In this episode of Startup Success, Connor Heggie explains why fast-growing AI companies are still hiring sales reps, how Unify shifted to serve them, and where AI can improve prospecting even while people remain central to major B2B buying decisions.
Founders building an outbound sales team face a practical question: which parts of the job should AI handle, and where do people make the difference? Connor Heggie has confronted that question while building Unify, an AI platform for sales reps. He studied electrical engineering at Rice University, founded a computer vision company, and worked in machine learning at Helm and Scale AI before co-founding Unify in 2023. The company began by serving marketing and growth teams, then shifted its focus toward the daily work of sales reps.
Why Unify Shifted Toward Sales Reps
Unify’s first product helped marketing and growth teams respond to potential buyer signals, such as website activity or a prospect changing jobs. But Connor noticed that even fast-growing AI companies were still hiring sales development reps and building outbound teams. That suggested an opportunity to put better research and prospecting tools in the hands of the people doing that work.
Advances in AI strengthened the case for that shift. New models could handle longer, more involved tasks, making it possible to support more of a sales rep’s workflow. Unify began building a daily tool for sellers, with capabilities that had previously often depended on a marketing, growth, or revenue operations specialist.
Here is how that focus shows up for a rep. A hiring announcement or job change might prompt a closer look at a target account. Unify can help the rep research the company, suggest an outreach angle, build a prospect list, and contact people by email, phone, or LinkedIn. The rep still judges whether the signal points to a real need and uses that context in the customer conversation.
That rep-centered workflow gave Unify a clear focus for its next stage. The company had raised a Series B and grown to roughly 55 to 60 people, so the shift called for shared understanding across the team. Unify could now build around how reps research accounts, plan outreach, and talk with buyers each day. Connor’s leadership task was to bring people together around that customer and keep the new direction moving.
Treating Sales as a Search Problem
Connor’s approach to sales originally began with a different search problem: finding useful details buried in online product reviews. For a tall shopper, a review saying a shirt fits a tall spouse could reveal something the product listing never said about sleeve length. His side project used AI to turn such clues into personalized product guides. When his future co-founder described growth work at Ramp, Connor saw a similar opportunity in B2B sales. He had once thought selling was primarily about persuasion. He came to see that strong reps first need to find companies whose needs fit what their product solves.
“How do I find people and companies that have a problem that my product uniquely solves?”
— Connor Heggie
That question shaped Unify. A prospect’s needs may be apparent in a job change, a company announcement, or other information that never appears neatly in a sales database. Connor saw an opportunity to use AI across dozens of data sources to find and interpret those signals, giving reps a better starting point for outreach.
Better targeting can help a small team focus its go-to-market resources on buyers with a plausible need, then have a more useful conversation when it reaches them.
Where AI Helps and Where People Matter
Connor is skeptical that AI will replace people across B2B sales, particularly in substantial purchases where a buyer needs to defend the decision internally. For a six-figure contract, he expects the buyer to want an accountable human counterpart on the seller’s side. He sees AI as well suited to researching accounts, identifying prospects, and helping reps prepare for customer conversations.
That could improve the buyer’s experience as well as the rep’s productivity. A seller who arrives at the first conversation with a stronger understanding of the customer can spend less time gathering basic context and more time working through whether the product fits. For founders evaluating AI for sales, a useful test is whether reps reach better-fit accounts and enter customer conversations better prepared.
“Don’t sell me on replacing employees. Sell me them being so much more effective that I want to hire more of them.”
— Connor Heggie
That shift may also change what founders look for when hiring. Connor says he wants reps who are eager to talk with customers and map solutions to their problems, with AI taking on more of the prospecting work.
Keep Your Values Steady When the Strategy Changes
Unify’s shift also tested its culture. Connor says the company’s four core values have stayed the same since its founding, even as its product and target user have changed. Those values give the team a shared basis for decisions when the route forward changes.
Connor’s advice to founders is to settle on principles the team can use when decisions get difficult. Unify’s four values did not change when its product focus did. That gave employees a shared way to judge choices about customers, the product, and how they worked together, even as their day-to-day priorities changed.
He also urges founders to recognize momentum and act on it. A new direction can take effort to establish across a growing company. Once customers respond and the team starts to see progress, founders need to keep pace with that pull. Unify’s experience shows how much work sits between seeing an opportunity and organizing a company to pursue it.
Thank you to Connor for joining Startup Success and sharing what Unify has learned about building for sales reps and leading a team through change. Learn more at unifygtm.com.
Brenda Hernández Jaimes: Podcast Producer & Talent Coordinator, Ellas Media
Angela R. Chong: Audio Editor & Post-Production Producer, Amplify Podcasts
- Strong B2B sales starts with finding companies whose problems your product can solve.
- AI can help reps research prospects and prepare for more informed customer conversations.
- Watch how customers use your product and how their teams are changing. Both can signal when your target user should change.
- A product shift takes internal work, even when the opportunity seems obvious to leadership.
- Shared values can help a growing team make consistent decisions as its strategy evolves.
Intro 0:01
Welcome to Startup Success, the podcast for startup founders and investors. Here you’ll find stories of success from others in the trenches as they work to scale some of the fastest-growing startups in the world. Stories that will help you in your own journey. Startup success starts now.
Kate Adams 0:19
Welcome to Startup success. In this episode, I sit down with Connor Heggie, co-founder and CTO of Unify. We discuss the challenges of building a startup in a rapidly evolving AI market and how Unify balances technical innovation with customers’ growth and culture. We also explore the shift toward human plus AI collaboration. What AI means for the future of sales and hiring. How AI is reshaping outbound sales and the way startups build teams, and what founders need to understand when building an AI startup today. So, Connor, thanks so much for being here today.
Connor Heggie 1:00
Of course, I’m excited to chat.
Kate Adams 1:03
I am as well. I really want to get into Unify what you’re doing, but if you wouldn’t mind first, kind of like setting the stage for us with a quick overview of your background, and then we can talk about what led to the founding.
Connor Heggie 1:16
Yeah, absolutely. Okay, let me maybe give you my background in chronological order. So,
Kate Adams 1:21
Okay.
Connor Heggie 1:21
grew up in Southern California, so SoCal born and raised. Went to school at Rice in Houston, Texas. Studied electrical engineering, not computer science. Importantly. I grew up watching you know Star Wars and Iron Man, and I was like, how do I do that stuff? And somehow ended up with electrical engineering. And then I started a company right out of school doing automated sports analytics from computer vision back in like 2017, 2018. Totally a different time in AI. Back before we called it AI when we still called it machine learning.
Kate Adams 1:55
Right, wow.
Connor Heggie 1:56
Much more of a research project. Did that for about two years. We decided to shut the company down for a bunch of reasons. Looked around, wanted to work with the smartest people I could in machine learning. Joined a self-driving company called Helm. Did a bunch of sort of like computer vision work there again. Back when we used to call it machine learning and not AI. I did that for a couple years. Joined Scale AI, which is a data labeling company where I was doing a bunch of kind of like human in the loop ML. So how do we get the like one plus one equals three of the human plus AI system? Which was really really interesting and kind of informed a bunch of my you know thoughts now, of course, as we as we build Unify. But yeah, my whole background is really like kind of this ML tradition as opposed to go-to-market tech, which is what I do now.
Kate Adams 2:39
Right, very different, but great companies. Seriously. Really strong experience. I think I had someone from Helm on the show. That’s great. So what then, you know, inspired Unify? Because you’re one of the co-founders.
Connor Heggie 2:55
Yep. So I’m one of the co-founders. I’m the CTO.
Kate Adams 2:58
Yes.
Connor Heggie 2:58
So I tell this story. So maybe first, like, what is Unify? You can think about Unify a lot as like Claude Cowork or Codex, you know, one of these like agent chat sort of products. but for go-to-market teams, for outbound sellers. It’s like really focused and built for that use case to help them do specifically outbound, but really kind of their full workflow. Flashback to you know 2022 pre-ChatGPT. You know I’m still at Scale, wanting to get back to starting companies. You know I just kind of have the thing messed up in my head that I like have to be starting – I just love the you know the game of being a founder. Probably hear that a lot on this podcast. Do you know the website Wirecutter?
Kate Adams 3:38
Yes, of course. Yeah.
Connor Heggie 3:40
They do the listicles, it’s like top 10 best non-stick pans.
Kate Adams 3:44
Oh yeah, I am a sucker for all those lists. Yeah, yeah.
Connor Heggie 3:47
I am too. My family is the kind of family where they’ll buy like a you know my uncle will buy a $20 pan, but he’ll spend like 10 hours reading reviews for it to get the best you know nonstick pan. That’s what I grew up with. And anyways, I was working on this sort of side project while I was at Scale, doing kind of like AI-written listicles, kind of like you know Wirecutter article, but hyper personalized for you. So you can’t see, right? I’m six five. I’m really tall, and it’s hard to find sleeves that are long enough, right? Very classic tall person problem. I know it’s such an annoying problem to hear about, but the way that you find that isn’t by looking up like extra long sleeve shirts, right? You kind of find that information in the like reviews where somebody says, “Oh my God, I bought this shirt for my husband. He’s so tall. Shirts never fit him, but this shirt happened to fit him. And you kind of know like semantically that means oh well, like he’s tall and must have like sleeves that are long enough, and that information is locked up kind of in the reviews, right. In like the Reddit article about it, where somebody’s talking about it.
Kate Adams 4:55
You have to dig for it.
Connor Heggie 4:55
You have to dig for it, and it’s kind of like this semantic data. Nowhere does it say that the sleeves are extra long. Or maybe it does, but often not. And so I was working on this side project that was basically Wirecutter style, hyper personalized articles, but from all the reviews on the internet. So how do we aggregate up like, you know, Shopify site reviews, Amazon site reviews, Reddit, et cetera, et cetera? Totally a different time.
Kate Adams 5:16
Good idea.
Connor Heggie 5:17
Thank you. I thought so too. And it was, you know, again, totally a different time in LLMs. It was like, you know, it took like 45 minutes to generate one of these things. It cost like $60. It was, I mean, insane, right? Now that product, I’m sure, would be great. You know, somebody should go build that product. But I really like fell in love with this this sort of concept or ability to take like huge amounts of just like unstructured semantically rich data, and pull some interesting insights out of it in this way that you just you couldn’t do before because we didn’t have this like general intelligence that these LLMs even back then were showing. So I was looking around. I kind of wanted to start something you know in this space, and I got connected to my co-founder Austin, who went to school with me, but we weren’t super super close in college, so we reconnected. And he was telling me about some of the work he had done at his past company doing growth for B2B companies, right? For his you know the company he worked at, Ramp. And he was telling me sort of about how they were doing you know this like automated messaging, and I was like, oh, that’s really interesting. That’s kind of the B2B version of the thing that I’m talking about, right?
Kate Adams 6:24
Right.
Connor Heggie 6:24
Except instead of helping sellers, you’re helping buyers, you know, find the right people to reach out to. And I was like classic engineer. You know, again, you maybe hear this all the time. Classic engineer. I was like yuck sales, right? I was like, you know, in my head, I was like, used car salesmen. Like the job to be done of salespeople, I thought it was rhetoric. I thought it was, how do I convince you to buy my product?
Kate Adams 6:50
Right.
Connor Heggie 6:51
As it turns out, totally not the case at all. Right. At least in B2B. At least great salespeople.
Kate Adams 6:58
Exactly.
Connor Heggie 6:59
The problem that they really describe is a search problem. They say, “How do I find people and companies that have a problem that my product uniquely solves?
Kate Adams 7:08
Exactly.
Connor Heggie 7:08
And then it doesn’t really matter what you say to them, right? Like, you have to, of course, communicate credibly and be effective. But at the end of the day, like, the economy is kind of just everybody solving each other’s problems for money. And if you can really credibly help somebody see that you solve a problem that they have, that they feel badly enough, that your product really uniquely solves, that’s actually super mutually beneficial. When you reformulate all of go-to-market as a search problem, there’s a bunch of really interesting stuff that comes out of it. That you know, I again, as a classic engineer, was like, I understand the search problem. Let’s go build, let’s go build that. And superpower it by this, you know, new AI ability to take again huge amounts of unstructured, semantically rich data and make it available and accessible for reps. And so that’s really that’s what we’ve been building. That’s what we, you know, we started with like a bunch that was more on almost like the marketing side and sort of growthy side, you know. Earlier this year, we made this sort of shift over to focusing entirely on reps because we think that there’s this you know exciting opportunity to give them leverage and leverage from all that data. But yeah, it’s how we started the company. So we started it in 2023.
Kate Adams 8:14
Wow, I love how you walked us through that because it does go back in a strong sense to that initial problem you were trying to solve, you know that was speared on by Wirecutter, like finding that information. And the way you describe B2B sales. That’s really what it is, but you know, it’s really I like how you described it. So you mentioned you’ve kind of pivoted, or not pivoted, but you’re focusing more on the rep. Like, explain that to us because I think that happens a lot with startups, right? You start to kind of define and narrow, and it would be interesting to hear how you all got here.
Connor Heggie 8:57
Yeah, absolutely. So I would say, you know, as with all things, right, there, it was a mixture of both the feedback we were getting from the market and from customers, as well as from the things that we were seeing on the technology side and the new use cases that were possible. You know, again, our north star is to help the best products win, to help all of the best companies, you know, I feel super fortunate to work with some of the best AI-native companies like Perplexity, Decagon, Pylon, and Together AI. Just like these amazing companies that solve this, you know, real problems, and they need to again find the people and companies that have them. And what we saw for many of them was our first product was really around this marketing use case of how do we help them automatically respond to signals of this sort of buyer intent, right? So it might be web intent, people looking at my website. It might be people changing jobs. It might be you know new hires in seed. It might be like a news article that you know one of their prospect companies puts out, things like that. And then we would sort of automatically send an email out. And that was, of course, you know, very, very effective at this sort of scaled, high-leverage use case that you know you probably are more familiar than anyone around, you know marketing and growth and demand gen. That’s sort of this more systemsy problem
Kate Adams 10:15
Right.
Connor Heggie 10:16
But even these amazing AI companies that have the fastest growth rates in history, the best, most technical, you know, marketing and growth departments were still hiring reps and SDRs and BDRs to go do actual outbound, which was very counter narrative. You know, like two years ago, we were all talking about how sales is going to get automated, right? It was all these AISDR like companies.
Kate Adams 10:42
Yes.
Connor Heggie 10:43
And so we were like, okay, that doesn’t really line up. And then on you know the technology side, we saw with you know the new models that came out, like Opus 4.5, GPT 5.2, like in December of last year, there was this ability to do this really long running work that had never been possible before. And like a real ability to do knowledge work end to end, sort of fully in an automated way, meaningful chunks of tasks and and jobs. And so we sort of saw that. We saw this trend of these rep teams like really being built at these you know again amazing companies with this very high growth rate. And we saw really the writing on the wall that we believe that these humans will continue to be important, and we don’t want to be siloed off in just the marketing department, which has you know one person inside of the company that strategies change you know quite a bit. We want to be sort of like the tool that the daily use tool for all of these reps, and actually give them the superpowers that was locked up in the marketing department or the Rev Ops, you know, sort of team and department, or go to market engineering department, and give every single rep kind of their own, you know, Kate in the in their back pocket, right? Or like you know, rep, you know, rev ops person or growth marketing person in their back pocket.
Kate Adams 11:57
I really like that. Gosh, you’re really empowering them to do their job so much more effectively. It’s such a good strategy. Why do you think that is? Like we talked about this when we met, two years ago on this show, everyone was saying, “No more salespeople. It’s done. Get out.” And now the pendulum has swung, I think, I don’t know if you agree that it’s more like salespeople with the help of AI, right?
Connor Heggie 12:23
Yeah, yeah. I mean, you know, I’m curious what you think about this. I feel like there’s this real allure to the like narrative, which is headcount replacement.
Kate Adams 12:31
Yeah.
Connor Heggie 12:32
And of course, there’s going to be a bunch of startups that want to go pitch headcount replacement because the TAM of that is 300 billion dollars of sales headcount.
Kate Adams 12:40
Yeah.
Connor Heggie 12:41
And there wasn’t a lot of proof points that they could go capture that headcount budget, but there was a lot of pitching. You know, and of course VCs want to go fund that because it’s a huge TAM, et cetera, et cetera. So it made sense to go after as a market, but my sense is always that today, and I and I don’t think in the foreseeable future there’s not going to be there’s not going to be buyer agents responsible for signing six-figure contracts because I need somebody internally accountable for that decision.
Kate Adams 13:08
Right.
Connor Heggie 13:09
And then if I have to be accountable internally for that decision, I certainly want a human counterpart accountable to me as the buyer.
Kate Adams 13:16
Yeah.
Connor Heggie 13:17
Which means you kind of have to have these salespeople. I don’t know. Like, does that line up with what you’ve seen as well?
Kate Adams 13:21
Absolutely, and doesn’t even have to be that big of a spend. I think you know, obviously for very small ticket items, yes, but absolutely, yeah. I think the AI though has really changed the sale process in that, like you were saying, these reps come on, they’re much more informed, right? They really can understand the companies that they’re working with and what they’re trying to do. I do feel AI has made it much more efficient, which is what you’re doing.
Connor Heggie 13:53
Yeah, and it should be a way better buyer experience too, right? (Yes.) There’s a lot of talk of how do we make salespeople more efficient? And look, I am all in on salespeople being more efficient. Like we want them to close more deals. We want them to, you know, to be able to do more with their time. But I think a really amazing outcome of it is actually that the buyers on the flip side are getting a salesperson who’s like you said much more informed. They’re much more engaged. They understand how their solution maps to your problems way better because they can, you know, get these reasoning models that are very smart that like they will probably have to go back and forth with. And they can do much more research on you before the first call to have a more informed perspective. So in a great way, it’s kind of this actual win-win where you both better service your customers and you’re actually more efficient, you know, per sales rep. And the sales reps are way happier because you probably hear from them all the time. They want to talk. They want to talk to customers. They don’t want to do prospecting, right? Like no sales rep is like, I love prospecting.
Kate Adams 14:55
No, that that’s usually not – if they’re a good salesperson, that’s not going to be one of their core competencies. I don’t think. I mean, there’s there’s rare ones that can do both really well, but most want to just be part of the sale.
Connor Heggie 15:08
Yeah, and that’s the kind of rep that I also want to hire. I want to hire someone who wants to be on talking with customers and solution mapping and and being really consultative consultative, and you know I don’t want someone who just wants to go into a room and like prospect. Which, by the way, there’s like definitely like a ton of value in that. But I,
Kate Adams 15:26
Right.
Connor Heggie 15:26
I think that’s what agents are really good at. So let’s like free up that time to now go do, you know, real community, you know, human human to human interaction.
Kate Adams 15:33
Have you found there’s a lot of buy-in from for what you’re doing in the community?
Connor Heggie 15:40
Yeah, I think
Kate Adams 15:41
I would think so. Yeah.
Connor Heggie 15:42
Again, that like that 2024, 2025, we’re gonna replace salespeople thing. there was such a rejection because I think everybody understood. There’s all these billboards around SF you’ve probably seen that’s like, you know, replace your humans. And I just see them and I’m like, oh man, I don’t, I don’t want to replace my humans. Like I love my … I come to work every day for the team. Like that’s what motivates me. Like, don’t sell me replacing them. Like, sell me them being so much more effective that I want to hire more of them. (Right.) And that’s really what we hear from, you know again, these like amazing companies. Like, like the most AI native companies, you know, Decagon, like all they are hiring more sales reps, and that’s like absolutely what we want. That’s what we want to make happen. And sales leaders, of course, also want to hire more sales reps because they have bigger teams and there’s you know structural incentives. But I’m very excited with how well it’s been received.
Kate Adams 16:36
That’s great. I love hearing that. What have been some of like your surprises or you know challenges that you didn’t foresee?
Connor Heggie 16:46
Yeah, that’s a good question. I would say the biggest one the biggest one for me was really, you know, internally. I think we had such a strong pull from the market. Like it felt really clear, even just intellectually, you know, as we’re talking about this, it feels obvious that this is such a great product that should exist.
Kate Adams 17:07
Yes.
Connor Heggie 17:08
And so we would go talk to customers, and there would be pull for it. We would talk to you – we would talk about what the solution might look like, and it felt really clear. To be clear: very hard thing to go build well and to like really you know get all of the like small things right in addition to the big things right. But I would say like the most surprising thing and the most difficult thing was really doing the internal – it’s not quite selling, but sort of righting the ship. You know, we’re not that big of a company. We’re you know 55-60 ish people. And even then there there’s you know maybe something that I discounted, being the founder who could just say something and like re, you know, decide that we’re doing something different, is really kind of like reorienting the ship again, you know, away from just servicing the singular persona that we’ve we’ve serviced this whole time of like a marketing or a growth person to servicing IC sales reps, like day to day sales reps. And those are really different mindsets to be in. They’re different people, as you know really well. They’re different, really different people to service, and you know we had to do the thing that surprised me a lot was you know how important it was to get that right, and the kind of like, not to sound corporate change management process. I had no concept of what change management ever was, right? Like I had to figure it out and go and like build, you know, again build the momentum in this new thing to show that it’s like really working and winning, even though it felt really obvious to everyone. There’s just this natural tendency of people to keep doing what they’ve done.
Kate Adams 18:38
Right. Right. You must be building a pretty strong culture to like make shifts like that. Is that something that you are paying attention to as a leadership team?
Connor Heggie 18:50
Oh yeah. (Okay.) Yeah, I always say it’s like probably a meme internally now, but I say all the time, and I believe this to my heart that a company is really just a bunch of people who decide to show up every day and like do this really hard thing together. I feel incredibly grateful and lucky that we have again these like 50,55, people, like amazing group of people who just decide to show up every day and do this. And I think the way that we decide to show up every day and do it is the culture, and it’s just the number one thing that keeps me up at night that I care the most about. It’s what all outcomes downstream are from, and you know, there’s like a lot of a lot of folks will kind of ask, like, yeah, you like make this like sort of shift in focus and strategy, and like you have to do all this work to go move people over, you know, how can you how can you do that, or like how you know what made it really effective? And I think the thing, one of the things, of course, is that the team is just brilliant and hardworking, and we’re down to be scrappy and move over. But I think another really big piece was that the core of our culture, we have these four cultural values that have been unchanged since we started the company. That all of the downstream decisions can be made on, and those didn’t change in this, you know, change in persona and the change of product, right? Still, we want everybody to show up and give a shit every day. That’s when you know number one to get their rocks done, to be a unified team. We have this one that’s very silly: Unified team, Unified dream, like to be all in, to be together, win and lose together. And then four to do what’s best for the customers. You know. And this was what was best for the customers.
Kate Adams 20:28
Wow, I like that. You know, of all the founders I’ve had on the show over the five years, the ones that are you know later stage very successful, they all say culture is what got them through the pivots, got them through the challenging times. So, and then you said something, and I I heard this on the show a few times. You said that kind of your decision making goes around those four values. Is that something that you really take to heart when you’re making big decisions?
Connor Heggie 21:01
Absolutely, yeah. I, you know, when you’re making certainly hard decisions, but even sort of all decisions, if there isn’t some framework that everybody in the company can point to and use as their you know lens and framework, it’s going to be chaos. It’s going to be difficult for us all to work together and make progress in the right way. And also like you know these culture you know cultural values are the way that I want to show up to work every day, and that I aspire to, and I think that I do, and the way that I want everyone else to. And that you know if I don’t make decisions off of them, certainly I can’t expect everyone else to make decisions off of them. And so if I want all of them to be making decisions off of them, certainly I should be making my decisions off of them, and you know, be a good, like I don’t know, not role model, but a good sort of like model of it.
Kate Adams 21:54
Yes, yeah, model the behavior you want to see. I think that’s really important for leadership. I think it’s true, yeah, and all of that. So, where does Unify, like, where do you stand today? Like, what’s going on today with y’all?
Connor Heggie 22:09
Yeah, gosh, we have so many really, really exciting things that we’re building. So, we raised our Series B right last year. (Congrats!) Again, we historically – thank you so much. We historically had serviced this, you know, more marketing and growth persona, and now we’re all in. We want reps living out of the tool day to day, and we want to give them the tools and leverage that, again, you used to have more of a like require a systemsy kind of background, and all of that built into a full sort of sequencing sales engagement product. And so, what does that look like? Today in Unify, and more and more day by day, week by week, month by month, as we ship more, you show up every single morning into Unify, you have your list of target accounts that you have put in that you have told us are the most important accounts for you. We give you recommended angles and actions of people to reach out to. You can go and put a list together using 40 plus data vendors that we’ve aggregated. Did a bunch of work to figure out where they’re good and when to call which one, right? Which is just so annoying to have to do, but you know, a rep needs that data. Build the lists off of it, and then sequence. You know, actual do phone calls and send LinkedIn messages and send emails, of course. All out of sort of like this end to end system, and then track what’s working, what isn’t. You know, all all in a single place, in a Unifyed place.
Kate Adams 23:34
I love it. So cool. You must be so excited about this. Really, what a game changer.
Connor Heggie 23:40
It is so fun. I’ve never been more excited building product than I than I am now. And yeah, it’s it’s really cool to see you know just like great companies and great customers and see them succeed and grow themselves and use Unify.
Kate Adams 23:53
Yeah, I bet that’s got to be so fulfilling. So okay, it’s been really fun talking to you. We always wrap up the show with advice you can offer the other founders listening, especially those that you know are thinking, Gosh, Series B. You know they’re still getting through their pre-seed or their seed. Like any advice you can offer them?
Connor Heggie 24:15
Man, so much. I would say, one again, just like you got to be really principles driven. Have the values that you believe in. Follow them, right, whether it’s through a pivot or through hiring or through you know all the hard decisions that you have to make day by day. It sounds so corny and cheesy, but it is just so true because anything else will just you know eat you alive trying to second guess it and like make the decision every single time. Like make the decision once, align on it as a team, and you know follow those follow those things. So that’s certainly one. Another one is really around momentum. Companies, startups just live and die by momentum. There’s kind of this like you know old saying that that growth cures all evils or all ills in startups and. That’s just momentum, right? Like, be moving in a direction, and when you start to feel, you know, you’re like pushing the ball up the hill, the rock up the hill, pushing the rock up the hill, and like as you like got to build that momentum, and then as soon as you feel it start to sort of like pull off your hands when it’s rolling in front of you, you have to sprint after that thing and keep up with it and keep pushing. And that’s the way that you kind of get the compounding advantages over time. And then the last sort of piece of advice I would probably give is really around the people, right. Just like at the end of the day, a company is a bunch of people who decide to show up every day and do the thing that you decide to show up every day and do. And you know, there’s a lot of downstream sort of implications to that thought, but I try to keep that really in mind. It’s what gets me out of bed every morning, right. The people is always what you know motivates me most, so…
Kate Adams 25:48
That’s great. That’s awesome to hear. Where can listeners go to find out more information about Unify?
Connor Heggie 25:55
Yeah, absolutely. So you can follow us on LinkedIn and Twitter. Just look up Unify GTM. You can find us everywhere. We have a PLG motion now, so you can self-serve sign up, which is awesome, and try it for free at just unifygtm.com. Highly recommend that folks try out the product and test it out. And pull a list of people that you think might be interesting and send them an email. And I suspect once you once you get through that flow once it’s hard to go back to doing it, you know out of LinkedIn sales and have one by one.
Kate Adams 26:23
That’s awesome! Thank you so much for being here today, Connor. It was really great to speak with you. You shared a lot of helpful insight.
Connor Heggie 26:30
Of course, thank you so much. This was so fun. Thanks for having me.
Kate Adams 26:32
Good. I’m glad. Thank you.
Outro 26:36
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