The AI-EQ Connection: How Emotionally Intelligent AI is Reshaping Management

0:00Season three of the Built Right Podcast is right around the corner, but we've got one big change coming your way. The Built Right Podcast is now the Talking AI Podcast, and we've got a lot to talk about in AI. In the Talking AI Podcast, we'll be having in-depth conversations with both AI experts and early adopters of AI. That way you can understand how the technology works and how early adopters are beginning to implement and, more importantly, get value from AI. Our guests range from AI research scientists to founders of AI products to industry leaders putting AI to work in their business. While you're waiting for season three, go ahead and subscribe on your favorite podcast platform so you don't miss an episode.

0:41And make sure to leave us a comment about the AI topics that you want to hear about. So get ready to talk some AI in the new Talking AI Podcast, coming your way August 6th.

0:58Welcome to Built Right, a podcast by Hatchworks where we help you learn to build the right digital product the right way. In each episode, we'll deconstruct the layers of successful product development, break down popular trends, and offer real advice to help make sure your product is Built Right. We may not have all the answers, but we've built a lot of digital products across a lot of industries, and we've seen a thing or two. Let's get into it.

1:33Welcome, Built Right listeners. Today, we're chatting with Brennan McEachern, CEO and co-founder of HyperContext, an AI-empowered tool that helps managers run more effective one-on-ones, which leads to better performance reviews. And it's trusted by 100K managers, companies like Netflix, HubSpot, and Zendesk. Welcome to the show, Brendan. Thank you for having me. So excited to be here. Yeah. Excited to talk today. So the topic we have for our listeners is one everyone really needs to stop what they're doing and listen to. And today we're going to get into how you should be strategically thinking about embedding AI into your products in an intentional way.

2:14And with the current AI hype cycle we're in, or everybody and their mom is bolting AI onto their products. And I don't mean that in a good way necessarily. This is a conversation worth having. But Brendan, as a way to kind of set context, I love getting into our guests with what problem they saw in the market that kind of triggered them to start their company. Give some good context for the background. Awesome. Can do on the context side. I think the story of HyperContext, the story of us founding it is an organic one. Myself and my co-founder Graham had a previous company. We've been working together for a little over a decade and that previous company was successful enough or maybe we were successful enough at building and selling product that we ended up becoming managers.

3:03We had enough employees and staff around us to help us build a bigger and better business. And as we stopped building and selling, we realized that we accidentally fell into a new career of managing and that this new task of being manager operators is completely different and very hard. So we did what we knew best, which was build. We built some little side of desk tools to help us be better managers and be better bosses. And as a long story short on that business, as COVID kind of came around and wiped out industries temporarily, we were caught up in that mess and that business disappeared almost overnight.

3:44But these little side of desk projects that we had built exploded. Everyone in the world became a remote manager overnight in the middle of a crisis and felt the pain of being a manager and being a remote manager and all of the problems that come along with that. And these little tools that we put out on the internet went from a couple signups here and there to, in some cases, thousands, thousands a week. And so we made some tough choices, but otherwise we're able to pivot almost all of our energy towards what today, hyper context, which is, as you mentioned, building tools for betterment to make managers the best bosses their team has ever seen.

4:26So we start with one-on-ones, we start with internal meetings, add goals to it all the way through to now just recently launching performance reviews. And I think that sort of leads into trying to build the performance review piece the right way. Yeah, I love the, it's kind of like the Slack story, right? Where you kind of built this thing on the side in power. You're like, oh, this thing actually has legs. And I was just chatting with a friend yesterday, same kind of thing. They had like this side thing they'd built and people were asking about it. And it's like, well, maybe this is the thing.

4:57But it's kind of an interesting story when something like a pandemic just changes your whole business model, right? Yeah, I think the saying, right, of like scratch your own itch is relevant here. We definitely started it as like something to scratch your own itch. And as early as we possibly could, tried to get external people's input on it. One of the things that I think I learned in the first business is like what you want and what helps you is not always the exact same thing as what helps other people. So we tried to look for the general solutions to some of these problems instead of a specific ones that would work for me being a tech guy, a product guy, whatever.

5:39We wanted to look for something that had that broader appeal. And that's actually how we landed on one-on-ones. We initially thought, hey, there's maybe more meetings that we could tackle. And when we went out and tried to talk to people and figure out a general solution, the amount of build we would have to do is just so big. We ended up looking for like, what are some commonalities? And one-on-ones ended up being really appealing for a variety of reasons. But one of the main ones is that an engineer having a one-on-one with their manager is very similar to anyone else at any other company having a one-on-one with their manager, almost by definition, right?

6:13You're not supposed to talk about the tactical day-to-day stuff. And so you talk about more of the meta conversations, which can be similar. So that sort of led us down to some of these pathways. Quick break in the pod. If you're listening to this podcast, chances are you've been thinking about how to actually use AI inside your business. And that's exactly why we built the AI Opportunity Finder. It's a free tool that helps you uncover high-impact, tailored AI use cases based on your business, your goals, your pain points, and your industry. No fluff, no generic use cases, just real ideas that fit your business and the ranked by ROI potential.

6:50It takes about three minutes to run and it's like having your own personal AI strategist for free. If you want to try it for free, check out the link in the show notes or go to hatchworks.com backslash AI dash opportunity dash finder. Yeah, I think that's an interesting point. Like just to pause there for anybody in product, we talk about building your solution, the right, building the right solution and building it the right way, building the right solution, start with a smaller use case. That's a critical piece. Like you could have boiled the ocean and tried to figure out every meeting under the sun and all this stuff.

7:24And then your head would just explode with everything under HR. But you started with the one-on-one because it was one that universal, it needed help, right? So you identified this problem in the market. I just love that. Now it's turning into more as you've built proof behind it. Yeah, we started with just exploring, especially coming from the last business where it was a lot of change management to kind of sell the product. We wanted to avoid some of the change management. So we're like, what is already existing? And the only thing that I could kind of point to as proof was like the calendar.

7:58So like, when we're building some of these products, it was what already exists on the calendar. Let's not make people do something new. Let's look at their calendar first and see if there's anything we can do on that calendar to make it 10 times better. And so the one-on-one was there. So it was the team meeting. So it was the board meeting. So it was the QERs, all these other types of meetings. The interesting thing, there's so many things that are interesting about one-on-ones for us as a business. Almost every manager has one. So there's lots of entry points into the organization, which was a key piece of what we thought our strategy would be.

8:30Very easy to try because you can try it with one person. You don't have like a town hall is tough to try. You have to do it with your whole company. So with a one-on-one, you can pick the most open-minded person on your team, try out the product. If it works well, you get into some of the other things. It's very replicable, right? If you have something that works with one person, it should work for other people. So many other things. It can spread, right? Like you have a one-on-one with direct reports. You also have one with your boss, right? You're all the way up to the CEO and the CEO all the way down to a different department.

9:01So you can spread. It exists on the calendar. There's so many things that led us to it. And just because you have seven direct reports, seven one-on-ones, plus your boss, plus maybe a peer one-on-one, just by frequency of meeting, it's a very high frequency meeting. There's way more one-on-ones than there are team meetings at businesses. So all of these things, as we bumped into it, we said, hey, maybe there's something here. What would it look like to do a 10x better job? And honed in on that use case. What are people already using for it? What are the good, the bad? Who are some of the competitors?

9:34And for a long time, the only people building tools for this space were the big, boring HR companies, right? And like, no one wants to open up our ADP and go into like this tiny little module to fill in a text box when you can have Apple notes or something like that. So I still have nightmares from using one of those with the time entry system. I'm like, all right, what button do I click? Like, who designed this thing? But they can't get out of their own way because they've so much legacy, just what's the word, technical debt that exists there, right? And they have to cover so many things. They have to do payroll for every culture and company type and all that stuff.

10:16And you're just one tiny module on there. Yeah. But a lot of great PLG type of motions there, like you mentioned. The high frequency of using the product, building the habit. it. I think we talked about the book Hooked, which if anybody has not read that, check that out. It's great. And there it is, the yellow blur in the background. It stands out like a sore thumb, which is another great way of standing out. But I want to, let's get into now AI, right? So your company was started post-pandemic. This was pre-Gen AI, large language model craziness, even though they'd been around for a long time, the crazy hype there.

10:55And you had AI integrated into the tool. But I'd love to get into this evolution because one thing that struck me when we talked earlier, it's like somebody's going to do this, talking about competitors, embedding AI, but they're just not going to do it the right way. And we want to do it the right way. But talk about that evolution because so many folks, they just bolt on AI. It's from a marketing perspective. They just want to key into the hype. But it's such a bad way to do it from a strategic standpoint. Yeah, it's funny. The place where we have AI the least right now is actually on the marketing side.

11:28It's something that we're trying to fix. It's definitely pretty heavy on the product. No, you're exactly right. We wanted to build the best, for lack of a better term, we wanted to build the world's best one-on-one tool for managers. And that mission will never truly be accomplished because the market moves so quickly and we always have to serve the managers in that use case. But like largely quote unquote mission accomplished, we have the best hyper-connected workspace for one-on-ones for managers, whether it's just one-on-ones or you want to bring that team in once we have it for team meetings.

12:08We added goals to it. So if you're working on professional development goals, you're working on team goals or OKRs. We have the largest library of goal and OKR examples on the internet built into the product. Like largely anything a manager, a team lead would need out of a platform for leading their team built it out of the box. PLG, go try it for free. And I mentioned some of the benefits of one-on-ones and some of these team meetings and that we get this organizational spread. Well, that started to happen, right? We would start to spread across these organizations through calendar invites. As people discovered our tool and shared our tool, COVID taught us nothing else.

12:49It's that you look for the super spreaders, right? Like we were looking for the people who would spread our tool internally and they did. And then because we say the word manager so often, because we say the word one-on-one so often, when it came time for the organization to look at this tool and say, well, what does this tool use for? This is often used for one-on-ones and for gold. Managers love it. It fell on the desk of HR. And HR looked at it and said, this is great. This actually might be a sign that our organization is maturing. Maybe we need some more of these HR, big HR tools, right? Maybe we need a platform for performance management, which it can do all of these goals and can do all these one-on-ones, but can also do surveys and can also do performance reviews and can also do all these other things.

13:38and the managers were like, no, no, no, don't get in our way. Don't ruin our thing. And often they would use us almost as an excuse to buy their tool, to buy the big, boring HR tool, consolidate the money that the company is spending on us and double it, triple it and spend it on something else. And the managers would revolt and stuff like that. We would try to fight back as best we could. But ultimately, when we started talking to the folks in HR, they were like, well, I need performance reviews or something like that. So we didn't want to build it, but we started looking at building it and taking that fight on.

14:14What would it look like if we did round out our platform to incorporate some of the more traditional aspects of performance management? I hate that word, by the way, performance management. That's like a micromanage-y word. I think that performance enablement, I think that the goal of HR getting involved in performance management is to help people be performed. They're not really there to micromanage performance. They're not getting fired if like marketing misses their KPIs or sales misses their KPIs. So like, why are they in charge of performance management? It doesn't even make sense. But enabling performance at the company, that makes sense for HR to kind of centralize, right?

14:55So we looked at what were the other people doing? Maybe there's integration plays that we can do, etc. And one of the first things that popped into our mind was just the quote that HR kept bringing to us, which is, well, if people are doing their one-on-ones properly, if they're doing their one-on-ones right, then come performance review season, there should be no surprises. No employee should be surprised. I've been through that experience. It's like, I have great intentions come January. I'm going to document everything that happens. I'm going to have this great thing at the end of the year.

15:29And I'm okay at it sometimes, but I'm not great at it. Right. And that's like a huge piece of what our core product tries to solve. Can we build in some of these workflows where you can follow through on those great intentions? I think most managers with those great intentions try to implement them with like a Moleskine notebook. right? They get like a new Moleskine notebook and they're like, this year it's going to be better. And that Moleskine notebook has like four pages and then it's tossed to the side. And HR says, well, we're going to make it better by giving you like a Commodore 64. And you're like, I'm not going to use a Commodore 64 for my like notes.

16:05That's insane. I've got modern tech over here. So we wanted to build what would the Apple version of this look like? And you're exactly right. If we did the daily habits, right, things would be much better. We've spent so much time on the daily habits that we legitimately help managers to the point where they spread the word internally. When we went to HR, it was like, well, if they're doing everything right, then there should be no surprises in performance reviews. Can we actually make it so that it's not just that there's no surprises, that it's effortless? What would that look like? And we started exploring around with AI, just making like proof of concept demos of, can we take the notes from your one-on-ones?

16:45Can we take the goal updates on your OKRs? Can we take some of the stats our platform can generate and integrate that with your HRIS system? And maybe you calibrate the AI with a couple of quick questions. Maybe the AI can actually write the review for you. Could that actually work? TechDemps proved that it could. And to the point where I'm sitting there looking at it being like, I don't know if I want to build this. I don't know if I want to enter this battle and fight some of these big name players, but someone is going to do it. And those people are not going to do it with the right intentions.

17:20They're going to do it as a marketing play, as a bolt-on thing. They have performance reviews where no one uses the one-on-one functionality, and they are just going to have an AI generate some supliferous text around nothing. And people are going to feel wowed temporarily until the gimmick wears off. And in order to accomplish, I think using AI the right way and implementing this sort of AI and HR the correct way, you need the daily use. You need the use from the manager every single day, documented, properly categorized in order to build on the everyday to write that end of quarter, end of biannual or annual review.

18:03And we had just so happened to have spent an extreme amount of energy over years working on those daily habits that we felt uniquely able to build this the right way in a way that it seemed like no one else was even able to attempt. So we threw our hands in the air and said, like, we got to get this out first so that people know the right way to do this. And then that's what we launched so far. It's been amazing. Now, take me back to when that time happened. Because if I recall, y 'all were trying to do some of this pre-having OpenAI and others kind of opening their APIs. And then they had that and they kind of just democratized things in a lot of ways where you had access to these large language models that you could then apply to your data.

18:51Correct. And then it becomes differentiating because it's unique to you, even though you're leveraging something that's, I guess, you get into a whole debate of OpenAI. We've been using machine learning AI for quite a while on the, how do we make the meetings better, right? So from categorizing what you're talking about in a one-on-one, using those with AI into an engagement framework. So if you're not talking about certain things in an engagement framework, the system's aware of that. It's able to use that information to suggest content to cover your blind spots. So if you haven't checked on someone's motivation in a while, we'll recommend here's a conversation started that checks on motivation because you haven't checked on motivation with this person in a while.

19:34Things that like busy managers have all the right intentions, but they're just busy, right? They're not going to be able to keep track of like, when was the last time I checked on this person's motivation? It's more like if things are silent, I'm going to assume things are good. And until I get punched in the gut a couple of weeks down the line. So we've been using some of those things. Same with our next steps. You type a next step out. we would automatically figure out the date with machine learning. We'd automatically figure out who to assign it with machine learning, all that stuff. When it came time to think about using that to a greater extent in writing the written formal feedback for the managers, obviously there's way more data we wanted to pull.

20:14It wasn't just, what have you typed recently? It was like six months of meeting notes. It was six months of goal updates on top of data from our reporting on top of a whole bunch of other stuff. So it could generate a lot more high quality feedback, but there's also little things about like coaching and training this model. And when we first took these sort of tech demos out to folks in HR, the reaction was like, wow, I feel like I saw the future. I just don't believe it will work. Like, I just don't believe the text there yet. I'm like, what do you mean? I just showed this to you. They're like, yeah, no, I see it.

20:49I'm looking at the future, but I just don't think the world is there yet. And I think they were more reacting culturally like this wouldn't be. They feel like they've seen it, but they're not sure if they're being tricked or what's going on. And so the reaction was overwhelmingly positive, yet very reserved. And then when ChatGPT came out, it was November, December, December, and obviously took off, exploded. And everyone on their, their uncle was using chat GPT for a bit. Come January, when everyone did their annual reviews, most people on HR found out that like half of their managers had chat GPT writing reviews for them.

21:33And so there's a few times where some of the HR folks I talked to and maybe November or October, the, the prior year, we're like, you were completely right. I got it completely wrong. The world is ready for this. We're already doing it. The issue is like, obviously the chat GPT is sending private data to chat GPT. It's obviously biased in its own way. It doesn't have information about it. It doesn't have all this knowledge. Came back to say, all right, we should check this out and earn it. So a lot of the stuff I think around AI is like a cultural reservation around are we ready for it? And I think what's interesting for tech companies to catch up on is like, we have to be ready for it, right?

22:13Like the wave hits tech first. And if we're not ready for it, then we're in for a world of hurt. So I think playing with some of these things internally feels a lot more palatable than playing with some of these AI tools with like your prospects or your customers. Right. That's a little bit more scary. So, yeah, that's true. I mean, we're doing this right now at Hatchworks, right? The generative AI, one of the big areas it will impact is software development. So we're leaning into it, almost trying to disrupt ourselves before competition or somebody else does. So we're taking a similar approach where, okay, we have this new tool and functionality.

22:50How can we leverage it and empower our teams with it, ultimately our clients at the end of the day? Yeah, I heard the stat the other day of the GitHub Copilot users, which is autocomplete within your development editor. About half of all code committed into GitHub is written by an AI. So of their users who use Copilot or OpenAI's code AI, about half of the code checked in is written by AI. So I don't know. If you chart that curve a few more years into the future, like some of this stuff is like a year old, will we have developers in the way we've always known them as or we've known them recently as?

23:33Or will developers be, I think they'll still be around, but will they be doing just wildly different things, right? And obviously the developers who are doing wildly different things first will have a leg up quite a bit on those who aren't or the companies who have armies of developers like that. But for us, it's even more nuanced in that we're building an AI tool now in that we want to use the AI tools to understand what are the interfaces that work for AI right now. So a big part of like us building it right is like we actually have to artificially inflate how much AI tools we use so that we get a sense of like, oh, this pattern, this UI pattern really, really works.

24:16This UI pattern doesn't, right? We had years of understanding the UI patterns of search. We've had years of understanding the UI patterns of like top bar, sidebar navigation. How do you interact with an AI? No one knows, right? Like we're in early, early, early days of just understanding how you interact with it. And obviously the first breakout interface has been chat, like surprise, surprise, but there's a lot more. And so just rolling these out, even some, some basic things and getting not only customer feedback, which has been really helpful, but us using tools like GitHub Copilot to understand the auto-complete UI using AI is like a really powerful interface, right?

24:58Like it can predict a paragraph of text at a time, which is an incredible time. So, I mean, half of code checked in is accepted AI code. So if it can autocomplete code in your code base, like imagine what it could do on some of the more monotonous tasks at your workforce. Yeah, the QA aspect of it becomes ultra important. But then again, you can leverage AI for that as well. And I think that UI element you mentioned was interesting. One of the best explanations I've heard is CEO of HubSpot. He talked about we've lived in this kind of imperative approach of like point and click, and that's how we interact with technology.