Culture, Knowledge, and AI: Lessons from Snøhetta + Knowledge Architecture

Welcome to the Troxell Podcast. I'm Evan Troxell. In this episode, I welcome Chris Parsons back to the podcast to talk with Kate Grimes. Kate is a Director of Knowledge at Snohetta, where she directs the flow of information across people, projects and platforms so teams can find what they need when they need it. In the fifth installment of our KM 3.0 series, we trace Kate's long game journey building KM at Snoheta from a hand drawn booklet to a stopgap intranet to today's integrated stack and how that evolution unlocked better project delivery and decision making. In this episode we explore what single source of truth really means in 2025, why structured data fields still matter, and how AI search can surface buried facts while connecting you to the human experts behind them. We discuss responsible AI implementation, prioritizing research and writing assistance over image generation, and the shift from simply sharing knowledge to effectively transferring it through learning management systems. We also examine the cultural trade offs of our digital tools, the capabilities we want to enhance versus those we cannot afford to lose, such as physical pinups and spontaneous collaboration. Additionally, we unpack the overhead paradox of measuring the value of problems that never occur, and share practical ways leaders can demonstrate ROI to maintain momentum. My key takeaway from this conversation is aligning your tech stack, which of course includes AI with firm values. We talk about building a value based tech stack and budget creating cohort, learning to raise literacy across roles and setting guardrails so adoption strengthens culture instead of eroding it. So now, without further ado, I bring you my conversation with Kate Grimes and Chris Parsons. Kate, it's great to have you. Welcome.

Thank you.

I'm a huge fan of your firm's work. I have been for a long time, ever since I think I first laid eyes on the Alexandria Library. I got to visit the Oslo Opera House in Ballet one time, which was amazing. And and then even cooler projects like the underwater restaurant. Oh my gosh. Now the story isn't about those projects today. The story is about how those projects come to fruition. I think at some level, right. Which is is really about knowledge management within the firm and how your firm is able to pull these kinds of things off. I think knowledge management probably has a lot to do with that and you guys have known each other for a while. Chris, could you introduce our guest a little bit more and give us an introduction to how you know each other for so long?

I'm Chris Parsons, Founder and CEO of Knowledge Architecture, and Kate Grimes is the Director of knowledge at Snoheta I've known Kate for 16 years at this point across two different AEC firms. And what's unique about Kate is that she's one of the first official people I ever met that had Knowledge Manager in their job title in an ATC firm. So I had a first implemented synthesis in 2023. So that means that for the majority of the time I've known Kate, it's been not as a client, it's been as a member of our community and through K Connect, our annual conference. But they have just done a kick ass job with the platform under Kate's leadership. And as you'll see in this conversation, Kate is one of the most thoughtful, strategic, pragmatic knowledge managers I know. And I'm very excited to bring her to the KM 3.0 series. So welcome Kate.

Thank you. I'm so pleased to be here.

Evan did a bit of an introduction about Snohetta, but I'd love to know kind of your perspective, like who is Snoheta? And also what does a Director of Knowledge do?

Sure. Well, Snohetta is of course an international design firm and we do architecture, landscape architecture, interior architecture, brand design, graphic design. So we're a full suite of design. And I think that is what attracted me to Snowhetta in the first place was just how integrated the design practices were are here, how multidisciplinary it is, and also how conceptual the work is and really is sculptural. And they've held onto that all the time that I've worked here. And so the projects that Evan alluded to were the things that first drew me in. And the people of course, are connected to that. So that's who Snohetta is a wonderful place and a Director of Knowledge. As Director of Knowledge, I truly think of it as directing the flow of knowledge. That's the goal of the role. And it means that I have charge of our information systems. And I think about how those information systems are connected to each other. I think about how people are connecting to the information systems, how they're putting information in, how they're drawing information out, the connections that they're making with that information and with each other. And I'm trying to establish processes for the firm to help all of those things be better connected, smoother and and meet people where they are in the course of their work so that they can find the information that they need to do their work better at a high quality, as we expect.

Yeah, can I just ask a quick question here? Were you hired in at this position, did it exist? Because if it does, which you're nodding along, I assume that like there was some foresight into the importance of a role like this. And I think there's a lot of roles that we're seeing in architecture and AEC firms across the board that didn't used to exist that now. And I'm just curious if you had conversations with them before that about like there was something that attracted you to that, but could you kind of talk about that kind of behind the scenes aspect of the strategy behind that?

Sure. My, my nod may have been misleading because the answer is actually no, that isn't what I was hired.

Okay.

As Chris mentioned, I was working in knowledge management, truly in a knowledge management role at the. A firm I was working at previously when I first met Chris. But when I joined Snohetta, it was kind of a passion move. I really wanted to work for this firm because of their work, the quality of their work, the nature of their process and the people that I knew working here. But they didn't have a knowledge management position or even anything remotely adjacent to that. What they had was an executive assistant position. So I joined Snoheta as an executive assistant. But in the interview process, it came out very early what my background was and what I was interested in. And they saw that as a positive in my qualifications for the job in general. And we talked about even then drawing on some of those skills, that thought process and building on it. And so from the very beginning, I've been bringing that thought process to bear on my work even when I was the executive assistant. So I started taking on different scope around the office from the very beginning. And then ultimately we made the decision to transition me away from executive assistant and towards dedicated knowledge management because that was what the company needed.

Nice.

Sounds an interesting journey. Yeah.

Can you talk about that a little bit? I mean, there's a little bit of an interweave between you implementing synthesis in 2023. Like you had this like very. You played the long game, right. For both synthesis, but then also for doing knowledge management. And I'm curious if you can kind of like you shared some of that with our, you know, in a webinar for us, you know, earlier in the year. But like just that journey to synthesis as well as your journey to knowledge management.

Sure. Yes. As Chris knows, I joined Snohetta in 2012 and as I said, we had that conversation even in the interview process. So very early in my time at Snoheta, I proposed the idea of bringing in synthesis, because I knew that without a knowledge management department or knowledge management leader, partnering with a company like Chris's could really bring a. Bring a company like Snohetta further into knowledge management very quickly. And so I saw a real practical purpose for that. But the company was much smaller. It was only 35 people at the time I joined. We were all in one room. We shouted across the studio whenever we needed to.

I think you should say, Kate, that's the US part of Stoheta, right?

Yes, yes, yes. That's a good clarification. At that time, there were two offices, only one in Oslo and one in New York. The New York office is where I'm based and where my scope of work is really focused right now. And at that time, the New York studio was 35 people in one room. And we truly did shout across the studio all the time. So the premise of investing at that time in a platform like synthesis, it looked like overkill. Despite my instincts, it looked like overkill and I understood that. So we had Chris and his team come in and demo the product. But we ultimately decided not to implement it at that time.

And you made a printed out guide instead?

Yes, a few years after that.

It was beautiful though, right?

It was beautiful. But yes, a few years after that there was, you know, the company was growing. There were all these platforms that we had started to amass and connect with each other and new protocols and everything like that. It was becoming more complex and there was a need to codify some of that. And so there was a decision to make a booklet. It was a beautiful booklet. It was, you know, hand drawn. It was very snowheaded. But as I was flipping through it, and even I wasn't the one even leading that project, but as I was contributing to the content and flipping through it, all I could see in my head was that this was a printed form of what could be an intranet. All the initial content was there.

Yeah.

What do you think?

You need to update it. Right. It's like people are just like architects, like to redline things. I'm sure that there was a lot of that going on.

Yeah, absolutely. And the pace of change even then, this was around 2014, 2015. The pace of change even then was too rapid for a book to keep up with. So we did reprint that book three times in less than two years.

Yeah.

Yeah, I bet.

So that was interesting. I took that as an opportunity to pitch the idea of a synthesis based intranet again. And even then it still didn't land exactly There was some discomfort with this social media aspect of it. The wall, the social wall felt foreign to us at the time. We didn't have communication platforms that were that real time yet. We weren't yet using instant messaging and all of that. It's amazing to think back to what was not that long ago and how different everything was from a technology and communication perspective.

For listeners who don't know what Kate just is talking about, Chris, it sounds like you were ahead of your time when it came to the integration of this social aspect to. But also a super important aspect of an intranet. Right. Which is to encourage people to participate in it. So could you just give us a quick elevator version of what that is?

Yeah, I mean, you guys know the scene from Back to the Future where Marty McFly is playing Van Halen to a bunch of kids in the 60s and said, well, don't worry, one day you kids are going to love it. Yeah, yeah. So like when I was in house at the second architecture firm, like I was super into Twitter when it first, first started. And to some degree LinkedIn, to the degree somebody's super into LinkedIn, you know, and Facebook, that had all started. And I'm like, sorry, LinkedIn. I'm like, how do you, how can we take this knowledge sharing technology that's happening in social and bring it inside a company for sharing lessons learned or asking questions or new technology updates or whatever it is. And so I started prototyping like really crude, really crude versions of this. Like, and we had multi offices in the firm I was in. And it was like amazing. It's like you could post something and something in LA could chime in. And so when we went, when we started Ka in 2009, this is what we call the KM 2.0 wave. So we're doing this podcast about KM 3.0, which is about AI, but KM 2.0 is about bringing social into the business for knowledge sharing. And some firms were like, this is the coolest thing I've ever seen. Let's go. And other firms were like, yeah, not a chance. What happens when somebody posts something inappropriate? They answer the question wrong. Can we approve everybody's posts and comments? Like there was, it was a massive, like cultural shift. This is pre teams, pre slack. It was basically like intranets were these static repositories of documents and some, if you were really lucky, like pages and then you had email and the network share. That was it. That was like the information ecosystem. And like we just came in trying to do what we called a Social intranet at the time, which, yeah, like now that seems really quaint that it would be a big idea that anybody in the firm could share and give feedback or ask questions. But that was a massive cultural change that happened huge. And so we caught Kate kind of. They weren't quite, quite ready for that yet. We weren't.

I was very ready.

And a lot of other firms, a lot of other firms in New York, if we're being honest. Yeah, right.

So yeah, no, very much. It was harder for everyone to accept that idea then the rest of the package was much easier to accept. But that social component was still a little bit of a hang up.

I got told Kate by a firm I won't mention in New York. They said exactly what you just said. We love everything. We like you guys, but this stuff is way too California for us.

So true.

There we are.

Yes. So that's where we were in 2015, 2016. But at that point, I mean, I already knew I was playing the long game. I wasn't even hiding that from myself. And I had the idea around that time. Having seen the booklet, having done the demo again and received the no answer again, I decided that it was time for me to build a proof of concept. Just to kind of demonstrate really what the power of a tool like this could do. Because again, at this point we just had so many platforms that we were beginning to use and it was only we were growing even more, our platforms and information systems were growing and it was getting really quite out of control. So I started to build an intranet of my own design in Squarespace, which was meant to be truly just a quick and dirty kind of put it together, me and one other colleague and just demonstrate the power of an intranet through that. And it wasn't meant to last more than two years at the outside. And I was really hoping it would do the job in less time than that. But we ended up hitting right at that two year mark, hit right around the time the pandemic swept through. And so at the time, I wasn't yet fully the Director of Knowledge. I still was wearing many hats, including the Director of Office Operations. So I really had to transition from wearing the Knowledge hat to the Office Operations hat during that time just to get everybody set up, working from home. I was supervising the IT department. Still, still do. But I didn't even have a full time in house IT person on that team. So if I had my hands full. So that intranet that I built on Squarespace took us all the way through 2020. Three, all the way through the pandemic and coming back to the Office. At that point, everybody had completely bought into the idea that we really needed this online intranet platform that brought a lot of information together and kind of was a single portal that people could go to for information and company resources. But we just didn't have the time or resources to get into a new project and launch something like Synthesis. So we finally were able to do that in 2023. Kind of circled all the way back around.

What helped you push that over the edge, Kate? Like that. Like this is where Squarespace finally ran out of gas and you needed to kind of go to the next level.

Yeah, it was things like the integration with Open Asset. We really needed project information and I wasn't able to deliver project information on Squarespace because it would have been so manual and you know, the pace of.

Projects, friction of effort.

Yeah, absolutely. And I didn't have the people for that. So Project Information was a big push. And honestly, ironically, it was Slack, I think, because at this point we have been using Slack for a long time and people were starting to rely on it as an information base as well. But it doesn't really do that effectively. And so I brought synthesis back up and made a price comparison to the features and functionality of Synthesis. But it comes not only with the integrations with our key information bases already as part of the package, but it also comes with Chris's team. It's not just about the functionality, it's about the relationship and the community that we get from synthesis.

When at this point, Kate, in this journey, if we're kind of double tracking this, like. So that was kind of like the synthesis evolution. When did you become the Director of Knowledge, or Director of Knowledge Flow, as we might start calling it?

I'm not sure that's a great question. I always have to think back. Some of those milestones feel fuzzy to me. It was around 2020 that we agreed that that was going to be the future of my role. But of course I was still functioning and I still function to this day as the Director of Office Operations and it. But we have developed my team in the past five years to support those other functions better so that I have more time to be the Director of Knowledge. So now we have a full time IT person who's managing IT processes for us. And I have a team member who handles reception and general office support. And I have a team member who is now handling Office Operations. So simply by developing my team, we've allowed me to focus more on Being the director of knowledge. So that's happened incrementally over the past five years. The decision around 2020, the implementation probably started around 2022.

What is it about knowledge that draws you to like, you know, you did the role before your previous firm, you played the long game through many like chutes and ladders to get back to doing knowledge again. Like, why, why are you drawn to it?

I think problem solving is my number one favorite pastime. I like puzzles and if you give me a problem to solve, I kind of latch onto it immediately and can't let it go until I've been able to make some progress with it. And knowledge management to me is fundamentally about problem solving. It's about preventing problems in the future to me. And that's the ultimate solve. If you don't have to face that problem again, then it's been truly really solved. And knowledge management to me is about looking out for ways to set people up so that they don't have to confront those same problems. They'll always confront new problems. But if they don't have to confront the same problems over and over again because they're able to refer to information and past experiences of other people and learn from them and you know, that's, that's the goal.

You're living in that quadrant of the famous two by two which is non urgent and important.

Absolutely.

That's where the preventative stuff happens, right?

Yeah.

Is like you're trying to, you've known these people for a long time, like to some degree, I'm thinking it's probably personal. Right? It's like, oh, I know exactly who I'm saving from stepping into this pothole, you know?

Right. It is, it is. I mean, it's always personal wherever. It always would be personal wherever I was. Yeah, I think, I think that's who I am. But absolutely, yes, I'm very connected with the people and projects here. And so ensuring that Snohetta continues to grow and succeed because of being able to solve and prevent problems in the future is definitely it's a mission.

Let's talk about some of those problems then. Like, what is knowledge management at Snowheada today? Like, what are your priorities? Where is it headed? Like, what are you, what are you working on? What problems are you trying to prevent?

Having still only recently implemented synthesis, I am still working on getting some of the back information really filled in so that it's, it's there and ready. So project data, I mean that's a classic one, but every time I go to the conference. It's still amazing to me how much we're all wrestling with project data, even though we've been talking about it for.

By project data, what kind of data are you talking about?

Sure. I mean all the project information. So everything from the hard data points, like when did it start, when did it end, what were all the milestone dates along the way, what's the size of each of its volumes, how much did it cost, who was involved, all of those hard data points, as well as the softer things, the narratives, what did it mean, how, you know, why did we do what we did? All of those sorts of things, the images, the other project assets, all of it, top to bottom. Some of those data points, I actually want to be in specific places so that they show up in specific places on the Internet and are easily findable whether you're searching or browsing. Others are just in other storage volumes that I want to make sure are connected and backed up and all the things. So we're still wrestling with that. That is an ever present problem or an ever present challenge, I should say, in our industry. But we are also wrestling with the proliferation of information and communication and creation platforms. So all of that, that has been growing since I joined in 2012, continues to grow. And now we're getting blasted with emails every day about AI features being added to everything.

Right.

Subscriptions being, subscriptions being updated because of AI features being added. You know, all of that is happening and it is breaking everybody's focus. So all of our employees are now looking at different, the newest, latest thing that's being advertised and asking questions about can we use this for this, et cetera. And we already had a problem of just connecting what we had and trying to create that single source of truth. But every day new software inventions make that problem harder and harder.

Yeah, you just brought up the term. I wanted to go back to it because you had mentioned it earlier and how difficult it actually is with this digital sprawl that you're talking about that everybody's dealing with. Yeah, and like features here, Web interfaces for all these different, you know, whiteboarding apps. There's so many things out there where information can be stored that is not in your in house, on premises server.

Right.

And I thought it was interesting that you alluded to, okay, there's certain things that I want to directly connect so that that information shows up in the exact spot I want it to on the Internet. But then there's also things I want to link out to. And so when you think about a single source of truth. The reason I just bring this up is like, this is a huge. It's a huge topic. Single source of truth used to mean something different than it does today. And so even that is an evolution. Right. And so I'm just curious, like, what's your internal process to kind of vet that? And maybe it's completely a work in progress all the time, I don't know. But as we're seeing this kind of asymptotic curve of fire hose, right. Things coming at us, how are you dealing with that? Because you're also overseeing it and you are getting those terms of service upgrade notices and the costs and all those things. You're seeing all that.

It is my biggest challenge, I would say. I. And as far as a process, I think that is an evolving thing. It is. I don't have a clear answer for what that process is. I think it's something that we're trying to define. Chris and I have talked many times over the years about how knowledge management has to fit into the culture that you're working in. And you kind of. You need to meet people where they're at. And the culture at Snohetta has always been it's not super top down. And so there's a lot of expectation of some amount of individual autonomy working within the collective. And so we want to be collaborative and connected, but also we want to leave room for people to individually experiment. So we haven't had the most locked down, rigorous system historically as far as bringing on new tools, vetting them, you know, disseminating them. It's often more ground up than top down. And I don't want to ruin the spirit that that brings to the studio, but at the same time, you know, the. The IT landscape has changed so dramatically. There's so many more security issues and privacy issues that we're facing with all the new software advancements, I suppose, today. And so we are currently wrestling with what is the best approach to preserve that sense of experimentation and individual empowerment, along with the importance of the group collective and the integrity of that. So just this week I was having a conversation with our IT manager and our design technology lead about revamping our IT budget based entirely on values, and so defining what are the values we want IT to uphold and then evaluating the tools that we're using and how they align with those values and. And try to rebuild our software and technology learning and development budget from the ground up based on that instead of just what we've always been using.

I ran IT and two architecture firms before starting ka and if I could compare my budget back then to what a budget looks like in 2025 for an AEC firm. Oh my God. It was like I could see it all on one screen, let's put it that way. Like there, there were just. Because there weren't even that many software companies in AEC back then. Like there were like what, 12, you.

Know, they were perpetual licenses. Right?

And they were perpetual licenses. So. Yeah, so true. But it's like so interesting because so many things, you know, at the conference, you know, we talked about that Knowledge architecture thinks more is going to change in AEC knowledge and learning in the next five years than has changed in the last 25. Like we just think it's that much of a sea change in the way that we're approaching things. But that's even finding its way maybe into things like budgeting. It's like maybe the old way of like even budgeting for technology, let alone that it was done by it who's not in the practice generally, like who are marketing is going through it to get permission for tools that they need to do their jobs. Like. Yeah, I feel like it's interesting, like even the budgeting part of this is probably going to get another, another look.

I think so. I mean I think it probably needed to change a while ago and I'm sure that some firms have, you know, they foresaw that and they did change. But you know, with the, the transition to all the different web based software subscriptions it that also has contributed to creep because it's sort of like, well, it only costs $25 a month, you know, what's, what's the big deal? And then you kind of like all of that just grows exponentially and all of a sudden you step back and yes, you can't even fathom all the subscriptions you've agreed to. Little one off experimentation things here it becomes hard to account for. And that's happened to us especially the pandemic really exacerbated that. Just the like splitting apart and everybody having different needs based on their home offices, their different project demands, et cetera. And we took on a lot of new subscription software in those couple of years and I think that's what we want to try to assess and walk back from a little bit.

I'm curious if we were to listen to this conversation three or four years from now how it will play. The history of technology is expansion and consolidation and expansion and consolidation. And I do wonder if you've got less line items three years from now because you'll find instead of having six tools that kind of do this thing a little bit, that you can find like one tool that's like evolved enough that it's like good enough to be the kind of general purpose thing or not.

That's what I'm hoping. Especially with all the AI software, I really, I don't want us to take on a ton of new AI tools just because they're the latest and greatest thing and they each do this little niche thing. I would like to have a system for sort of vetting them as they come along and the quality and what they contribute to our work and our culture and try to focus on only bringing on the best, the ones that rise to the top, rather than the ones that just are thrown at us every day.

Can I throw my bed in here real quick? I'm guessing it's not going to be like that. I totally understand why everybody wants that to happen. I just don't see it happening. I see it getting fine grained and just tons of tools that are purpose built. That's how I kind of see it happening. Because I think a lot of times you see these companies come out with something and then because of the VC funding mechanism on all those, it's like, oh, now we have to start to widen our footprint and there's so much crossover and that's where things get difficult. It's like, well, if you would just stay in your lane and do this one thing super well, I would totally use you. But now that you're competing with this other company, now I'm forced to pick and now you just keep leapfrogging each other and I always feel like I picked the wrong one and, but I, and so I'm not painting a beautiful picture here, but that's just kind of how I see it going for the next five years.

No, I mean, you're not wrong. I actually was just having that conversation with the software company this morning about how that is. You know, they were calling us to talk about upgrading our subscription because of all the new features that overlap with all the new features of everybody's software that, you know, so. And I was explaining to them that to me that's not a value add. It's actually, it's a detraction for, for.

Me, because they are distraction.

Well, there's, there's a, there's a new book out this year I think called. They're called Jolt Selling. I listened to a podcast basically during the pandemic because everyone was, you know, in front of a screen. Tools like Gong and Zoom were recording all the sales calls and they got this insane corpus of data to be able to analyze sales calls and like, what happens and why people buy and why people don't. And the fundamental takeaway from that book is that like something like 75 to 80% of the time, people don't say no and not buy your software. They say not yet. And when they dig into it, it's because they're afraid of making the wrong decision.

Yes.

Not that like your thing isn't great or they don't see how it could be useful. It's like people are terrified of making the wrong decision. Some of that might be generational too, but like, it's also. There's like, there's so much choice now.

Yes. Yeah, it's interesting. Well, I agree with you, Evan. That's true. I think that is something to be avoided. I still would want to make sure that even if we're choosing specialized tools, that we are really thinking about them. Not from fear of making the wrong choice about the software, but for fear of making the wrong choice about what we need the software to do, if that makes sense. The new shiny thing is exciting even to me. But oftentimes we find that we didn't need that new shiny functionality and our work was perhaps better before we started using it. The software itself might be fine, but how it affects our processes and our culture are what I want to be more cautious about going forward.

The nimbleness that is going to be required to constantly go back and look and see is this serving us or is it not? And getting rid of the stuff is the new normal. And that to me is actually super required because we see the bloat that happens over time. It's like we just keep adding, adding, adding, and that is not sustainable. So now on to segue, Chris.

Yeah, well, no, now I'm changing it. No, it's interesting to listen to this. With two lens, it's like one hand. It's like we're going after Cam 3.0, but from my seat. It's like running a technology company who has expanded their reach. Right? So moving from just intranet to intranet plus LMS and adding in the AI stuff. Like, I agree with everything you're saying and yet we're also doing it now. I could argue we're doing it for very strategic reasons and maybe we're doing it better, maybe we're not. But like, that's because you see, there's so much opportunity. And I think we can kind of transition to knowledge management at Soheta, but kind of like how you're using AI rather. But to us like the, the view is like to really provide a really good AI experience, you want access to as much high quality, firm wide knowledge as you can. Right. And so it's why we built all the investments in video, it's why we, you know, are building a learning management system is because we want people to have one place to go to like get answers to questions about standards or how we do things or how a piece of technology works or how many projects we've built in this sector over the last whatever years. We want that to be a really great experience and that requires more integrations and also adding scope. So I'm giving it from that perspective. But I also can empathize with how it might feel for someone else seeing everyone doing that kind of thing.

Yes, you do it at an entirely different pace and with apparently different motivation than most software companies in my experience though.

So what are you doing AI wise? I know some of what you're doing, but for our people listening, what are you doing with AI and knowledge management? What does KM 3.0 look like at Snoheta?

Well, we were just at Ka Connect and I had a debate with our design technology lead as one of the presentations at the conference. And the debate between us was about the whether to rush into AI tools or not rush in necessarily, but you know, jump in head first with great enthusiasm to all the AI tools or whether or not there's a different approach. And my premise was that it is better in this moment to slow down a bit even while we're getting the fire hose of AI information and offers and upgrades. I would rather slow down and consider the field and the tools that we're taking on, rather than just take on a ton without much thought about it. And part of the reason is because I saw what happened in some of the software upgrades that we've taken on in the past five to seven years and how much they have changed our working culture. So we talked in that debate about how the sort of rapid upgrades in real time rendering and everybody's excitement about using those tools and how much efficiency they could bring and the ability to iterate much faster. And in that same time we have seen much less physical modeling, much less physical collaboration like interpersonal collaboration. I see people glued to their computers in ways that never was true prior to that shift in software. I saw a similar impact when we took on Miro at the beginning of the Pandemic I now hear the lament almost every day that we don't have physical pinups often enough in our studio anymore. It's because everybody is choosing to have those pinups in Miro. Yeah, yeah. So these things are sort of core to our practice and the way that we say that we want to work physical, interpersonal, because these are ultimately the qualities of the spaces that we want to design. They're about humans and the other beings that inhabit them. They are inherently physical and social. So designing physically and socially is important to bring that same quality to those spaces. And it's not that we don't do that we do, but we just do so much less of it because.

We.

Didn'T talk as much about the impact that the technology has on our processes. And I think that facing this sea change which the AI revolution is, I believe I agree we need to be very thoughtful about it and I don't want to just fall into the trap of responding to all the hype, not.

Just how much does it cost or what is it to manage, but like, how is it changing us?

How is it changing us? Absolutely. And so we're taking that stance. We're proceeding a little cautiously and I really want to sort of lay a foundation first. So we are talking about establishing sort of a company wide learning program that will, that would be cohort based and sort of bring everybody on board and level set across the company about expectations of what AI can do, what it's best at versus what it doesn't do as well, and what we want it to do for us versus what we don't want it to do for us. And some of what we've already identified is we find it really useful for research and sort of like data processing, data mining, finding things in big sets of information. It's fantastic at that and it's really helpful and that's a great value add. But we haven't found as much value in image generation yet. And so we aren't using it as much for that as we are as more of like a writing assistant and early design phase ideation sort of tool.

Chad kind of talked about that at the conference. Can you say more about like why you found like image Gen isn't landing for Snohetta. And there was this great quote in that section of your presentation, like, I don't use AI for design, I use it for ideas.

Yes.

Which still makes, every time I read it or hear it, it makes me laugh. But like, can you talk about more what that means?

Yeah, absolutely. What we found Is that when we experiment with it for image generation, the images that it comes out with, it depends on the prompt, of course, but oftentimes the images that's coming out with is of a designed or it appears to be a designed building or a designed landscape. It's already delivering the whole package. Whereas when in our typical conceptual process we are looking at abstract ideas, we're drawing metaphors with natural forms or, you know, geometric forms, whatever. There's a lot of abstraction is truly the word abstraction. And metaphor is what we're usually looking at in early concept design. And so seeing a finished building, it goes way beyond that level and it starts. It starts to be like a period at the end of a sentence rather than more of an ellipses, which is I think what we're going for in the early design phase. So we're having more luck or more interesting results just by using text based conversation. If we use AI for ideation at all, it is more often for text based sort of back and forth of feeding it a bunch of ideas that came out of a group brainstorm and trying to get it to escalate those ideas, amplify them. And that's what the person was referring to when they said I don't use it for design, I use it to generate ideas is they are literally throwing a bunch of their ideas into an LLM and seeing what happens when they try to dial all of that up. And then they're extracting ideas from that and taking that back and using that to do more image brainstorming. And that is generating more interesting, richer results than the image generation tools themselves.

I love this idea that you're talking about and it seems to me it really requires knowing your values. Like this idea that you proposed a few minutes ago about refocusing the way you do budgeting based on the values that the firm has and using technology to augment the values of the firm. But like megaphone out to the world value. This is who Snoetta is. And this is why we do what we do is super important to keep that feedback loop going internally, but as well how that makes it out in the world. I love that idea of kind of this whole value based tech stack that you're talking about.

It's a conversation that Chad, our design technology lead and I have often, because it is something that's been very important for him throughout his whole entire career, is the impact that technology has on the design of spaces. It's something that he was interested in, you know, even before he started his professional career. And it's still the case. And we see it every day like the buildings and spaces around us change because of what the technology we use to design them is capable of doing. And that's wonderful and so interesting. But it also means that we can start to develop spaces that truly do leave behind the humans and the other beings and ecosystems, because the technology isn't connected with all of that in the way that we are so maintaining that connection and making sure that we are intervening to create the balance between those two things. We want to embrace technology and everything it can do, but we don't want it to have. We don't want it to be in the driver's seat, in my opinion.

Chad kept using a Marshall McLuhan quote when we were preparing for your Talk about like every new technology is both an amputation and a augmentation, I think is how it went.

Every augmentation is also an amputation.

Every augmentation is also an amputation. And so Miro augments you, but then it cuts off pinups and whiteboards and, you know, all that kind of stuff too.

It's true and it's possible. I mean, it will always be true. The augmentations will lead to amputations. But what we've talked about is that we want to be involved in making the decision about what's amputated.

You don't want it to just happen to you.

No surprise amputation.

Amputations. No surprise amputations, please.

That's not the title of this episode. Evan, I know what you're thinking.

Making an executive call right there.

I see.

There was a great vignette. So for people listening and that haven't seen their K Connect talk yet. I don't know. They're going to come out around the same time, so please go watch it. But there was a section around. I don't remember the project name, but you were doing these facades and you were writing custom programs. I think it was in Python to be able to even do all of the complex facade. But then the person that wrote the program left.

Yes.

Then what happened?

This never happens. This doesn't happen.

Never happens. I know. It's the classic knowledge management conundrum, right? You have a very heavily knowledge based task or project and the person who had the knowledge leaves. Something happens and they leave. They're not there. And that happened here. And because the team had some facility with AI tools for coding, our IT team has facility with that. And our different team members had been experimenting with it and so they were able to Use AI assisted coding tools to bridge the gap between what had been written in Python to what needed to be written in C and expanded to recreate the facade pattern across 1800 panels that were all individually different. And so they used the AI tool to close that knowledge gap. And I, you know, I respect that as a technique. I think it's a smart solution to the problem and it certainly got the job done. The question that I raised, though, is, you know, they were Vibe coding, and if everybody decided to vibe code every time we need to do computational design, I feel like that would be unsustainable and would lead to less knowledge development than more.

Less knowledge development. And also just liability. Like, not liability, right?

You know, Absolutely. Yes. Yeah. So, you know, it's one thing with a facade pattern, there may be a low liability there, but if I guess.

I mean, like a knowledge liability, not a. Not a.

No, no, no, you're right.

Safety and welfare liability isn't where I was going.

No, fair enough, fair enough. Lia. A broad term. No, but you're right. Yes. It's a knowledge liability.

Yeah.

I think what's super interesting about this thread is that you can use the large language models to interrogate code and say, tell me what this is doing where that was never a thing before. And so to help bridge that gap can also become a learning process to upskill people who are taking on those new responsibilities. Because every firm out there has code laying around for some bespoke tool on a project. It happens, right? Like, not every tool can be reused. A lot of stuff just is purpose built for that one thing. But there's a higher chance that it could be reused. If there's something that can explain it to me, who has never looked at that spaghetti of whatever that is.

Uncommented code.

Uncommented code, Grasshopper scripts, Dynamo scripts, whatever those things are to then teach me. Oh, and then. And also, like, look for issues. Right. I think this is a pretty amazing development that I don't think we really saw coming.

Yeah. And that's actually where we. Where we went from that conversation in our presentation about the Vibe coding and the potential liability that it brings to the value that AI can actually add there by not only helping to bridge that knowledge gap, but also to document what they did and why. And as you say, you can also use it to go back and query the thing that you didn't know about. So there's actually, at the same time, there's a danger and a liability implied. There's an opportunity at the same time, that AI can answer. And that's what's really interesting. And sometimes frustratingly, yes, I could imagine. Yeah, it sort of creates its own conundrum where it's truly a blessing and tension.

Yeah, that tension is totally real. Yep.

Yeah.

What, Kate, self serving question. What are you been? Well, you've been in the synthesis AI search beta since the very beginning. Tell me about what you're doing with it. Like, how is it? What are you excited about the capabilities for it to do for Snohetta and how is that impacting the way you're managing knowledge to take advantage of what AI can do?

It's a lot of interesting things. Before we started experimenting with it, I was very focused on the idea that I was going to be filling in all of these data blanks right away, as soon as I got the basic framework of synthesis set up, that my very next priority was going to be going around and filling in all the project data blanks that we were talking about earlier, that it was going to be a very focused process of truly filling in the blanks. And then we started using the AI search and I was starting to find little bits of information hidden away in corners that I didn't know was there. And as soon, you know, it was like documents that I didn't expect to have, any project information had been uploaded and they revealed little data points. And the AI search started to bring those to my attention almost immediately. And so then I realized that there was an opportunity to use that as a tool to make it a less onerous process for me and others around the studio. If we upload more of the documents that already contain those data points and then use the AI search to get at them and then fill in the blanks, it really can be a time and effort saver to save someone from having to answer the question they already answered 50 times before. So it's interesting for that. It also means that people, other people than me, are already stumbling on that information. Even though my project of backfilling the project data isn't done, people are still finding that project data even without me doing it, which is interesting and unexpected. So it means that we can be now progressing in parallel more, rather than them waiting for me to finish something for them to experience it.

I mean, I'm inferring what you're saying, something in what you're saying, but I don't want to make sure. So I'm kind of imagining you're talking about things like town halls or design crits that talk about projects or maybe a past proposal or something like that that talks about a project that's what we would call unstructured knowledge. You're going to go behind and kind of populate a structured database that's a little more tight and tidy and accurate and audited. So that's kind of. The unstructured data is kind of a bridge until you have better structured data to replace it. Is that my understanding that?

Right, that's correct. And some people have, of course, wondered, is it even necessary to go fill in the structured data if you have all that unstructured data that's already doing that. And the answer is yes, because we've found this out through testing. The AI is going to more reliably pull the right information from the structured data fields. That gives it all the context and that it needs to understand what that data point is. And it will more reliably serve up the right answer if the data exists in the structured field. But, yes, I can already get at some of it through the unstructured data. And as long as I or somebody else who's qualified to sort of vet that data and make sure that it is the correct data gets into the structured field, then we can use it that way. If I left it completely unstructured, you know, every firm, I'm sure, has this where the square footage of a building has been written down five different ways on five different documents. And so if I left it unstructured, you would get a different answer each time you queried it.

We call it pulling the slot, the AI slot machine lever, you know, and like, you know, we'll just see what answer we get. Yeah. So five stars for your answer on structured data. I am aligned very much in everything you had to say.

And a term that keeps coming up, which I know nobody likes to talk about here, is just like this overhead of doing what you're talking about. Right. You've got to have people do the thing to get the data into a structured form. And I imagine there's a bit of a, oh, wow, what if we don't need to do that? Because the AI can do some of that. Even though, like Chris just said, sometimes as a slot machine, you still need to kind of chase it down. So you're still spending time either through overhead to accomplish that task or through following up and making sure with your staff who's not overhead doing those kinds of things. I'm curious how your firm sees that. Obviously, there's been some intention around putting you in this position of doing this thing, which is an overhead position. But for the benefit of the firm. And so there's some kind of value attached to that. But I'm just curious, how are those conversations that you have all the time about overhead? Because again, there's value, but it takes time.

I wake up every morning thinking about the impact of overhead on all of this, and I go to bed every night thinking about it. Absolutely, yes. I mean, we've had a lot of debates internally about whether or not this actually qualifies as overhead or whether it should be qualified as part and parcel of the process, project process, and therefore part of the billable work. And, you know, I see it both ways. On the one hand, making it overhead, calling it out in that way. It gives it a certain amount of attention and autonomy of a sort, you know, in the. In how it's viewed. And it also gives you a little bit more flexibility. Like you're not limited by what we've promised. The project value is going to be. You. You can do it as overhead, and it doesn't have to be hemmed in by the project valuation. On the other hand, if you can call it billable work because, you know, it's in the course of work that you're developing this knowledge and that you need to document this knowledge for the success of this project that you're working on and also the next project that you're working on, you know, then. Then it's less of a financial liability. So there's, you know, there's a tension, and I think it's a little bit of both. And so to me, it's about minimizing the overhead and making sure that most of the processes support the work in the. In the course of the project work, but without creating too much of a liability for each individual project. I don't want to infect. I don't want to unfairly inflate the cost of doing the work. But to the extent that a lot of this could be optimized so that it does just flow as part of our natural project processes, then it could reduce the overhead for the company and for each individual project. And that's ultimately my goal. But I do think that it's important for the company to invest a bit into this as part of the company values. And there's. There is a chunk of this that truly can't be encapsulated in individual projects and that we need to make sure that we are putting the attention there.

You touched on this earlier. It's a conversation that you and I have had many times. It's like Working within the culture that you have.

Yes.

And I'm paraphrasing here, so I apologize if I'm not quite right, but I remember you saying something like snowhead is, I don't know if you said, suspicious or highly biased towards projects versus things that aren't projects, meaning project work always comes first and second and third. And then there's stuff that's outside of projects, and that's a spectrum. Some firms are just like you described, and then there's others that they are kind of like businesses who happen to do architecture versus being design firms who happen to have to do business in order to keep doing design. You know, there's like a whole spectrum there.

Yeah. And I. Yeah, I hate to say that they're suspicious of anything that isn't project work, but the art.

That was maybe too sharp a point to put this.

I don't think that's true. But there is. I mean, we're very focused on our project. We are project forward, for sure. And so to the extent that anything that we're doing as a business really supports the project work and is clearly tied to the quality of the project delivery, then that's embraced. To the extent that we lose the connection between those two ideas of like, we've got operations working over here on one thing and we've got project teams working over here on another thing, and they are. They've lost the connection. That's when it becomes problematic.

So, like a change management perspective, I think what you're saying is you need to show the benefit to project teams of all these different things that you're doing on the business side.

Yeah. To project teams and ultimately the project delivery, the quality of design is number one, the end. The quality of delivery is, you know, side by side with that. That's our number one priority. And so everything that I do with knowledge management ultimately needs to be in service of that. Otherwise you're right. Then there is suspicion about it, like, what are we doing?

But this, this overhead thing keeps coming up in my mind, which, and I want to say this thing like that, I think just has to be said, which is like, we can't measure things that don't happen. Right. And all this proactive stuff. All this proactive stuff is so that bad things don't happen. Right. Or so that we can minimize the amount of time it takes to do this thing that we've done 50 times, but nobody ever documented, like, it's stuff like that. And so I don't know if you guys have any ideas of how to measure things that don't happen. I would love to hear them.

But.

But to me, like, there's a huge value here that is.

That.

That's. This seems like a conversation that shouldn't need to happen, but it.

It does.

It needs to happen all the time.

Yes, it does. Yeah. And I'm big on that. I'm big on overhead.

You have a thesis on this?

Yeah, I could write a thesis on it at this point, I think. But yes, being able to categorize what we're doing as overhead and track it as we do projects is very important. And I know a lot of firms do that already. It is not what Snohetta was doing when I came in. And it hasn't been what Snohetta was doing for a very long time. Like, really carving out chunks of overhead effort and tracking them as projects in themselves. It was kind of just like a big bucket of overhead and then project work. And that was revealing of that value that we talked about earlier or in this conversation about the focus on project quality and delivery. But what I ultimately needed to carve out space for overhead projects to be defined and have a similar amount of care taken with what they encompass, what the delivery looks like, who's working on it, how much they're working on it, and all of that sort of stuff. So tracking overhead in that way is very important. And even if we are doing some part of it as part of the project delivery, I've been trying to work out with our teams how to call it out as what it is as part of the project delivery that it isn't necessarily putting in that big bucket. Yeah, yeah, exactly.

Makes sense.

I've got some stuff about measuring things that don't happen.

I was going to say that AI can do that.

I've got three examples. Well, I mean, it will tell you that it can. So a few things like. So we've got a client. The first one's a synthesis thing. We have a client who's using synthesis AI search to help with proposal development and specifically answering RFP questions. And so she took a proposal and measured how long it took pre AI. And it was something like 18 hours, 16 hours. And then with AI, it was two or three hours. So that's like an 80% improvement. So of course it requires you to do measurement upfront in order to compare it against the other thing. A lot of our clients use things like engagement surveys to understand, do people feel like they know what's going on in the company? Do they have the resources they need to do their job. And again, it's kind of before and after. So when everything's smoothing, you have to have a, in order to do a post occupancy survey, you have to do a pre occupancy survey.

Right.

Like, so you have to have like both sides of the data. We have a client who implemented a whole learning and development program driven from the CA team that it's like, look, it's the same 10 issues on drawings all the time. And so we should be teaching these things. And then they go back and they can measure whether or not those things are still showing up on drawings. So like it can be done. It takes, ironically, it takes effort and overhead to measure whether or not the overhead is being effective, which is the whole thing. Yes, but that is, you know, working in it is one of the worst examples of what we're talking about where if you do your job right in it, nobody even knows that it's happening. You know, like it's only when things go wrong is it visible that there's an IT department, you know, like it's right.

So the goal is to be invisible.

The goal is to be invisible.

Absolutely.

Yeah.

Well, and that was interesting. I was approached by a couple of people at the conference this year. Susan apparently pointed them to me. They were design practitioners, but they were, were enthusiasts of knowledge management and wanted to develop that more at their firm. And they had asked how to kind of make a knowledge management program manifest at a firm that hadn't yet embraced it as a practice yet or as a formal thing yet. And that's what I told them, is that the practices are, are going on. You have information systems, you probably have some sort of learning experience there, whether it's formalized or not. You know, if you look at Chris's periodic table of the elements of knowledge management, you probably have a bunch of those things that are going on just in the course of your business operations, calling them out, like identifying them and starting to codify them, as we're already doing knowledge management and we're doing it here and here and here and then trying to like draw connections between those things and demonstrate the value that they already bring and the value that they could bring if you amplified them or made stronger connections. That, that was my recommendation. So knowledge management, I think very much in order to succeed, shouldn't be invisible. That there's a great danger that it can be.

Yeah, that's right. I think. Well said. Another five star rating. I'm curious around. You guys are. In addition to being in the Beta for synthesis AI search. You're also in the Beta for synthesis Learning Management System, the lms. What is your kind of vision for what you think learning and development can become at snohada?

Great question. I mean, I think this is a perfect example of what I was just saying. We have. Learning goes on. It is very much informal here. We don't have, you know, we aren't one of those companies that has a snow head of university or anything like that. It's very much unstructured and informal. And I would like to change that because I think, you know, while there's value in that, I really want to be able to ensure that we're offering the highest quality of learning and development experience for, you know, for retention and ultimately, you know, knowledge transfer. Just the quality of our company going forward. And I think it's past due. And so I think the learning management system to me is an opportunity to try to codify and draw attention to the learning experiences we already have and can offer and then build on those. And like what that firm did with their CA, identifying that it's the same 10 problems all the time and we want to cut that down. I hear that all the time. And so I want to try to work with groups like RCA Group and our 3D design group and technology. There's so many opportunities just in the world of technology to reduce problems, IT issues, but also design delivery issues just to close knowledge gaps in the technology heavy industry that we work in just by offering more consistent learning opportunities around all of that. And so I see the platform as an opportunity to kind of build the thing because you can see what you're building, if that makes sense.

It does. I think when we're doing a beta this magnitude, Evan and listeners, we will do cohorts and get teams together like from. So we have Kate's in a cohort with seven other firms and we had a banger of a conversation on Tuesday. And what it really kind of exposed was much of the learning and development in at least that cohort. But I think it extrapolates out further is what we would call more knowledge sharing. So it's like somebody's presenting a design thing or they're very excited about this topic and they're going to share it. And it's all great. Like knowledge sharing is amazing, but it's not knowledge transfer. Right. And so it's like if people happen to catch it or they saw it, like it's kind of like just in case knowledge sharing versus like just in time, like no I'm going to be working in CA or a site visit or I've never worked on this project type. Like I've never managed projects before. Like there's all these learning opportunities where you can just be much more intentional about upskilling somebody. Right?

Right.

Doesn't say you shouldn't do knowledge sharing, but you need to do both. Right?

Right. And there's so many opportunities that the new platform offers in that regard. You know, it's. You could always share an hour long video of something that you recorded that was a live thing. That's. That's common. We could always do that. And there's something in it. And now that we have video transcription and the AI search on top of it, there's more in that. You know, taking an hour long recording and uploading it to the Internet, you get so much more value now than you did, you know, years ago. But it still means that if any one thing in that hour long recording goes out of date, and it always does, just like that booklet from 2015, you have to redo that entire recording. And now the learning management system is building something where you can package a bunch of small things in a meaningful way, in a sort of curated way. That one thing speaks to the next. But it also means that each of those individual pieces is all you need to replace if it goes out of date. And that's a much easier content collection to manage than a battery of hour long recordings of live patients. Right.

They started off as assets and then they become liabilities as they age and degrade.

Exactly.

I'm curious, going back to the culture and the amputation and augmentation around. On one hand there's all this great stuff you can do with video. On the other hand, we've talked a lot about how you want in person connection and people interacting with each other and kind of. What's your thinking about that kind of on demand video stuff plus having people interact and learn socially?

Yeah, I mean, that's something that I wrestle with because on the one hand I want to make sure that we don't lose that. And on the other hand, I'm not entirely sure it's possible to guard against that entirely. It's. The culture is changing around us, not just in. It's not just the culture inside Snohetta, we're not in a vacuum. The culture and values of everyone around us are changing at large. So I can't control all of those.

Variables about how meaning like more asynchronous or search first or preferring videos like Is that kind of what you're getting at? Yeah.

Yes. And even, you know, even the appetite for social interaction in generations coming up now is changing, if that makes sense. You know, it's like there are generational gaps in that regard that I can't guard against, but I can, I can do. We can do our best to try to establish that in this company at least, we, we want a culture that really prioritizes those interpersonal connections. And I think that when, honestly when I see people experience that, even if it wasn't their, their preference to begin with, they warm up to it. Because ultimately, like we are as humans, we are ultimately inclined to be connected with each other, but sometimes by being so disconnected, we lose the taste for it. You can build the taste back up again in my experience.

Interesting.

Anyway, to answer your question.

I like it. This is what I was saying in the intro. Very thoughtful. It's always philosophical when we get into it. Kate.

One of the Research council conversations we were having about the development of AI Search, I brought it up, Chris. When the AI search delivered its results, I wanted it to prioritize not just information results, but ultimately end with a. This is everything I found about this, but I think you should go talk to so and so and then call someone out in the firm, an expert that's been identified as an expert in a structured data field. The AI can pull that name and end with it. Or if the person who recorded the video, you know, they can call that. The AI can call that name out and you made that change. And I think that that's important, that it, it re emphasizes that that's one of our values, that we can deliver this information to you. But you will have a richer experience if you go follow up and talk to a colleague of yours who knows more about it.

Yeah. What's so interesting about that, Kate, is like, we. So we put out the first version of AI Search, which was just general knowledge based search, and then we have a feature in the product where people can rate searches and provide feedback and like. So we had like hundreds of those things coming in per week and like well over 50% of it after the first release was about people stuff like, I want to find the person who's got the skills, who can help me, blah, blah, blah. Like, so it's interesting that, like, even with all this AI stuff, which people are really worried is going to like hurt interpersonal communication and relationships, what people wanted to do with AI was connect with other people, which I am like, that was like heartening. I think A little bit about, like, where we're going as a species, like, that was like, it's not all over, you know.

Yeah, absolutely. I think it also means, you know, for instance, talking about the learning management system and the opportunity to sort of deliver the content differently because you're building it for a learning management system and you really want to be thoughtful about the quality of learning and ultimately the, you know, the experience that someone has at the end of it and what they have learned. It means that if we put our attention into doing the content that way for the learning management system, we can think about the live events differently.

Right.

Because if you're trying to get the live event to serve both purposes of.

Like information transfer and just like. Yeah, right, yeah.

Or just having the recording device on can change the dynamic of that whole entire thing. So if you remove the recording from that experience and you focus on a live interpersonal experience without all the devices, then you have a higher quality interpersonal experience and you can save the recording for the learning management system. They have two different purposes.

Me too.

I love that it is so important to say that. And I realize that, like we're on a recording right now saying this, so it's not lost on me. AI note takers and meetings automatically being set up to be recorded completely change meetings, completely change meetings. And I don't know what you do about that because people are very guarded with what they say. Whereas before it was like, no, we can actually have an exchange of ideas and not have that fear of it being recorded. Right. And so I just think it's super important to put that out there. I don't know what the answer is because, like the proliferation, like how many AI note takers do you need in a meeting? There are a lot. Right. And at the same time, it has completely changed the quality of meetings.

Yeah, it's a real dilemma. It's one of the things. We have not yet implemented any AI note taking on our ends, but we of course are often subjected to it, which is fine. I see the value in it myself, but I also see a lot of pitfalls in it. You know, classic. I'm of two minds on that. On the one hand, I've seen studies that show that organizations that are using AI to alleviate tedious tasks, including meeting minutes, as one of the large tedious tasks that is alluded to, that they actually are recording higher levels of sense of well being in their employees, in part because of the AI doing that lift of the tedious, repetitive tasks. And that's really interesting to Me and meeting minutes are onerous.

Yeah.

And the quality of meeting summaries that I've seen from these tools is quite good. And especially for the types of meetings that I'm in that perhaps don't go to bottom line liability in, you know, the delivery of an architecture project. They're great. They really save me a lot of time by having those meeting minutes. So I see a lot of value. But yes, absolutely. The impact that they have on the quality of the conversation is huge and very negative. And one of the funniest things I heard was at the KA Connect conference. We were sitting around the dinner table just having a chat and all of a sudden someone chimed in and they were like, oh my gosh, I have just had an experience that is completely new to me. A colleague just reported that they joined a meeting and the only other attendees in the room were meeting were AI note takers. They were the only human that showed up. Everyone else just sent their AI.

Oh my gosh.

It was inevitable that that happened at some point. I had this. I've started doing this thing over the last six months where, you know, I don't do as much sales as I used to, but I still do like 10%. And the thing I would put off for days and days and days is like typing up my sales notes and putting it into our CRM because the least valuable thing I can do with my time and it's just tedious, whatever. But now. So like another option which a lot of sales organs are doing is they just record every single sales call. Like that's just no questions about it. I'm not doing that because I feel like all the things we said about the dynamics, but the second I pop off the call, it takes me two minutes in ChatGPT audio mode to just read my notes, recount the discussion, go outside my notes, the things that people were feeling, what I took away from it, like, and I'm getting way richer things than I ever got before. And I don't just feel onerous, it's like I should kind of look forward to it. I can just dump all that context out, you know, and so it's a, it's a middle ground a little bit.

Absolutely.

Yeah.

No, that's a cool tip.

That's an interesting solution. And we have to talk about that with people. That's. That bridges the gap between having personal responsibility in it and using the AI tool to take away some of the onerous quality of it.

One thing I just want to just add on the learning and development piece Just I mentioned that thing before about me thinking there's like all of this change is going to happen in the five years more than the last 25 round L and D. And there's an emotion I've been picking up in our community that like people that have been teaching for a long time are just kind of tired of saying the same thing over and over and over and over and over again. And there's this opportunity, I think, if we do kind of what you articulated, Kate, really well, where it's a hybrid of some on demand, here are the fundamentals and then we have a non recorded live discussion about it. Like I've been asking these people, like, are you tired of the live part too? And you know, like, no, no, no, no, no. That's the fun part. That's when I get some random curveball question or there's some unique thing going on in their project and I'd love to chime in on that. I just don't want to do the one on one stuff anymore. Like I'm burned out on it, you know. And so there's something for the teacher too that's like potentially really great here too.

Oh, 100%. I mean, both of my parents were teachers, so I heard about it all the time. When teaching is a conversation and you're getting feedback from the class and it really is a conversation, then they get a lot of enjoyment and enrichment out of it and they learn and they grow as humans and teachers. And that's true however the teacher manifests. And when you have to repeat the same base level information over and over again and it is not a conversation, then it is dehumanizing. And you, you know, they're not paid enough to do that.

And I can't imagine it's your best performance either. By performance 19, you know.

No.

And so yeah, absolutely. The idea is you can get one like gold standard awesome 100, 105 take and then yes, that'll stand until it needs to be, you know, until the facts change. And then you need to. Yeah, Kate, this has been really, really awesome. I'm just my, my final question would kind of be like, what's next for you? As you look forward to the end of 25 into 26. What's exciting for you with KM AI learning, development? All the things.

I'm actually really excited. It's kind of ironic because sometimes still the AI naysayer around here, I'm actually really excited to get into the sort of AI development program that I have been talking about with our IT manager and with our design, technology and our leadership in general, I'm really excited to see what it brings. Kind of what we were just talking about, about the classroom discussion and what it brings to the table. Every time I talk with somebody about AI, I do learn about a different thing that they're doing with it that I didn't think to do myself. Like your description of the meeting notes just now. And so having these internal cohorts where we actually like get people together to talk about AI in a way that is, I don't know, more celebrated and less frustrating. Like right now, it's just being thrown at us. And I think that having these conversations in a thoughtful way will energize people and actually like bring a lot of creative ideas to the table and make people feel more empowered around the AI revolution rather than overrun by it. And so I'm really excited about getting into that and seeing how that transforms people's feelings about it, including my own.

What I'm visualizing while you were telling that story, Kate, is the famous hype cycle diagram, right. Where like hype cycle ramps and there's a trough of disillusionment and then there's a slope of enlightenment. And it feels like maybe we're getting it kind of the end of that first wave. Like you could definitely feel there's some backlash, you know, happening and. But there is value in this technology. But now people can start building and doing things in a way that's consistent with their values. You know, like no non planned or forced amputations, you know, all the things we talked about.

Yes.

And so there's like, it's just less of a over caffeinated driven, you know, like we got to do all this stuff like right away and now we can just start like solving problems and building things, right?

Yes, exactly. So I'm excited about that and I'm excited about the learning opportunities that we have in the future and seeing how that will positively impact my colleagues around here. I'm very excited about getting some learning programs together in the LMS and seeing that enrichment happens.

I would love to just kind of wrap up by saying, I mean, it's amazing to hear what you guys are working on and how you are kind of driving this idea. And obviously there's a lot of collaboration going on here, but this idea of going back to the values and kind of pairing that with where we got to close to the end of the conversation with this idea of the 101 stuff, the rote stuff that people have said 50 times and don't need to say it a 51st time. Using technology to like codify that information so that when you come together for that valuable human engagement on a project can be such a more rich experience. So it's like you set the baseline. Okay, everybody, here's your homework. You do the homework before class and then you show up at class and we have an amazing interaction with each other. And to me, that just seems like a really neat flywheel because you're going to get a higher baseline out of those interactions that can then be fed back into the system so that you can continually evolve this forward in a really cool way that really codifies the culture of the company so that those interactions are just like the cherished part of it. And you really. That then expresses itself in the projects and with the interactions with clients and all of those things, I could really see that being a really amazing feedback mechanism to really build your culture around. So kudos to you and your team.

Thank you. That's exactly where we want to go.

And it is. It's back to the way you talked about AI, but we're talking about it from a learning perspective. It's like, it's not like we're not going to use technology, but we're also not going to lose sight of our values. So, like, how do we. How do we blend them?

Absolutely. We want to make sure that we are. There has been a sort of a fracture in the conversation because of the. The knowledge gaps built created by these technologies.

We're going to have a healing moment for technology and AI and.

Exactly. If we. If we can reduce those knowledge gaps, then we can have richer conversations about design and process and all the things that actually energize us.

Amazing. Kate, thank you so much for your time and thank you sharing with us. We really, really loved it. I can tell.

Yeah. Thank you both for this conversation. I know it went a little longer than we've. We probably planned for, but there are so many great things in the conversation that came out of chasing those digressions. And I really feel like there's so much value in that. So thank you so much. We'll put links to everything that we talked about here in the show. Notes for the episode. And for those of you who want to know more, definitely follow these two. We'll put links to them on LinkedIn and all of the websites and valuable resources that we talked about. Thanks again.

It was great conversation. Thank you so much.