SEASON 2 - EPISODE 186 - March 4, 2026

AI Revisited - Part 2

Following up on an earlier conversation about AI, this episode shifts to the product side of the discussion. Host Kimberly Rhodes chats with 37signals CEO and co-founder Jason Fried about his daily AI use, what it’s helped him do more efficiently, customer expectations, and how he’s thinking about AI’s role in future product updates.

Watch the full video episode on YouTube

Key Takeaways

00:12 - Putting AI tools to work
06:42 - Using AI to reclaim time, not replace thinking
12:19 - Where 37signals sees thoughtful implementation fitting in
17:16 - Why rushing adoption can backfire
18:25 - The ongoing debate from the customer perspective
21:45 - Why workforce changes aren’t always tied to automation
25:40 - Human interaction still matters

Links & Resources

Transcript

Kimberly (00:00): Welcome to REWORK, a podcast by 37signals about the better way to work and run your business. I’m your host, Kimberly Rhodes, joined this week by Jason Fried, CEO of 37signals. Now, we talked a couple weeks with David about AI and this new energy around it, specifically how our programmers are using it internally. This week, I thought we would talk with Jason about his thoughts on AI and from a product perspective, where our thoughts are. So Jason, before we talk about our products, let’s maybe talk about just AI in general. Are you using this on a day-to-day basis and what kind of use are you getting out of it so far?

Jason (00:34): Yeah. I use it for all sorts of different things. On the personal side, plenty of stuff. Business side, what I’ve been using it most for lately is actually as sort of an editor.

Kimberly (00:44): Same.

Jason (00:44): So I do a lot of writing. So I’m currently writing, for example, a new basecamp.com homepage. And I wrote this piece as sort of a letter form, which is kind of how I approach these things. And I wanted to make sure that I was speaking really plainly and clearly. And I thought I was, but I also wanted to really match it up with a lot of the language that our customers use very specifically. So we have this page on our site, basecamp.com/customers, which has about, I think it’s close to a thousand customer testimonials.

Kimberly (01:13): Wow.

Jason (01:14): And I use both Claude and ChatGPT. I kind of use them almost in competition with each other to kind of hone in on something because they each have their own style and I don’t like their house styles necessarily, but they can kind of somehow help me get somewhere that I’m comfortable with in a way that I like. So what I did was I pointed them both at the customer testimonial page and just said, internalize the language our customers are using, how they describe things, what they call things. Because for me, I might call a feature to-dos, and most people might call it tasks.

Kimberly (01:42): Right.

Jason (01:42): Now, I know it as to-do’s, the tool in Basecamp’s called to- dos, but maybe people are calling it tasks and maybe we should call it tasks, but I want to make sure that what I wrote will land with more people and just land in their own mental model of what they’re thinking about and how they’re thinking about the product. So I asked it to internalize all the language and then read my letter and then make some suggestions for ways to tweak the language, not to tweak the letter or the tone, but make sure that I’m more aligned with how our real world customers speak about these things and call these things and name these things. So for example, I was using things like stay on top of things, make sure you know what’s going on. And I like those phrases, but our customers just say organized.

(02:24): They just say, “I like that I’m organized. Basecamp keeps me organized. I’m so much more organized.” So I don’t always take the suggestions from AI, but I think it’s a really good way to gut check and go, “This phrase, this word, is this lined up with what people are thinking in their head?”

(02:40): So I’m not asking it to write the thing. I don’t like that, but I am asking it to see things that I can’t see and hold a lot of context in its head that I can’t hold and go, you know what? These four words would probably land better if they were these four words. And maybe I’ll use all four, maybe I’ll use three, whatever it is. I also tend to sometimes write in a way where I have one sentence too much in a paragraph, just like one too many sentences. And so I’ll often say, turn this into three instead of four, but don’t just concatenate them. Really, what needs to go here? And so that’s the kind of stuff I’ve been using it for primarily. That said, I also have been digging into, we’re doing Basecamp 5 right now. So I’ve been digging into some features in the product and getting in there and having it tweak some things for me and change some things for me and quickly prototype some things for me. So I could see if this idea I have in my head is even worth pursuing and it can throw some things together pretty quickly that are really, really handy that I could have done, but it would take a long time and I don’t want to sink that kind of time in to find out if something’s worth doing in the first place.

Kimberly (03:38): Okay. When you say prototype, what do you mean? Are you having it build something for you that you can physically see?

Jason (03:45): Yeah. So I’ll give you an example. We now have this feature in the product, but in Basecamp 5, there’s a sidebar with your pings in it. Currently in Basecamp 4, there’s a menu where you pull it down and you can see pings are like direct messages. So you can pull the menu down and see. Now we have it in the sidebar. If you want to open the sidebar, you can chat with people and not lose your place. What we do is we have these, currently we have little heads that show up, little avatars that show up when someone pings you. And if you don’t have the bar open, their head shows up with a little orange dot saying, “Hey, there’s something new from Kimberly,” or something like that. That’s what that suggests. And if you hit P in your keyboard, it opens it up and you can start chatting.

(04:18): And that’s great, by the way, it’s great. But once I’ve clicked your avatar and I chat with you and I close the sidebar, your face is gone. And so if I want to get back to you, it’s like an extra step or two to get back to that chat. And I found like I’m often talking to the same handful of people over the course of five hours or something like that. So it’d be nice to have this menu build up of people I’ve talked to recently. We didn’t have this in the product though. We just had the new pings. And I’d asked someone to build this, but they hadn’t gotten around to it yet because they were busy with something else. So I just built it. I mean, I didn’t do the building really. Claude did the building, but I asked it to quickly prototype this idea so heads would stick around after I chatted with somebody.

(04:58): Now in the real product, I think we have like a six-hour timeframe in which a head sticks around. If you don’t talk to that person again, it clears out. That way you’re not like having the sidebar full of people you’re not talking to, but it’s kind of kind of an active culling of people. And I was able to quickly make this work for me. It probably wasn’t like robust enough to like ship in the product, but I got it together in a way where it was working.

Kimberly (05:22): Yeah. So you could see it.

Jason (05:24): Yeah. I could mock it up myself, but that’s just looking at two states. I wanted to actually use it that way and see it work. And so that’s something that I would’ve had to ask someone else to do and I was able to do that myself. So I’m doing more of that. And that’s been really, really incredibly handy and like a breakthrough revelation kind of thing like, wow. And for me, it’s not so much like I can do things I couldn’t do before because there’s certain things I could do before that I just chose not to do. So it’s mostly like, this is a huge speed up of time and I don’t need to bother somebody else. And I’ve recognized how important this is because we’ve written this up in the past, like I think it’s called like the Owner’s Word Weighs a Ton or something like that, was this old post I wrote up about how when you own the place like I do and David does, and if we ask someone to do something, there’s just more weight attached to that request regardless of whether or not we’re like, “Don’t worry about it, don’t worry about it.” Somehow there’s still more weight attached to that. So people tend to sort of drop what they’re doing to help.

Kimberly (06:21): Yeah, of course.

Jason (06:21): I really don’t want that most of the time, but it just comes with the territory. So it’s nice to not have to ask anybody and then not pull people off of things that even if I said, “Don’t worry about it,” somehow they’d maybe get to it just because they felt obligated in some way that I don’t want to put on them, but they still do. And so I just find that I’m able to bother people less and just get some stuff in my head quicker and decide if it’s even worth pursuing or not.

Kimberly (06:42): Okay. Here’s a unique, I don’t know, unique to our use case situation that I came across with ChatGPT specifically recently. We were doing a live Basecamp, let me show you how this works, but there was data that we didn’t necessarily want to show. Chase was actually doing this. And so he did mock-ups of actual documents. He’s like, “Make me a PDF with this fake customer data, fake email addresses, fake phone numbers” so that we could show this is how it actually looks, but it’s not our account where you’re seeing these private things. And something as simple as that is like, okay, that just saved me from making it up and it did it in seconds.

Jason (07:21): It’s huge. In fact, I did the same thing recently. I should have mentioned this example, too, I’m glad you brought that up. So I’m running Basecamp locally as we’re developing it. So I have my own local database and I can screw around with it without messing up the real thing. And so one of the things I’ll often do is I was working on UI on Campfire, our chat tool in Basecamp. I was working on the UI. I was curious, there’s a lot of stuff in there. I’d like to just get rid of it and move some stuff around or whatever. But the sample data, we typically have our seed data, which is like our default account that we use when we run things locally.

Kimberly (07:52): Sure, like our demo type account.

Jason (07:55): Yeah. It didn’t have a lot of chat history in it. And so I wanted to see a lot of different scenarios with file attachments and different people having conversations longer and shorter over many days and all sorts of different things going on. And we just didn’t have that in the standard seed data in our basic data. Now, historically, I would’ve asked maybe Merissa, and she’s done this, and I think you worked with her on this too, this incredible sample project stuff, which we have in the production version, but the local version, we didn’t have this. And there was a scenario, I just wanted to sort of paint this scenario, but to make it happen was very complicated because you have to log in as multiple people to chat with fake multiple people. You’ve been through it, you probably know. So I asked Claude, I’m like, okay, just in this one Campfire, in this one project, give me like three weeks of conversations between five different users, including file attachments and long conversations and short conversations and emojis and boosts and stuff, just as much stuff as you can that would feel like a real conversation over three weeks, about five or six different topics, whatever, something like that.

(08:59): And I just said that and it populated the database and it’s like, it’s all done. I hit reload and it was pretty good, much better than nothing. Not as good as what you or Merissa would’ve put together, but I got it in three seconds or whatever. It was pretty instant. At that point though, I realized it was very repetitive and like too many one word responses. I’m like, this doesn’t work. Let’s undo that. And then do it more like every response should be at least 12 words and maybe a couple that are really short and whatever, thumbs ups and whatever. Anyway, after like a minute or two of screwing around, I just had a full Campfire chat with fake real people, with fake real conversations that helped me simply be able to design some ideas and see it in a bunch of different scenarios. And that alone is so hugely helpful. It’s like what Chase was doing, but with chat it’s especially hard because you have to come at it from multiple users.

Kimberly (09:55): Right.

Jason (09:56): Don’t want to just chat with yourself that doesn’t look like a real chat. So the fact that I was able to spin up fake data like that, fake real data was so incredibly helpful. And then you could also just be like, okay, I’m done, undo it all. And it just gets rid of it all. So it’s a sort of temporary, fast worker to do some things just to get a sense, and then you can back out. You can also leave it there if you want, or just back out and do something else. Hugely helpful for me, especially as a designer wanting to see things in a certain way, it’s hard to design when you don’t have the baseline data to design for.

Kimberly (10:29): Yeah. And when I was talking to David about this, it sounded like he, more recently, not had come around AI, but as things have evolved more, he’s been like, okay, now I’m on board in a way that I wasn’t several months ago. Are you in that same boat where you’re more onboard more recently or have you always been pro AI in your everyday use?

Jason (10:53): I would say, and I won’t speak for David on this, I think where he was coming from was a bit of skepticism initially with code quality and the whole thing.

Kimberly (11:02): Yeah, agreed.

Jason (11:03): And so then I think he was impressed by the fact that it had evolved because back three, four months ago, it wasn’t as good as it is today.

Kimberly (11:09): Right. Even just like the end of last year.

Jason (11:12): Yeah. So I don’t think I was skeptical because I hadn’t done a lot of these things that I’m doing now. So I think I’ve hopped on board, let’s just say. I mean, I was using AI personally for all sorts of like just replacing Google stuff, right? Mostly. And then at work, I was using it for some writing stuff, but now getting into product development, I’m just impressed by how quickly I can do certain things that I would’ve had to ask someone for before or really get up to speed to do again. So I wasn’t as skeptical and now I’m sold. I’m just like sold now.

(11:45): I think Claude could have done this six months ago too. I just wasn’t really digging into it in that way, but I think I’m just riding the wave right now. A lot of people, of course, are talking about it and showing off what it can do. I’m like, well, I should kind of get in there and figure this stuff out. And it’s been very, very helpful. I’m sure there’s a million ways, if someone was sitting next to me here who really knew all the things you could do and all the ways you could do it, I’m sure I could learn a lot more. But for now, the things I’m able to do, I’m really appreciative that I can do those things. I’m using it in the ways that I find it to be valuable for me and I’m not searching for use cases. I’ve got the things it’s doing for me right now.

Kimberly (12:19): Okay. So now let’s talk a little bit about our products. Of course, we’re not going to reveal any spoilers, but tell me a little bit about…

Jason (12:26): We’re not, that’d be more fun, wouldn’t it?

Kimberly (12:28): I mean, it would, but I figured you didn’t want to.

Jason (12:30): I don’t really have any spoilers at the moment, but-

Kimberly (12:33): Tell me what you’re thinking in terms of AI and our products. Is that something that as we’re launching Basecamp 5, you’re digging into? Is it a not now? And then also our other products, not just Basecamp, but HEY and Fizzy, kind of where are you thinking the next step for AI is for us?

Jason (12:48): Yeah. I mean, we explored it quite a bit in Fizzy and I think there’s of course an endless amount of things you can do and maybe we should do at some point. Things we explored it for in Fizzy weren’t entirely useful at the moment. That said, I can imagine, for example, duplicate detection, like this bug looks like these three bugs. Is this the same thing? Things like that I think would be handy.

(13:10): We had some summary stuff like summarizing a week of worth of work and what’s been going on and we just found those to be adequate but not interesting to read. And I think that that ultimately kind of pushed us back away from it for a minute. We can generate summaries, we can generate reviews of work, but like if no one really wants to read them, ahhh it didn’t feel right. So we kind of backed away from that. Anyway, that was a few months ago. David and I and Brian actually just caught up yesterday about AI and Basecamp 5 and we’re exploring some different avenues for inclusion of AI in the product. It’s also very, very interesting time because, and this is sort of David’s argument, which I buy, I also have other arguments that I’m trying to push forward, that a lot of people have spent a lot of energy building a lot of custom AI stuff into their existing products.

(14:01): The alternatives in the market, competitors, alternatives, whatever, other people in our sphere basically all have AI features in the products at some level and they talk about them very proudly on their sites. It’s very obvious that it’s like pervasive now and we don’t talk about it and we don’t have anything and that’s been an intentional decision so far. And David’s point of view, and again, I agree with it and I also disagree with it in other ways, but I really agree fundamentally with it, is that things have actually changed so much in the past month, like with OpenClaw, for example, and 24/7 running agents, things are just perpetually running for you and the ability for agents just to log in as normal people, that people are going to end up bringing their own agents to our products and just have them be normal users, like just have your agent sign up for an account and then you can grant it access and you can bring all the knowledge it has.

(14:53): It can learn everything about your product in no time at all. We’ve seen this already. We already have agents in Basecamp in our Basecamp account. We’ve invited our own. And so you can see that there’s a lot of custom work you can do to try to do those things or maybe you can wait a little bit longer and the game’s going to change where OpenAI, Anthropic, Grok, Gemini, all these things will be offering these always on agents. Just like OpenClaw is, OpenClaw is like extremely technical right now. You got to set up your own server or use a virtual server and it’s very complicated, but it’s a view into what things are going to be very, very soon. So what we can do is make the product simpler, clearer. We are working on some other stuff, some CLIs, command line interface for Basecamp that would make it easier for agents so they don’t have to use a browser.

(15:41): We’re doing a bunch of that stuff too, but currently we’re thinking that people are going to be bringing a lot of their own stuff into Basecamp. However, there’s also stuff in Basecamp that we can be doing with AI that we’re going to be looking into doing for Basecamp 5 when we’ve already begun to think about these things. So I can’t reveal anything more than that, but I do think there’s going to be this hybrid world of some native AI features within a product and then people are going to bring their own agents that are connected to all sorts of other things also and that are going to know them really, really, really well and they’re going to bring those into the product as well, just as if they were coworkers. You’ve probably seen Jeremy’s doing this and David’s doing this and a few other people are doing this.

(16:17): And it’s incredibly impressive. And it’s interesting because we didn’t have to build anything to make this happen. And that’s I think ultimately where the puck is going. That said, again, there are, I think, specialized things that we should be thinking about and things that are just more straightforward than having to think about signing for something somewhere else and then bringing it in versus just having a few things available to people. So it’s very exciting. It’s very much like on the edge of following what’s going on here and trying to determine what the best path forward is. And I’m actually very glad that we have not spent the past year building things that might be undone in a matter of weeks by a better way to do things. So there’s a point though, you can’t wait for someone else to invent the future that you want…

Kimberly (16:58): Yeah

Jason (16:59): because you might have to wait 18 months and it might be too long. So it’s figuring out the right timing for these things is always challenging. It’s very hard to call the top or the bottom of any market or any situation. At some point though, you got to just go, “Oh, this is very interesting. This is going to change. What else can we do though in the meantime that still is very helpful?”

Kimberly (17:14): Yeah. I mean, it feels like you should always be early on the early side of things, but this is one situation where if you were early, you’re redoing basically what you’ve already done and with the small teams, we don’t have time to do that.

Jason (17:26): Yeah. Look, we also have a small team. We have 62 people in the company. A third of the company might be engineers and designers really, ultimately. And AI is very helpful in allowing us to develop faster and fewer people in the whole thing, but ultimately we don’t have a company of a thousand people of which a hundred can go explore some of this stuff. So we still have to make decisions. There’s a lot of trade offs to make about what’s worth focusing on. And we currently think that the core features of our product, Basecamp, for example, that are ours that work the way we want them to work is a better place to invest most of our energy. We’ll still be investing some energy into AI and also have open arms and open doors for people to bring their own AI into Basecamp and make it easier for those AIs or for those agents to be able to access data in Basecamp. So we’re making that a lot easier. So I think we’re going absolutely the right direction here. Again, I’m glad we didn’t spend 10,000 engineer hours over the past year and a half or whatever it would be, building stuff that’s kind of going to be obsolete pretty soon.

Kimberly (18:24): Yeah. It’s interesting because I see some of the customer feedback. People write in or comment on our YouTube videos that people are very polarized by this topic. I’ve said it before, but there’s people who are like, “When is Basecamp getting AI? You guys are late.” And there’s people who are like, “Don’t touch my Basecamp. It’s like the only piece of software I have that hasn’t been sucked in with shitty AI.” So it is one of those hard to balance between those different opinions and doing what’s right for the product.

Jason (18:53): For sure. And we want to make both those sides happy, and I think we can. I absolutely think we can. Our approach is always to be as straightforward as possible, as no nonsense is possible. So slathering AI on everything everywhere all the time is not going to be our approach. And I’ve used tools that are like that now, where everything is like AI first. And I just think it’s a bit of a novelty at the moment. And I think it’s wearing thin in some ways and you just have to be careful not to sort of ruin things because not everybody wants that all the time. It should be available for sure. And others are very gung-ho about it, want it everywhere. So the good news is they’ll be able to bring theirs and have it wherever they want and do whatever they want. Meanwhile, for those who don’t want to go down that road or aren’t sophisticated enough or aren’t interested in enough in doing that, we have to provide some assistance for them as well and give them some leverage that they didn’t have before and show them that this stuff is very powerful and very useful, but also not in your way.

(19:48): So it’s a delicate balance, but this is the same delicate balance we’ve been balancing on since the beginning of Basecamp. Everybody wants more stuff. This is the nature of software. Everyone wants more stuff and everyone has their two or three requests and they can’t understand why you haven’t done them yet. And then you’re like, well, there’s 85,000 people asking for two or three things. And some of those things overlap and many of them don’t. And then you also, people will also say like, “I love Basecamp because it’s so straightforward and simple and thank God because everything else is a mess.” And you’re like, big reason for that is because we’ve held back doing certain things that everyone’s been asking us to do and it’s always a delicate balance. So it’s no different. Expectations are no different. They’re just about different things. So it’s always the thing we’ve been really good at, I think, which is understanding the limits, making things very accessible for a huge swath of people and not getting ahead of ourselves and making things complicated to benefit a handful of people who really want the most and the many, and instead just kind of figure out what’s the right collection of things that makes the most sense for the most people that’s easy and approachable and understandable for nearly everybody.

(20:48): And also there’s some more power around the corner if you really know how to get at it, you can do that. A good example of this, well, let’s call it Basecamp 3, actually all the way back to 2, kind of had a handful of tools that were, you could have to- dos and messages and files and documents and schedule stuff basically in a project. And that was the same up until a couple years ago, we added this feature to allow you to add multiple tools to a project so you could have multiple to-do sections. You could always have multiple to- do lists, but I give to do sections or multiple message boards.

Kimberly (21:20): Two separate chat tools.

Jason (21:22): Right. And so it’s still simple for everybody. There’s a collection of simple, straightforward tools that make sense to everybody, but those who want to reach around the corner and pick out a few more things off the shelf and put it on their project, they can, but it never gets in somebody’s way if they don’t want to think about the fact that they can do that. That’s always the line we’re trying to tow here. And so I think the same thing will be true with AI.

Kimberly (21:44): Okay. A little off subject, but I’ve read a lot or heard recently about the whole tech surge of people being laid off because AI’s going to take over all these jobs and we don’t need programmers and we don’t need all of these different positions. I kind of wanted to get your take on that. One of the things I think of in particular that drives me crazy with companies, their use of AI, is support and offloading that support to AI robots where you can’t talk to a real person. I want to kind of get your take on the company’s philosophy when it comes to the roles that we have here and AI, how those might be supplemented or not.

Jason (22:23): My longstanding opinion about most companies is they tend to have too many people. I think companies tend to be too big, teams are too large, and we’ve intentionally kept our company as small as we possibly can since we existed. We’ve gotten a little bit bigger than we are today, but we’re about 60 people, that feels like really good. And a lot of the people in our industry have teams of hundreds or thousands of people in their company. And I just never really understood that. Fair enough, whatever. So in general, I think that companies will often look for reasons to let people go that may or may not be true. At some point, when their numbers aren’t right and Wall Street, if they’re public, Wall Street’s demanding this or demanding that, it’s easy to lay people off. And you can say, “We’re laying people off because AI is going to make us more efficient or more productive.” And that might be true, but it also just might be an excuse to lay people off. So I don’t know. I don’t know.

Kimberly (23:17): Sure.

Jason (23:17): There’s no question that it should make people more productive, but I think people should have probably been a lot more productive to begin with. I don’t think you need a team of 12 people working on something that’s relatively small. So it’s all one and the same for me there. I agree with you that in some cases, AI-based customer service is actually quite good if you have a very simple, straightforward question. It’s also incredibly frustrating when you have something a little bit more nuanced and you just have this boiling urge like, “I just want to talk to somebody who will understand where I’m coming from, who’s not as intelligent as AI technically, but totally gets what I’m talking about because they’re human and they get it.” Right? Now, there’s also terrible human customer service out there as well.

Kimberly (24:01): True.

Jason (24:02): And that’s because people aren’t trained well and companies typically see it as a cost center, so they try to find the lowest common denominator. So it’s not that humans are better or worse at this. It’s like you want highly trained, long-term humans who know a product inside and out, are extraordinarily good, and that’s what we offer. We do offer some AI help in some places. You hit the little question mark and you can ask a question and stuff, but you just email support@basecamp.com and you’re getting a human.

Kimberly (24:32): Right.

Jason (24:33): So if we’re around in 245 years and we’re all dead and that might be different. In the short term, near term here, I think humans are hugely important. I think we have a massive advantage because we have incredibly good humans on our support team, many of which have been here for many, many, many years, some of which have been here for 15 years on support. This is a career job here, not just a temporary job, which it is the most place that’s kind of a temp job. And we’ve developed incredibly good people who have a huge depth of knowledge about how our products work and they really, really care. And I think it’s a massive competitive advantage for us and I would not want to give that up. That said, there’s also times you just want to get a quick answer. So we should have both and make both available, but it shouldn’t feel like you must go through the AI and then get pissed off enough to get a human.

(25:18): I don’t ever want to have us do that. Those are the experiences I never want to have with other people’s companies. And by the way, it’s so different than old school support, like phone trees, you’re like, oh my God…

Kimberly (25:28): Press five.

Jason (25:29): And then the recording is so slow and you just…

Kimberly (25:32): Agent. Agent.

Jason (25:32): Slam the zero button or whatever and try to break through it. I don’t want anyone to ever feel like that with us.

Kimberly (25:40): Yeah. The reason I brought it up is I recently had this terrible experience with an airline trying to get a question answered and talking to their AI bot, trying to get a real person like, okay, you’re not answering my questions, so I need to get to a real person. And literally being in a circle of, “No, I’m the bot and I can help you.” Well, you’re not helping me. “No, I’m the bot. I can help you.” I’m like, oh my gosh! Infuriating

Jason (26:01): I know. Well, there’s this sort of know-it-all complex. And you’d imagine AI technically does know more than any human at this point, essentially, but it’s still different because people relate, it’s not just about knowledge. It’s about relating to somebody and inventing, frankly, to a human who understands that you’re pissed and can feel that and understand how to respond in a way that’s still just human to human. Humans want to talk to humans, especially when they’re pissed. They just do. I mean, you could also yell at an AI and let it all out and not worry about insulting anybody either, but I don’t think that’s what people actually want. I think when people really get a little bit frustrated and sometimes when they’re writing support, they are.

Kimberly (26:45): Yeah.

Jason (26:45): They are. And it might be because they had a bad day. It’s not that the product is terrible. They may have had a bad day or who knows what happened, right? They have a deadline coming up and they can’t find this thing they knew was there. And people are frustrated for all sorts of reasons. You want someone on the other side who can meet that, absorb it, understand it, and know how to work with you on it. Now, it’s not that AI can’t be trained to do that, and I’m sure there’s some very sophisticated models that can do that, but that’s a technologist’s point of view. If I’m a human, there’s a point, and it’s not a very deep point where I want to talk to somebody. I just still do. Maybe in 20 years I don’t. Today I do. I believe that’s true. I talk to our customers, I know it’s true, and we want to make sure that we’re never skimping on that.

Kimberly (27:31): Yeah. Well, that seems like a perfect place to wrap it up. We will look forward to seeing what comes in the way of AI as we launch new products. This is a production of REWORK. You can find show notes and transcripts on our website at 37signals.com/podcast, full video episodes on YouTube. And if you have a question for Jason or David about a better way to work and run your business, leave us a voice recording. You can do that at 37signals.com/podcastquestion or send us an email to rework@37signals.com.