Build Your Next Business With This Viral AI Tool

Oh, my gosh. I mean, every single one of these flows is a business. Pay me $300 a month. I'll send you an email every Friday with your top three competitors, fully automated. And as far as your customers know, you're spending four hours a week doing this for them.

We actually hired one of our experts because he was just so good. I was like, what if you could do this for our largest enterprise accounts? All he had to do was like, learn this drag and drop tool and now he has a new career. You can build software that is immensely valuable without needing to be an engineer. Almost everything that people really build on Gumloop and find valuable they could have never done on Zapier. Use AI and be more efficient. If you're not using AI, you're going to fall.

All right. You're going to love today's episode. You may have heard of this company out of Silicon Valley called Gumloop. They are a Y Combinator backed company blowing up like crazy. If you've heard of Zapier, I talk about Zapier a lot. It's an automation platform that's easy for anyone to use. These guys are the Zapier for this new AI age. It's like Zapier, but very easy to use. I had the co founder on to talk about how people are using Gumloop in interesting ways. How people are making money with Gumloop agencies that can be built on top of Gumloop. How to become a Gumloop expert. So you could charge money to implement Gumloop. And I just want you to know up front, this is not a sponsored video or podcast. I was paid $0 to do this. But the way I look at it is what if we could have talked to the Zapier founder in year two or year one and you could have got ahead of that curve and started an agency on top of Zapier. That would have been amazing, right? Well, I look at Gumloop as the next Zapier and so anyone listening this will have a leg up to anyone else in the future that wants to build an agency on top of Gumloop. But if you do want to support this podcast, you can use my affiliate link. You'll get a discount. I'll get a little kickback. It's linked in the show notes. You're going to love it. Enjoy. How would you explain Gumloop in one sentence to someone that has no idea what it is?

We're an automation platform where you. You drag and drop build really powerful AI workflows. Without needing to be an engineer, you can just play around with these Lego blocks and deploy super useful tools for your team.

Okay, here's an analogy I would use. Tell me if this is accurate or not, but like, Instagram was like Facebook, except pictures only and mobile first, right? And this kind of reminds me of Zapier, except AI first, like AI front and foremost, whereas Zapier is like, you can use AI, you can integrate OpenAI's API, but it's not like AI first, it's automation first. Is that pretty accurate?

I think that's accurate. In the early days, people would describe us as an AI first, Zapier on steroids. So it's. The AI part is a big component of Gumloop, but also just the complexity of the sorts of things you could build are very different. So what I've noticed is most of the things or almost everything that people really build on Gumloop and find valuable, they could have never done on Zapier. It's kind of like expanding what is possible instead of replacing them. If someone just wants to connect two APIs and get a notification or something, I would say totally use Zapier. That's. That's their bread and butterfly. Much simpler, probably cheaper for the task. But for anything else more complex, use Gumloop for sure.

What's a good example of like, a common flow that is just not possible on Zapier?

I can give some examples of the ones we use internally. So, like, every time someone signs up for our product, we do a ton of, like, AI web research to figure out everything we can about them. Like every signal that would be valuable in terms of scoring that lead, we run it through a bunch of AI categorization steps that apply, like, our reasoning to what is this account? A key account that we should be emailing. It drafts a personalized email and it puts it in my email inbox and I'm able to send those out at the end of the day. But there's a lot of nuance. Like four different models being used, tons of different endpoints being pulled from to enrich data, to scrape the web, to look at their website. That's one workflow that I use every single day or like hundreds of times a day. Every time someone talks to our customer support chatbot called Gummy, they normally are curious about something or they can't figure something out. It would be super useful if I could go and read every chat, but I don't have the hours in the day to do that. We're doing like 60,000 messages a week on our chatbot. So I have a Gumloop workflow that runs at 5pm every day. It reads every single thread. So every conversation with every customer tells me what they were confused about. And then with all of those summaries, it makes one large report that tells me like the top five things with the substantiated evidence. Like this email was having a ton of trouble with this sorted from most to least important. So we kind of have this like product manager report that is totally autonomously done without needing an engineer or to waste any hours doing that.

You're like passively collecting feedback on your product with an agent, basically that you built.

Exactly. And it's, it's using our own product to help us figure out how to improve our own product. It's a nice little tight loop of feedback.

You're eating your own dog food.

Yeah, we eat a lot of it.

I feel like people throw around the word agent a lot. Is this is. Would you call Gumloop a proper agent builder or is it agent like.

So we make AI powered workflows at the moment. I think the term agent was super is a big buzz term. Two years ago when the first agent frameworks came out, those are definitely much more autonomous and inherently unreliable and more expensive. In the previous state of how agents existed, you kind of had to cross your fingers and hope that the agent would do something useful because it just had so much autonomy and there was so much AI being used at every step. I think we're getting to a point now where agents are becoming useful, but we've taken the approach of instead of promising people the world and then underwhelming them and losing their trust, which I think is what a lot of these open source agent frameworks did. Like everyone tried it and is kind of scorned because they spent six hours getting nothing except for making a really big OpenAI bill. We promised very little in the early days. We're like, you can do this step and then you can do another step after it. And it's very rigid and defined and we're kind of continuously adding these agentic features. Like if you wanted to split a path of your workflow and have an AI step, decide what path to pursue, that is somewhat agentic, but it's pretty constrained and rigid. I think one thing that direction we will be heading in is if you want to make agents useful, they need to have useful tools which are essentially just workflows in their little toolbox. So there's a layer on top of what we're building that can be more agentic. But fundamentally we are making AI powered workflows, which I think is the shortest path to just extreme, extremely obvious business value.

Yeah. So if you come at customers and say we're basically an AI first AI enabled zapier and then they sign up, they log in, they start playing around and they learn on their own. Oh my gosh. Like this has a lot of agentic features. I could make an agent with this. Like they're, they're super users and they're super evangelists of the product. Whereas if you come at them promising agentic features, maybe they're disappointed and it's a net loss in the end.

Yeah. I think people who, who are get super excited by agents specifically often think like it'll abstract away all of the hard work of solving or like automating a problem, like it'll just figure things out. But I think the nuance of really automating something well is kind of like encoding what you understand to be like true, whatever. You deeply understand some workflow that takes a bit of like you're kind of building this workflow with all of your expertise in mind and encoding that into the workflow. If you just ask an agent to go write a sales email, it's going to write some slop, you know, and then technically it did the work for you, but it's not that valuable. So our AI workflows are kind of like assisting the human, making someone 10 times more productive, but not just like hand waving away all of the complexity of how you do work.

I feel like a lot of the problems that we're having with AI today is that everyone knows that AGI is not here yet, but they treat it as if it is. Right. And I think you need to treat AI like an employee, like you onboard a new employee and you're not going to tell them on day one, write this new sales email for me when they have no idea like what your branding is like, how you like to speak to the customer, how many automated follow ups you want, if any. Like you're just setting that employee up for failure and you're setting the AI up for failure unless you, you bring it something. Right? Like this is what I'm doing on a daily basis. It takes me about 30 minutes a day. I've done it a thousand times. I'm sick of doing it. I know exactly how it's done inside and out. Do it for me. You show it exactly what to do. You're, you know where it's going to break because it breaks for you sometimes. Would you agree that that's where people have the most success, when they kind of. They bring.

Totally. Yeah. Okay. We like to say that if you can define something as a list of steps, it's kind of ripe for automation. If you have a workflow that you can't actually break down into a list of steps, or it gets into a bunch of conditionals, like, oh, if it's not here, go check there, give them a phone call. If, like, there's a bunch of random edge cases, then it's not really great to automate. But normally a workflow that you understand so deeply that you can write it in, like a point form list, give it to an intern, and have them perform it accurately, that is exactly the sort of thing you should be automating. And the context you're talking about is, like, kind of the biggest pitfall with people who approach agents or automation. They say, like, write me a sales email with no context. And if you would have given that to your new hire who started today with no information about the company, they would write an equally bad email. You know, there's.

Yeah.

Unless they were agentic and went and found the information in your. In your Google Docs and then figured out the branding from your website, that's definitely, like, the direction AI will end up in this sort of, like, totally agentic software. But I think the path there is workflows and tooling around how AI does work.

Yeah. Okay, now I want to know, like, the 8020 of how people are using Gumloop. Like, that's one of my favorite things to do on this podcast is to talk to the people behind the scenes and say, how are people making money with this? Like, what's the one customer that comes to mind that's really using your tool in an interesting way that could. Other people could benefit from? Right. It would benefit you because you'd get more customers, and it would benefit them because they can make money or they could save money with it. So what's the 80 20? Like, what are most people using it for? And then what are those really interesting edge cases? That's a loaded question, but I'm with you. Just take one at a time.

Yeah, so people ask us this all the time, and it's. I don't have a great answer for what the most common use case is, because I think Gumloop is more comparable to Python, for example, than it is to a normal vertical SaaS that has like, five features or something. So, I mean, when you ask yourself, like, what are people doing with Python? They're building like crazy things and each one nicher than the next. There's definitely like local maxima that we see. So there's tons of like web scraping, outbound sales automation, CRM related enrichments. Document processing is a huge one, like general admin tasks like preparation, data labeling and categorization, lead scoring. There's kind of like patterns we see. Content generation is another really big one. But when we like, our most successful customers are doing everything. So like Instacart has a thousand seats on Gumloop out of the 3,000 employees. And it's almost evenly spread across 10 departments. So there's not one killer use case. It's like 150 really solid automations and they're all kind of empowered to automate work. Almost none of them, or I think like 18% of them are engineers. When we did the breakdown, we did the breakdown with a Gumloop workflow. Actually we loaded the entire user list into a research workflow that found their role and then categorized them. Yeah, that's our favorite type of customer because, like big scale, high volume, you can automate so many things I've never even heard of. And that's like really the power of this platform.

18% of their employees are engineers. And 33% of their employees have are active gumloop users.

18% of the active Gumloop users are engineers.

When we did that pie chart, that's even more impressive.

Yeah, I think engineers appreciate just how much easier we make auth and security. Like, you don't need to spin up a little side project and then deal with compliance and like oauth apps and all of that stuff. Gumlab makes it super, super easy. And engineers pick it up like so easily. It's like the fundamentals are the same for loops and thinking in systems, passing inputs to outputs.

Let's talk about like a local business owner. Let's say I own a plumbing business in the middle of the country. I've got several crews, $10 million in revenue. What's a normal use case for this?

It really depends what they're struggling with. So sometimes people are getting tons of orders via PDF emailed to them and they have someone sitting in an office, like extracting the order number, the amount and the address and putting that into a Google sheet. That is a Gumlab workflow that could be set up in like 30 seconds. It's super easy. They might have a list of leads that they're buying from some sourcing company. Like people they should be reaching out to, but they don't. They know in their head what a good lead looks like. It's like they have these five signals or sometimes they have this, which means they're really valuable or you shouldn't reach out to them. If they have that, they do a bunch of enrichment on the platform with our AI scraping AI web research nodes and then they have a categorization step and then they press run. Their whole leads list gets processed and categorized and then sorted by the most valuable. They save all of that time. And then if they want to go above and beyond and like generate the outbound or the messaging or like the call, the phone call transcript. So sometimes people will make like a research report for each qualified lead and then have that dumped out as a Google Doc. So when they're actually making the call, they have all this ammunition for like kind of like a research report on who they're about to speak to. You can really go down the rabbit hole. Like the, the more niche the better. To be honest. Gumloop is just like the infrastructure that lets you convert what you understand to be a workflow into a functional tool that's deployed.

Yeah, I'm thinking like if I'm a, if I'm a local handyman or I own a handyman business and my best customer is an investor because they're going to use me every month or a property manager, they're going to use me every day or every week or every month. And I have a, a form that they fill out on the website with just a radio button that says are you a homeowner or an investor? Right. And I just kind of know instinctively if I get an email that says investor, I want to call them more quickly. Whereas if they're a homeowner only 20 close rate, it might be a hundred dollar job. It's not really worth it. Gumloop could help. Like who I want to get a text on my phone marked as urgent when that's an investor and I just want to, you know, one click I want to call them. Whereas if it's a homeowner, put them in my CRM, put them in an automation to send them emails. Cause it's not worth my time to call. Is that kind of a decent use case?

Yeah, that's, that's a nice and simple one for sure. It'd be really easy to set up. We have a texting node. I have a bunch of text notifications that get sent to me when important things happen. Yeah, totally doable. And then you can Expand upon that. The text could include all of the background research and the, the person who submitted the form's Twitter Account and their LinkedIn and their company website. Like, you can really go deeper with it.

I think that's a big problem that people have, is they hear about these cool tools and they're like, oh, this is amazing. And then they log in and they're like, what do I do? You know, like, what? All right, what can I do? I wonder if this is an interesting framework where whatever you're doing, you know, control, find control, C, control V, whatever you're, you know, control finding, copying or pasting, there's probably an automation to be found there. Like we have a GPT wrapper in our holding company that helps skilled nursing facilities bill for more codes. And so they'll onboard a new client and then upload thousands of pages of PDFs and medical records. And for the last hundred years, what the, the, the medical billing manager does is they do control, find Alzheimer's control, find diabetes control fine. And they miss stuff. And so there's thousands of dollars a month that they could be billing for that they're not. And so we just built a wrapper that you upload all the PDFs and it tells them and it saves them thousands of dollars a month. Right. So that just kind of made me think, control, fine. Control fine. That's inefficient, that's repetitive. Right. How could we automate that?

There's definitely little signals like that throughout your workday where you, you should be thinking in terms of automation. I think that's a good one. Like the control fine. But also just whenever you're applying reasoning to like a really repetitive thing, that's really where LLMs shine. Like, even if it's a little more nuanced, like you're seeing emails coming into your inbox and you know what an email you should be forwarding to your support team looks like there's some signals, like it's, it's clearly from a customer. They seem, yeah, they seem upset. Maybe those are the only ones you, you, you forward. But you go through 800 emails a day because your inbox is flooded. That's the sort of thing that you could set up in like 5 minutes with GPT4O mini. Just doing the same reasoning, doing the same work for you. You only have to set it up one time and then you have this like totally autonomous support email bot that works for you.

Yeah. And it can analyze sentiment. Right. Like if negative, surely.

Yeah, yeah, it's really tremendous at just reasoning. So like categorizing into negative. You can even put it into buckets like, oh, this customer's complaining about this specific issue and I know who to route that to. That sort of even more nuanced reason beyond negative is something that you could set up so quickly.

You mentioned that like at five o' clock every night you push all the emails through. Are you or your customers using any email automations that they fully trust to just fully send without any human interaction? If so, what do those look like?

Yeah, I do that sometimes, but rarely. I normally like to be in the loop, so I always save emails as drafts and then I'm the one sending it off. The only ones I fully blast off are like let's say every, every week we like monitor the really high value signups on Gumloop. The customers that look like they, their companies could be so much more efficient with the tool. I'll blast out like a template and email. That's to the point. It's just my calendar basically like saying, I'll help you out, let's talk next week. That I trust. Cause there's, there's not much nuance there. But if it's a really thoughtful, like researched email with all these different hooks and personalizations, I'll review that. Sometimes like there's a customer within that list that you're personalizing for that's just so high value. You want to throw in like an extra something. Yeah, but yeah, review it just gives you more peace of mind. I think that's the. You never want to be someone smashing.