How AEC Firms Use AI Search To Find Internal Expertise

What is important, and I think, especially I've learned from working in AI, is we have a really hard time predicting what's going to be important and how long things are going to take. I've been working in software for a couple decades now and I have a pretty good intuition. Like we say, hey, we're going to build this thing. I can sit with the engineering team and we can basically say plus or minus this many months or this many weeks. We have a sense of how to build that stuff with AI. It's wild. You just don't know. And in both directions, we're doing stuff in the product today with AI search that we thought was going to be a couple years out with us having to build a lot more infrastructure. On the other hand, there's other stuff that's been a lot slower to get right, so it's just really hard to predict. But the other part of that has been we had a lot of hypotheses. Like we got a 1.0 out and we had a lot of guesses on what 1.1 and 1.2 would be, but we didn't commit to any of it because we wanted to get feedback from real users and understand a what was the most broken but what was the most compelling opportunity for us to work? And nowhere really on the bingo card, I think, did we think that employee search was gonna be the next thing we built. We thought there was a lot of other stuff we're gonna have to build first. But because people can rate their searches in the platform and put feedback, we see all the feedback when people rate how good their AI searches are. And it just became like 45, 50% of our feedback was about people looking for people, which I think is also really interesting. Based on skills. Based on like, what? What are they? What are they searching for? Skills licenses, who do I go to? A lot of it was like, I have a question, especially if you're in a multi office, who's the expert? Who's the expert? Or who's the person who signs off if I have to get a certificate of insurance, Pedestrian stuff like that. There are hundreds of these questions that come up every day that people need to find out who in the company knows the thing or who's worked on this kind of project before, all this kind of stuff. And what I feel like is really kind of warming or comforting about that is this idea that AI is going to reduce the need for people. If you think about it, we took a swing at what we thought the most important thing to do. Was is general knowledge based search. And the community told us, actually we want it to be able to connect with each other. That's the next most valuable thing that this product can do for us, is help us connect with our peers. And then the thing after that is about projects. Obviously I want to know how many projects we've done, this square footage over the last five years, that kind of thing. But also who worked on that project or who are the people that have worked on projects in the city. That's what people really want to use. We're seeing emerge organically what people really want to use this technology for. I feel like our role is to facilitate the conversation, build the tools and just be really good listeners.