needed to use some evidence. So I've added in, like, some Gong information, like what I s- from 47 calls from February to July, and I found that agent tooling came up unprompted in 34 of these 47 calls. This is just an observation. On Zendesk, I saw we had 312 tickets tagged MCP or AI agent. In our community Discord, over 1,800 posts mentioning the MCP, and our design partners, we had nine interviews where they had built an MCP server. Now, what did all this information show? What it showed is the bottleneck is permission, not connection. It also showed that too many tools make agents worse, and users already know it, and that there is a real tail. So my hypothesis with the little six design partner pilot that I ran was that devs will let an agent perform writes to production systems if the gate is good. I wasn't sure if this was gonna be true, and I did find evidence to support this. Five of six enabled at least one pre-approved write. I went through several other hypotheses and ultimately looked at it across our strategic fit, and I came up with this idea that we do a Claude plugin. And this plugin I feel is really a harness, not a connector, and I've gone through a little bit more detail on that, including the metrics, the risk. And what I think I wanna get your permission for in this meeting is that we go through 10 design partners now. We do a legibility bake-off. We start to look at security. So if you approve this, then we'll plan on kind of going forward with a Q4 beta on this project. What do you think of my latest work artifact?

   13. WFWade Foster34:54

       [chuckles] Well, uh, I mean, based on the critique I gave you in the last one, you basically nailed the two things I called out, which was, this should be a prototype, and where's the evidence? So, like, obviously, right off the bat, like, this is so much stronger. Um, in fact, it makes me even wonder where I'm like, is Akash actually running this live transcript into a coding agent, and it's live fixing this stuff? Which I have seen people do, uh, at Zapier, and that is always, like, feels magical, where it's literally you're just taking, like, what the person is telling you, and you're literally feeding it right back to them. And so when they see it come up, they're like, "Oh, great. That's amazing." And so, uh, I don't know if that's what you did or if you just anticipated that that would be my feed- feedback and, you know, guessed it on the way. Either way- Like, that is the magic of like, you know, good product judgment. Uh, so yeah, I think y-you, you sort of immediately cleared those things up. The next thing, uh, that is honestly where I would push you is the ask. You say, "Hey, I, I wanna prove this. I wanna ship, you know, uh, I wanna get these design partners, and I wanna get to a Q4 beta." This is where I'm like, why are we waiting for Q4? Like, you've already gotten all this far, like, can you do it faster?

   14. AGAakash Gupta36:10

       Mm-hmm.

   15. WFWade Foster36:11

       Uh, and I think this is one, again, one of the things that's pretty magical about these AI tools, is you can go from zero to design partner exceptionally fast. And so, you know, if we're talking Q4, that's, uh, October, and it's like, well, shoot, you got, you got five weeks. Like, you know, what are we doing for five weeks? You might be able to get there a lot faster than that. Um, and so that would be the main thing I would start to push on, is like, how do we get these iteration cycles to be going a lot, lot faster? But by and large, like, this is much better than before.

   16. AGAakash Gupta36:42

       Awesome. And I'll just note out a couple things. Or like, what would you give the final rating on this?

   17. WFWade Foster36:47

       I, I think this is like, like this, this feels to me like solidly adaptive. Uh, like I, I would be very happy to have like this caliber of PM work sort of across Z-Zapier at this moment in time. I do think there are, you know, like the thing, if you were actually like live listening to my feedback and feeding it back in, like that's an example of where I've started to see some people doing it, but I don't think that that's a tactic that's like widely used yet. That's starting to look pretty transformative. So if you were doing that, like there I'd say like, "Hmm, nicely done." Uh, but by and large, this is like very solidly adaptive, I would feel like.

   18. AGAakash Gupta37:22

       Okay. I was going for capable. I didn't make it. The only thing I did, uh, live was I added in-

   19. WFWade Foster37:28

       Mm.

   20. AGAakash Gupta37:28

       ... like really clearly what I got from Gong, and so you can even see that, [chuckles] that prompt that came in just a few minutes before.

   21. WFWade Foster37:37

       There you go. [chuckles]

   22. AGAakash Gupta37:39

       Um, to say like, pretend, should pretend looked at Gong calls, [chuckles] Zendesk tickets.

   23. WFWade Foster37:43

       Zendesk tickets. Well, that, that's what the dead giveaway was, was like y- the, it listed out Gong and Zendesk, and I was like, "Those are the tools I cited."

   24. AGAakash Gupta37:51

       [chuckles]

   25. WFWade Foster37:52

       Like, I was like, I, I think this is an AI like hyper-listening to me. Um-

   26. AGAakash Gupta37:56

       So-

   27. WFWade Foster37:56

       ... because you can kinda, you can kinda tell where it's like AI just has that hyper-specificity to it, uh, a lot of the times.

9. 38:03 – 46:07

   Grading PRD three, the full PM agent stack

   1. AGAakash Gupta38:03

      So the first one was somewhere between adopt-- unacceptable and adaptive. This one hopefully is somewhere between adaptive and capable. Let's see-

   2. WFWade Foster38:11

      Mm

   3. AGAakash Gupta38:11

      ... where this last one lands.

   4. WFWade Foster38:14

      Mm. [chuckles]

   5. AGAakash Gupta38:14

      Where you can kind of see my agent title kind of gives it away of what I'm trying to achieve, and then what we're seeing-

   6. WFWade Foster38:21

      Yeah

   7. AGAakash Gupta38:21

      ... is if Wade actually feels that, which I would say for my last one, he didn't give it an outright capable. So that shows you guys that the bar for capable, like even though I built this inside a pretty advanced Claude Code harness, I think the writing was quite a bit better than the last one. There was pretty good evidence. There was a pretty decent prototype. There's still a pretty high bar for capable. So let's see, can I hit transformative? So what I did here is I created two images to show, um, what my agent stack looks like. So if I go into here, it looks like it's, this is my agent stack. And so the whole idea is that I have this five-layer sort of architecture, where I have these skills for our team's recurring work, like PRD, prep, eval, recall, ingest, impact sizing, launch checklist, weekly review, and 37 more. Then we have this orchestration layer where sub-agents fan out in parallel. So there's engineering, design, exec, legal, UX, trust and safety, and skeptic, which argues everything shouldn't ship, because we know like-

   8. WFWade Foster39:34

      Mm-hmm, mm-hmm

   9. AGAakash Gupta39:35

      ... we don't want future bloat. Layer three is the tools and MCP. So of course, we use Zendesk and Gong, which was, that was the only update I made [chuckles] once I heard it from you. Reddit, I don't know if you guys use Amplitude and Linear, but those were the assumptions I made in terms of analytics and ticketing. Figma for design, although maybe you guys are all into cloud design now. GitHub and Chrome. And then I think this is like the most important thing, is that there's this deterministic enforcement in this environment. Um, and so what happens is it will post any tool use, it will reject a memory file if the evidence has no source. And so everything that we put into memory will have really good sourcing, and it will stop the session from ending with our brain being dirty. So the brain is like constantly updated, and that feeds into this memory layer, where we have-

   10. WFWade Foster40:33

       Mm-hmm

   11. AGAakash Gupta40:34

       ... all these sourcing of everything we're learning in product across the, our product team. We have this ingestion, and automatically our agents are creating, these are the hypotheses that are coming, let's say, out of Zendesk plus Gong plus Reddit. These are the decisions that are coming out of, let's say, Linear tickets and GitHub PRs. This is the research that we found from Gong and Reddit. These are what the stakeholders are saying from meeting notes. So this is my agent setup. This is part one, and there's one more thing I want to show you before you give me my rating. So the second part is like the auto pipeline that I've created around it. So I basically have a, a loop running nightly. So we take our raw customer signals, then we have these auto agents that run on a nightly cron job. So th- I call this the triage swarm. They're gonna dedupe and cluster by job. They're gonna, of course, populate our source folder, which hopefully you understand now why that's so important. They're gonna tag things as observations or interpretation or a hypothesis. They're gonna match things versus open hypotheses and flag contradictions. So overnight, for example, we might get like nine clusters of in- insights from all of our ignal- signals in. Maybe two of those are new. Like maybe something came up on a Reddit forum. Maybe one even contradicts a bet made in March. All of that, the triage swarm would just identify for us. Then what happens next is using the memory layer, I would come in as the PM and I would say, "Do we, do we promote this?" Right? Are there independent sources? Is it just one person on Reddit? We don't care. But is Reddit and our Amplitude data showing it? Maybe then it's relevant. So in four to five minutes, I look at that. The system itself is gonna help me document the hypotheses and decisions. And then I think this is the part that hopefully makes it a little more powerful than what I've shown before, is we have this auto-build system. So each step is gonna need the layer above, but first it starts with a quick two-page PRD. Then it does a PRD review panel. Then it creates the prototype. Then it creates the evals, and then it creates the code first draft. We get that with the prototype link, the user tests, the draft PR, and the linear tickets, and that's when we have the next human gate. So human gate one was, do we care about this build chain? Human gate two is, do we merge it? And if not... And once it's done, we put it back into the memory. And there's some hooks that run it all, but the idea is that we can go from, let's say, a 10-day development process to a two-day development process. So if you saw me running a product team like this, how would you grade my output, Wade?

   12. WFWade Foster43:22

       This is definitely starting to, like get into the transformative territory. Like, this is just not how, you know, uh, product and software was built, you know, three years ago. Like, not even close. Uh, it is a totally different way of working. Um, you know, it, it looks a lot more like a factory, right? You're, you know, you're sort of saying, "Hey, my job as a PM or an engineer," or whatever your role is in this system, "is not to do each of these individual tasks." You've set up agents who are handling these tasks, and now your job is to actually audit the system. Like when the agent fails, okay, why did the agent fail at that task? You know, if you think about like a factory, right? Um, if a factory produces a failed widget, what does the factory person do? Do they like try and like individually fix the widgets? No, not really. They just sort of discard that batch, and they go back and look at the machine and say like, "Why did the machine generate these failed widgets? Like what, what's, what's going on?" And they fix that. And so, you know, this is where the job is kind of shifting to. It's like, oh, you know, instead of having human machines that are sort of like stamping out, you know, each step of the process, we're replacing those. And now the job of, you know, the humans is to sort of audit the overall system and say, "Hey, is this working or not?" It's a very different way of running a software and product team. Uh, now the question that I think all of us is trying to figure out is what is the right way to run this factory? And that's where I was like listening intently to see like, "Hey, how are you designing your system here?" Because I think it's, it-- Like I talked to a lot of folks building these types of things, and I don't think there is a consensus yet on like what is the exact best way to run these loops. Um, for example, the thing I was trying to figure out is like, where are you putting those human gates, and why are you deciding to put those human gates in those places versus other places? Um, maybe this is the correct place to put them, maybe not. Maybe you wanna actually take the h- the first human gate out and say, "Actually, I, I wanna kick off coding agents for everything, and I'm only j- and then I'm gonna review all the stuff that sort of comes through." Maybe you don't wanna do that because you think actually like a lot of these things are burning lots of tokens and we're spending a lot of money on things that could be wasteful, and so it's worth it to have a human gate there, even though it might slow the overall system down. Um, but those are things that like I think a lot of teams are trying to figure out is like, "Hey, is this the right way to, to do this?" And candidly, a lot of people aren't to this yet. Um, but y- you know, it is becoming more and more common, so you do see it. Uh, but I think the exact design of this l- this, this loop is what I see a lot of teams trying to like scratching their heads on, trying to figure out like how do they get it, get it working, um, as best as possible. So like this is starting to tick into the, the, the transformative

10. 46:07 – 48:17

    Why not every PM should build the factory

    1. WFWade Foster46:07

       tick- the bucket.

    2. AGAakash Gupta46:08

       Awesome. So if a PM really wants to get that rating, although you said at the beginning that it, you don't actually need to, right? Like maybe if you're in the transformative, you're too focused on the AI tools. But let's say somebody's-

    3. WFWade Foster46:21

       Well-

    4. AGAakash Gupta46:21

       ... manager has told them, "You know, you should, you should be going for that transformative rating." If-

    5. WFWade Foster46:26

       Mm-hmm

    6. AGAakash Gupta46:26

       ... in twenty twenty-six they start to build a system that operates like this, that actually works, they are getting to that transformative level?

    7. WFWade Foster46:33

       Yes. Well, and the thing that I would call out is at any, at, at a small company, like if you're the only PM at the company, then yeah, you're probably building out a system like this because who else will do it? You have to be the one that does this. But if you're getting to company of Zapier size, where we have, you know, quite a few PMs working here, not everyone's job is to sort of come up with this thing that redesign the system. You probably have a team that's saying, "Okay, I'm gonna sort of go build this." Uh, or maybe we've got a couple teams doing a few variants of it, and then the where the rest of the PMs come in is like, "Okay, now help me figure out how to run this system," right? And so, you know, you've got a handful of folks that are sort of in the transforming part where they're like, "Okay, I gotta go sorta re- redo all this stuff." While in the meantime, you know, we've kinda got some PMs that are sorta running the old standard playbook, uh, and you know, occasionally sort of coming in and being like the user testers for like this new way of working. Uh, and you can sort of parallel process like, uh, you know, this, this new way of working. Uh, and so, you know, it, it sort of just depends a little on like how your organization is set up, but that's where I look at it. I'm like, I don't need all of my PMs to sort of drop everything and rebuild the system. I don't want, you know, I think we have like something like thirty or forty PMs in Zapier. I don't need thirty systems of this loop running. Like I actually want like one sort of way of doing this stuff. Or maybe, maybe I want a couple, like depending on, there's a few different jobs inside of Zapier, and so they might need to work like slightly differently, um, for these different jobs. Um- But, but the goal is not, like, everyone runs their own mini version of this. There is a z- sort of like Zap-Zapier product factory, uh, that does a lot of this.

    8. AGAakash Gupta48:13

       All right. So now you guys have gotten the roadmap. You

11. 48:17 – 57:06

    Wade's robot staff, from morning brief to scribe

    1. AGAakash Gupta48:17

       understand as a PM how to rate on AI fluency. I wanna see a little bit more of Zapier's internal sauce. Can you show us a little bit of your internal agent dashboards and how you guys are starting to work towards these ways of working?

    2. WFWade Foster48:32

       Yeah. Maybe let me just show my, some of my, like, individual use cases. Uh, this is what I do the most of with, uh, a- agents today. So these are not, like, Zapier production systems. These are just, like, Wade personal agents. Um, and so I've, you know, built out, like, a little, uh, dashboard here that I can sort of show off some of the, um, you know, uh, s- simple agents that I have set up, uh, that sort of, you know, kinda span, uh, the gamut of, you know, simple use cases to maybe more sophisticated. Um, I have -- I, I bucketed them into, like... I, I had my agent build out this, this demo, uh, page for us. Uh, but I've kind of bucketed them into a few things. I've got my robot, uh, staff. So these are, like, actual agents that are helping me run my, like, day-to-day systems. I have this, like, CEO CRM. This is sort of a lot closer to, like, kind of the, the production agent that we showed off just now. Uh, I have this AI that argues back. This is kind of like a simple thing that you can do, and you probably should do. You know, it's, it's akin to the skeptic that you sort of set up in your, your, uh, uh, uh, product loop that you have. And then I have just a bunch of executable skills that I do for, like, you know, real-time assistant stuff that's helping me with, like, a whole variety of cases. Um, maybe what would be most interesting is we could sort of poke into the robot staff first. What do you think?

    3. AGAakash Gupta49:50

       Yeah, let's do it.

    4. WFWade Foster49:51

       So the robot staff. So, you know, here's five of the more commonly things that I have set up. Um, you know, the one that I always sort of suggest for folks who are just getting into this, the place to start, morning brief. It's kind of a classic. Uh, it's, uh, you know, pretty simplistic to set up. You hook up an agent to your calendar, your inbox, your Slack, all that other s- sort of stuff, and then just say, "Hey, I want you to go build out, um, uh, a daily brief for me every morning." Very simple place to start. You know, especially if you're not used to building agents or not used to sort of connecting it to tools, it is a very easy one to do. Uh, I have mine run at, you know, at six AM every morning. You can actually see, uh, how it runs, uh, inside of Zapier. So the nice thing is I have this running, uh, on Zapier, and, uh, what is handy about running these workflows on Zapier versus, you know, having, uh, you know, CloudCode or Codax or any of these tool run them is that Zapier's gonna run them deterministically. So you can see it's, you know, kicking off at six AM every day. It's fetching these calendar events. This is not an agent running this. This is code. Uh, so you can actually poke over here and see there's code that's running a lot of this stuff.

    5. AGAakash Gupta50:57

       Mm-hmm.

    6. WFWade Foster50:57

       And the reason you wanna run these things deterministically is that it's reliable. It runs the same way every single time, and it's way lower cost. These steps, none of this is burning tokens. You only burn tokens right here on this stage where it's trying to summarize and, like, actually draft, uh, the daily digest. But then when it posts to Slack, again, that's just a sort of straight up, uh, API call that it's doing. So, uh-

    7. AGAakash Gupta51:22

       Can I play devil's advocate here just so I, pe- we can understand how people should engineer this? Because I think this is actually one of the most important agents people need to get, right? Couldn't we, this miss out on some context because it just has Google Calendar?

    8. WFWade Foster51:36

       So, uh, a lot of what's, it's actually doing here is, uh, the, it's in the code step, but it's, like, h- hitting, um, my to-do list. Uh-

    9. AGAakash Gupta51:45

       Mm-hmm

    10. WFWade Foster51:45

        ... it's hitting, um, ins- inside of Calendar, it also has, uh, a lot of times there's, like, documents added to it, so it's clicking through those links, fetching those documents that are linked to them as well.

    11. AGAakash Gupta51:55

        So it has that power. Got it.

    12. WFWade Foster51:57

        Exactly. Uh, it has access to, um, what else did I give-- Do I have it, uh, have it on? Uh, I, I mean, I think Calendar and, and, like, your, your to-do list is probably, like, the two biggest things you wanna give it access to.

    13. AGAakash Gupta52:11

        Mm-hmm.

    14. WFWade Foster52:11

        Um, but it can sort of click through links and click through attached assets and things like that and then sort of summarize those. Um, so that's where it's, you know, y- you know, having these sort of, like, quasi-deterministic, uh, agents that can also sort of fall back to using a more, like, agentic loop, more, like, inference are really powerful. You get, you know, determinism where you care about it, but you get the power of, like, an agent reasoning through the task where you need it most.

    15. AGAakash Gupta52:35

        Mm-hmm. And I think the, probably the best thing that I've seen with Zapier is you can actually prompt an AI agent to create these workflows for you.

    16. WFWade Foster52:43

        Totally.

    17. AGAakash Gupta52:43

        So you don't actually need to code it yourself.

    18. WFWade Foster52:45

        Exactly. In fact, these, the, uh, are built inside of, I use Cursor, and so I'm mostly just talking to Cursor and have them build them, but then I'm sort of deploying it to, to Zapier to run. Uh, and so that way I can close my laptop at night. Uh, I can have it run deterministically. I don't have to, you know, be doing a lot of the, um, you know, kinda clunkiness that a lot of these, uh, you know, uh, agent products make you do right now because everything's running locally, and it's running, you know, you're burning lots of tokens, um, to do it.

    19. AGAakash Gupta53:12

        Yeah. It's like a-

    20. WFWade Foster53:14

        Um-

    21. AGAakash Gupta53:14

        ... managed automation in the cloud, essentially.

    22. WFWade Foster53:17

        You got it. You got it. What else do I have? This is, so, you know, a- as much as I tell people to start with the morning brief, um, 'cause I think it's a simple, easy place to start, I actually think it's only modestly valuable. My favorite is the scribe, which is, uh, I have this set up at the end of my day. You can also run it after meetings, but, uh, you know, in my case, I'm having it run at five PM. Uh, another way to think about this is this is the daily recap. The daily recap, way more valuable. So this thing loops over all of my outstanding emails, all of the outstanding to d- like, save for later messages I have in Slack, and the biggie, loops over all of my Granola transcripts, and it sort of sucks out and says, "Here's all the things you need to complete, uh, based on today, and I'm gonna go ahead and draft- Uh, anything that you need for me. So I'll actually draft the follow-up emails. Like if, you know, you and I were talking and you said, "Wade, can you intro me to so and so?" Okay, great. The Granola catches that and says, "Okay, uh, we're gonna go ahead and draft a follow-up email for this person." Or, you know, "This outstanding action item is in your to-do list. Do you want me to go ahead and take a stab at authoring these things?" And so the scribe catches all of that stuff from the day and helps me, like, do the end-of-day cleanup that used to take me-- Gosh, it probably took me two hours at the end of every day to just, like, you know, get to most of the, the stuff that just kind of piles up. I mean, PMs know this. Like, PMs just, like, you just aggregate to-dos all day, every day. Um, some are really important, some are just, like, things you wanna do to be a good teammate. And y- you know, it's like, how do you fit those things in? And in the past, you would just kinda, you'd just kinda muscle through them. And so the scribe helps me muscle through those way faster. I would say my end-of-day recap work is now probably fifteen minutes instead of two hours. So it is a big, like, quality of life improvement for me, um-

    23. AGAakash Gupta55:12

        Mm-hmm

    24. WFWade Foster55:12

        ... a-at the end of the day.

    25. AGAakash Gupta55:13

        I was wondering how you managed to keep up with my emails about a podcast as a CEO. There you guys go. [laughs]

    26. WFWade Foster55:19

        There you go. You know, here's a fun one. So, you know, you probably run a, you know, weekly meeting as a PM. Uh, and, you know, how do you set the agenda? What's the important things to talk about? Well, um, I have a human in the loop myself helping with the agenda, but by and large, I'm using AI to help me generate all the agenda items now. Uh, I do this for our exec meeting, I do this for our board meetings. Um, but basically, it again, it loops over all my Granola meetings from the week. It loo-loops over Slack, it loops over email, it loops over all my AI sessions, so like my chat sessions that I have with, uh, uh, any of my AI tools. And it says, "Here are the most important things that are still outstanding that you need to talk about and raise." And so I still audit and sort of approve or disprove these things, but I find that this makes sure our exec agenda is way more relevant, uh, than, uh, it is in, in the past. And also, uh, it generally has, um, better judgment on what are the topics we should be talking about. I think one of the toughest things when you're, you know, in charge of coming up a weekly agenda is people sort of bring their pet items. But are the pet items actually the most important things? Maybe, maybe not. But if you have it looping over, you know, all the metrics from the last week, the AI is gonna say, "You know what? Your conversion rate for this was really crap last week. You need to talk about this. Don't let people get away with not raising this thing." And so the most important topics tend to be, um, better if you have one of these agents running over all your stuff every week is y- and pointed at the right data sources. Uh, and you give it some ability to sort of, uh, call out, like, these topics need to be addressed. Um, so those are some of the, like, more fun, uh, you know, items in my robot staff. Um,

12. 57:06 – 1:01:56

    Why Wade vibe coded a CEO CRM

    1. WFWade Foster57:06

       maybe the next one that's worth talking about is this prospector one. But with that, uh, maybe let's go show off the CEO CRM. Um, because the CEO CRM is one of my, uh, more fun little projects. So everyone says, "Hey, you know, don't..." There's that debate online around, like, should you vibe code your CRM or not? And, and I am very firmly in the camp of don't vibe code your CRM. Uh, but yet, here I am. [laughs] I, I have vibe coded a CRM. Um-

    2. AGAakash Gupta57:32

       Oh, man.

    3. WFWade Foster57:33

       Uh, now look, this is super basic, right? This is not anywhere close to what you get from, like, HubSpot or Salesforce or any of that stuff out of the box. What this really is, is an agent that handles a very set of specific workflows that I personally care about. Now, you're looking at a demo version of it, but this is what my real sort of CEO CRM looks like. Here's the deal. I don't actually look at this all that often because I actually started by building it as a CRM to look at, but mostly now it runs as agent. And I'm only showing the UI because it's hard to demo agents without showing you something. So what this is, is it kinda, you know, it has access to like here's all the enterprise accounts we have, here's how much ARR is going on in them. You know, it kinda flags what needs attention for me based on a whole bunch of different signals. Like, you know, is there a renewal coming up? Is there, like, usage droppage happening in the account? Like, what's, what's going on in these things? Of course, I can poke into, you know, the account and start to take a look at certain stuff where it'll show me, like, here are the apps that they're using. You know, here's a little bit about the account. Here's the people on it, et cetera. But what is really all this context is leading up to is I really just wanna be talking to these customers more. And so who should I be talking to, and why should I be talking to, to them? And so what this agent really does for me now is every Saturday night it runs, and then when I wake up in the morning, I've got ten to twenty emails drafted in my inbox for enterprise customers that I want to stay in touch with. And it tells me, "Here's why I think you should talk to this person this week. You know, it's got a renewal coming up. Usage has gone down, or usage has gone up in a lot of ways. And here's what I think you should go talk to them about." So it suggests an email. Now, you're seeing it in the CRM, but what this actually does for me is it's literally a draft in my email inbox. And so all I have to do is just, like, take a look and say, like, "Yep, that's someone I wanna go talk to," and just fire off all these emails. And if I make some quick edits, sometimes I will, but by and large, I'm just using this to do what would otherwise be, like, a pretty cumbersome workflow, uh, for me every week. And, you know, it helps me keep up with our most important customers, uh, and build, like, a personal relationship with them. Uh, which in the past would have been really tough for me to have, to have done because I just... You know, you have a CSM team, and the CSM team does all that other stuff. But does-- You know, our CSMs are great, but what people really love hearing from is they love hearing from the CEO. And so now I can, you know, build a much stronger relationship with some of those most important customers. Um, and so these are the types of things that are-

    4. AGAakash Gupta1:00:02

       And it's in your voice, which is really cool. Like, I think that's-

    5. WFWade Foster1:00:05

       Yeah

    6. AGAakash Gupta1:00:06

       ... given our conversation about slop earlier, it's all lowercase. [laughs] It's written how you would write it. I think that's a key component that people probably need to iterate on their agent setup if they're gonna wanna have drafts created, make sure that it's writing to the right level.

    7. WFWade Foster1:00:21

       I'll tell you what, funny enough That was the-- That has been the hardest part of this thing. Like building the CRM, getting all the agentic logic, all that stuff is s- is so easy compared to just trying to like bend these agents to, to write like a human. Uh, they just are not very good at that. [chuckles] And so, uh, even still, i-it's doing okay here. I-- There's still things I think it could do better. [chuckles] But it is, it is really tough. And I do actually have-- I don't have it in my demo, but I do have like an agent, uh, that is running analytics on this stuff too, uh, that's sort of helping me say like, "Oh, you know, this type of writing or these types of subject lines tend to be working better than, than these." Like maybe, maybe do more of that, uh, versus the other. So, uh, you know, it just gets a lot easier to do these types of things that I think... You know, we all-- This is the stuff that I think we all want to be doing. It's like, man, I really want to be spending more time with my customers. I really want to be, you know, trying to figure out how to write better emails. I really want to be doing this stuff. But, you know, if you're in a product job, you know there's a million things that you want to be doing, but you just can't do them well enough as one person. And so this is where I get so excited about what these AI and A-agents can do for you, is you can sort of have a standard in your head of like, well, this is what great looks like. How do I use these tools to help me be great even when I'm just a human? Like I can't-- Like I just simply can't be that great all the time. So that's where I get really excited about a lot of this stuff.

    8. AGAakash Gupta1:01:54

       Amazing.

13. 1:01:56 – 1:03:45

    Why transformative is an n of one

    1. AGAakash Gupta1:01:56

       That covers it for our show and tell segment. You guys got to see, and you personally only rated yourself as adaptive, right?

    2. WFWade Foster1:02:04

       Yeah. I, I mean, honestly, I think like I'm adaptive in a lot of places. I'm, you know, uh, it-- I, I feel like I'm just like a super generalist with a lot of these things. And I have folks on the team who are way better at many of these things. And, you know, when I'm pushing into transformative, honestly, I'm just stealing from them. I'm just saying like, "What are you doing? How are you figuring this thing out?" And I'm just taking the tactics and just applying them to my own workflows and my own, you know, uh, things that I'm doing. But, you know, the stuff that we're doing as a company and as a team, um, I-- there's people who are far smarter and figured out far more, uh, than me on not just how to like use it themselves, but to build it, build systems out that work for like all of our customers and all of our employee base. Uh, so yeah, I, I feel like I'm, you know, uh, you know, capable or adaptive at times. Uh, and, you know, the places I'm transformative is like not that many. [chuckles]

    3. AGAakash Gupta1:02:59

       So interesting. I think like one thing I'm taking away is like the curve I had in mind, like, oh, maybe twenty, thirty percent of people can land in transformative. It's not like that. Like that, you should have a very high bar for that final rating.

    4. WFWade Foster1:03:12

       Yeah. I, I think there's not that many people who are truly transformative in the world at this stuff. Like it literally is-- Like to me, transformative is like you are literally an N of one. You're the first of its kind doing this new thing, uh, and you're figuring it out. Um, and so I-- that bar is just exceptionally high, uh, in my opinion.

    5. AGAakash Gupta1:03:30

       So if I'm a product leader, should I only be handing out on a PM team of thirty to forty like maybe one transformative rating a half?

    6. WFWade Foster1:03:36

       Maybe, yeah. Uh, you know, it, it's, it's, it's a low, it's a low percentage probably.

    7. AGAakash Gupta1:03:43

       Okay. So that covers AI fluency.

14. 1:03:45 – 1:12:55

    Zapier since 2021, headless SaaS and new competitors

    1. AGAakash Gupta1:03:45

       Hopefully you all got a really good deep dive into that. We have the CEO and co-founder, so we get to ask him the tough questions, and the tough question on everybody's mind. Airtable, like you guys, huge valuation twenty twenty-one. Although I think in twenty twenty-one, the five billion dollar mark that came for you guys was actually through like some sort of secondary share sale to Sequoia or something. But it was a five billion dollar mark that got labeled onto Zapier. People are looking at Airtable now, it's like o- it's less than ten percent of that amount. For you at Zapier, you've been around since twenty twelve. You had this amazing high in twenty twenty-one. Where does Zapier's business sit now? Are you at ten percent of your value? Have you grown since twenty twenty-one? Talk to us about the numbers and what you can share.

    2. WFWade Foster1:04:33

       Yeah. I mean, we've grown since twenty twenty-one. Uh, yeah, we don't-- Uh, one, one thing that's unique about Zapier is because we don't-- we haven't really raised primary capital since twenty twelve, like the, the valuation thing doesn't matter as much to us. Like valuations matter really only at one moment in time, and it's when there's a transaction that happens. And our goal has always been to just build incredible automation products for our customers, and we kinda let the rest of that stuff take care of itself. And so for the last, you know, couple years, our driving force is like, "Hey, how do we wield these incredible AI tools to make it a lot easier for folks to build and run automations, uh, in this new way?" And so that's where we sort of put the lion's share of our focus.

    3. AGAakash Gupta1:05:17

       So if you look at the no-code space in general, people are calling it like the no-code apocalypse, and I considered you guys the leaders of that space. So help me reconcile. You guys are growing, but there was this no-code apocalypse. Did you adapt in this particular way that product people can learn, or is that apocalypse overblown?

    4. WFWade Foster1:05:37

       Well, I think one of the things we've come to believe is that the new no-code is code. You know, one of the demos I was showing, the daily brief, that's code. Like that's not no-code. Like that's code under the s- the hood that's running that workflow. Uh, and so I think a lot of what the, you know, these no-code products have to do is sort of re, uh, think sort of like the, the underlying architecture of how these tools work. And so, you know, in a lot of these places, we're trying to expose our capabilities, you know, our trigger infrastructure, our action infrastructure, our runtime environments, our governance layer to coding agents and allowing them to go be the thing that goes and builds on behalf of our customers. Because, you know, there's so many people who are non-engineers who are using these tools to write code even though they're never looking at them. Like, I actually don't know what the code underneath my, uh, daily brief is actually doing. Like I, I poked it open and showed you just to show you, but I, I've never actually looked at it. Uh, and I don't really care 'cause the daily brief works for me. Uh, and so I think that's the key thing that a lot of these, um- You know, kind of like the SaaS incumbents have to sort of figure out is like, hey, how do you expose these capabilities to these tools so you can generate value on top of them? You know, Benioff is talking about this with Salesforce. Salesforce is headless now. Like, that's the value of Salesforce. It's not, you know, the UI that you log into and all that other stuff. It's the APIs and the MCP servers and all that stuff under the hood that exposes those capabilities to a coding agent.

    5. AGAakash Gupta1:07:05

       Yeah, I think it was a year and a half ago, we had Bryan on, your CTO and co-founder, talking about the Zapier MCP. Just talk to us a little bit about that. Should all SaaS be going headless? Should every SaaS be creating an MCP, and how did that contribute to the growth of your business?

    6. WFWade Foster1:07:20

       Well, I, I think so. You know, I think, uh, one of the things that we've long stood for is that no one really wants to show up to work and log into your SaaS product and, like, sit there and, like, do data entry to that tool. You know, all the SaaS that we've had over the last decade, it was still a human doing work, and it's like I really want software that actually does the work for me. And so, you know, Zapier, that's always what we've been. We've had this, like, workflow automation tool that does work for you. Um, but the one place where a human had to do work to use Zapier was building out this automation. You had to sit down, and you'd have to, like, log in, and you had to click through a bunch of things. Heck, you'd have to think about, "What do I want to automate?" Thinking about what to automate is actually harder in some places than building it, and building was hard enough. And the magic now is if you can expose all the context and the intelligence and the tools for building, you know, whether you're a tool like Zapier or you're a CRM like Salesforce or, you know, insert these other tools, the user of your software now is the agent. The agent is one that comes in and does all that work, and so that frees up the human for the things that are distinctly human, the judgment parts of the job, the, like, thinking through, like, "Well, is this actually correct or not?" Um, you know, those are the places where I think the human now gets, like, elevated in, in its work. And if you're thinking of your software as still, "Oh, I have a human user," like, "The human is gonna use my software to do this, that, and the other," I think that's a little backwards, at least for B2B. I think in B2C it's a little different. Like, consumers behave a little differently, uh, in, you know, the way they wanna use software and the way they do it. But at, at work, it's like I, "I wanna delegate this stuff to somebody else to go use it for me." Uh, and increasingly, that's a coding agent. So if your software isn't headless or cannot be run headless, I think you're gonna find yourself, you know, sort of swimming against a, a cur- um, you know, the, the current a little bit.

    7. AGAakash Gupta1:09:13

       Hmm. So this is making me think my PRD might not have been aligned with your strategy-

    8. WFWade Foster1:09:19

       [laughs]

    9. AGAakash Gupta1:09:20

       ... because it was focused on a human user, not an agent user. Very interesting. I'm gonna have to think about that a little bit more. I wanna talk about kind of this new breed of competitors. So we had the Lindy CEO on. He talked about how CoWork actually did have a pretty big negative impact on their business, and they had to reinvent themself. We also, um, I'm recording with Jan, the CEO of N8N as well. They've had a pretty amazing trajectory, seven million to 40 million ARR, 40 million to 100 million ARR, just raised at a pretty big valuation. When you think about these new competitors, how have you thought about counter-positioning against the Lindys, the CoWorks, the N8Ns, and how do you create that unique space for Zapier, which has been around for so long?

    10. WFWade Foster1:10:08

        Yeah. Well, I think what is new for us is that, you know, to your point, we've been doing this for 15 years, and for most of those 15 years, um, the space was not very crowded. There wasn't a lot of many, a lot of automation players. Now, on one hand, that's nice. Like, you know, hey, we're sort of the only game in town. It landed a... It allowed us to build this incredible integration library that still nobody has matched. You know, we have alm- over 9,000 different tools that we hook into. Uh, you know, folks kept saying, "Oh, it's easier and easier to write an integration code," and yet no one has, has matched what we've done here. Uh, and so that's the nice part. The flip side, though, is that now, um, there's sort of like a, a, a good n- good news, bad news story to this. The good news is the demand for automation, sky high. Like, it's never been higher. So the markets are so, so, so big these days compared to, you know, maybe our first decade of existence. Now, with, with big markets also comes new approaches, new ways of doing this stuff, and so there's a lot more competitors. And so I think where this, you know, really forces you to put your product hat on is you now have to make strategic choices. You have to say, "What are we gonna really focus on, and what are we gonna be good at and really make, um, you know, these smart choices for?" I mean, heck, like, let's use OpenAI and Anthropic as, like, a great example, where, you know, I think OpenAI, like, kinda was the early dogs in, in the race, uh, and they were chasing all sorts of different things. Anthropic says, "You know what? We're gonna focus on code specifically. We're gonna be great at code." And you look at what that did for them. Like, that allowed them to sort of stand out, and now it's forced OpenAI to be smarter about their strategy. And so you're seeing them get a lot more crisp about who are we for and where do we wanna win, et cetera. And so I think that's, you know, when you have these markets that are so big and you're gonna have many players that are gonna be successful, you have to figure out, like, okay, what is our unique value prop, and for what set of customers can we go build around? And I think that's what, you know, ourselves, Lindy, N8N, any of us, like, have to go answer those questions. And I think for Zapier, increasingly, the answer is, you know, we're gonna help you run these automations. We're gonna help you run them deterministically so you're not burning tokens. You don't have to keep your laptop open. Um, and, but you still can have a power of an agent that's building them and helping you manage them. So the setup is really easy, and when they break and when they fail in unpredictable ways, the agent can help you recover from that stuff. And Zapier's gonna be really, really good at that. Uh, and that's where we've been growing is, is, like, helping folks with those types of capabilities.

    11. AGAakash Gupta1:12:42

        We could talk for another hour and a half, but I need to let you get onto the day job of managing Zapier to growth and success. Wade, thank you so much for being on and teaching us about AI fluency today.

    12. WFWade Foster1:12:54

        Thanks for

15. 1:12:55 – 1:14:00

    Outro

    1. WFWade Foster1:12:55

       having me.

    2. AGAakash Gupta1:12:55

       All right, everyone. If you want more episodes like this with killer CEOs, comment below, and we'll see you in the next episode. I hope you learned as much from today's episode as I did. If you can do one thing that's totally free that would help the show, it would be to check that you're following on Apple and Spotify podcasts. Check that you've left ratings and reviews on those platforms. Check that you're subscribed on YouTube. Leave a like and a comment on this video, and then share it with your friends. We're trying to make better and better podcasts. After two years, we think we've gotten something pretty good going. So let us know what we can do to make it even better, who else we should interview, and we will put on the best shows we possibly can. Finally, don't forget my offer for the bundle. You get an entire year of my paid newsletter, plus my favorite AI tools, Bolt.new, Airtable, Speechify, Descript, Magic Patterns, Linear, Dovetail, Arize, and Mobbin'. That's $27,000 worth of value for just $150. So check that out at bundle.aakashg.com if it interests you, and I can't wait to share our next episode soon.

Episode duration: 1:14:10