141: ‘AI is Not Your Strategy’, with Mehdi Nourbakhsh and Scott Thompson

141: ‘AI is Not Your Strategy’, with Mehdi Nourbakhsh, PhD and Scott Thompson
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[00:00:00] Hi, everyone. Welcome to the TRXL podcast. I'm Evan Troxel. Some housekeeping. Before we get into this episode, I recently had the privilege of attending Autodesk University in Las Vegas, Nevada, and it's always great to meet members of the AEC community in person. Especially TRXL podcast guests.
And speaking of them, there were a couple dozen at AU this year. And I even got to meet up with one of the guests from today's episode, Scott Thompson. I've recently put up a couple of posts on the website, talking about my experience there this year. And one of those posts includes a bunch of selfies that I took with past guests of the show. I've also recorded an episode of my Archispeak podcast, where I talked more in depth about my experience.
So if you want to know more about what I find valuable about attending AU or are interested to hear what I think about the conference in general, please go check all of those things out. I'll put links to all of [00:01:00] them in the show notes for this episode. that's a great reminder for me to tell you about the show notes.
I actually put a lot into them. And they include things like the links mentioned during the episode. You can find them for every episode at TRXL.co and I would love it. If you'd go there and click on one of the subscribe buttons to get them emailed to you each time a new episode comes out. As a bonus, you'll also get my AEC tech newsletter that comes out a few times a month and really fills in the gaps about all of the things that are piquing my interest as I track the co-evolution of AEC and technology. Okay. In this episode, I welcome. Mehdi Nourbakhsh, PhD and Scott Thompson. Mehdi is an author, speaker and CEO of YegaTech, a technology consulting company in AEC industry. With a decade of experience in research and development of innovative AI solutions in the AEC and [00:02:00] manufacturing industry at YegaTech, Autodesk and GeorgiaTech, Mehdi brings a unique perspective to this space. He has developed several AI solutions that are used by tens of thousands of AEC and manufacturing professionals.
Every day, he's filed seven us patents on the use of artificial intelligence in AEC and manufacturing industries. And served as a member of the technical advisory committee of the center of integrated facility engineering at Stanford University. In his new book written for AEC innovators and professionals called Augment It: how architecture, engineering, and construction leaders leverage data and artificial intelligence to build a sustainable future, Mehdi explains how AEC leaders can invent, innovate and augment their capabilities using AI. We're also joined today by Scott Thompson. Scott has over 40 years of experience in the technology space in a variety of sectors, but once falling into the AEC space [00:03:00] over 25 years ago has dedicated his passion for automation and continuous improvement to those that help to develop our built environment. He is the vice president of technology for the SSOE group and internationally ranked architecture and engineering firm with over 1000 employees. I have them both on today to talk about AI, because there are many people in AEC firms talking about AI, but today's conversation is about how Scott and Mehdi are working together to actually implement it.
Scott's firm SSOE has tapped Mehdi and and YegaTech to bring their incredible expertise to the table, to build a strategy around using tools like AI, among others, to create a differentiated, competitive advantage. And perhaps most importantly, we discuss the focus on people in the implementation of AI. In the AEC industry. We highlight the need to address people- related challenges and create a culture of innovation. Be sure [00:04:00] to listen for Mehdi's free offer to TRXL podcast listeners in the episode. There's a link in the show notes as well. So are you ready? Let's go.
Evan Troxel: Mehdi and Scott, thanks for joining me today. This is going to be a great conversation. Mehdi, can you start us off with a definition of of AI? Here's why I ask: there are a lot of ways people interpret the term AI when they hear it. So I think it's important to set a baseline for the audience to understand exactly where the rest of the conversation is going, beginning with your definition.
Mehdi Nourbakhsh: Yes, of course. Thanks for having us. AI is a branch of science in which scientists design computer systems that mimic human intelligence. To help you visualize it, You can think of AI as a tree with several roots and branches. The roots of this AI tree are philosophy, logic, and mathematics, computation, cognitive science, biology, neuroscience, and evolution.
The branches of this tree are subfields [00:05:00] of ai, such as computer vision, machine learning, speech recognition and synthesis, search and optimization, knowledge, representation, and reasoning, and robotics.
Oh, one more thing before we begin. Mehdi and I collaborated ahead of time on this episode to create what you just heard. And you might be surprised to learn that those were AI generated voices. For both of us, we both wrote our parts. Then I trained the AI with recordings of this conversation that you're about to hear today with Mehdi's permission of course. And then let it generate the output. And after tweaking some settings and picking what we thought were the best versions we settled on the ones you just heard. We actually tried it with a couple of different voice generators, and this was by far the best one. All tools are not created equal.
So take a moment and rewind. Go back for a second. Listen, I think you'll agree how interesting it is to hear that it added some [00:06:00] ums and breaths between phrases all on its own. It's incredible. No, I'm not worried about deep fakes at all. Maybe I am. Anyway, this was a possibly terrifying experiment.
And so with that, I hope you enjoy this conversation as much as I did. So without further ado, I bring you Mehdi Nourbakhsh and Scott Thompson.
Evan Troxel: Mehdi Scott, Welcome to the TRXL Podcast. Great to have you here.
Scott Thompson: Thanks for inviting
us.
Mehdi Nourbakhsh: for having us.
Evan Troxel: And so obviously the topic is, is ai. And so we've already heard Mehdi your definition of ai, the, the AI version of you saying what the definition of AI is. And, and this is all laid out in your book. I'm gonna hold it up here for the people watching on YouTube. It's called Augment It. And many, this is a fantastic book because it really just lays a foundation for us all to be [00:07:00] on the same wavelength as far as what we're talking about, right?
And, and, and then you go deeper. And so I think that's important, and that's why we, we did this little exercise up front, was to lay out the definition of what we're talking about because it is so easy to interpret what AI could mean. And we hear other terms interchangeably with ai. We, we hear ML we hear all kinds of stuff, and, and so your book really does a great job at breaking down.
And you use the analogy of a tree with branches and roots and the different pieces that make up the whole thing of AI but before we get to the book, and before we get to what you and Scott have done together, I would love a little bit of a background and Mehdi, let's start with you, uh, of why you do what you do and how you got here.
Mehdi Nourbakhsh: Yeah. Um, so I'm, I'm a tructure. I used to be a structural engineer and, uh, moved to construction. You know, started, uh, building [00:08:00] what I used to design, and, uh, played there, did my PhD in architecture and design computing. And this is where I got Introduced to the beautiful world of AI and
found myself, uh, you know, working at, uh, Autodesk, uh, was part of a team that, um, helped Autodesk to introduce AI to Autodesk.
And, um, I worked during my, uh, work at Autodesk, I worked with a lot of different architecture engineering construction companies, and I started seeing a pattern, you know, why some of the AI projects are successful, why some of 'em are not. And this is where, you know, I, I started putting them together in a framework.
And this was the genesis of my book, um, augmented, uh, my goal really was to help the industry don't make The same mistakes over and over, and creating a framework that can help companies to create their own AI strategies. Finding AI opportunities that gives them market [00:09:00] differentiation and start, you know, looking and implementing AI and be more proactive, uh, than reactive, uh, about AI and new technologies that that comes in. And for me, when I was writing my book, I interviewed like more than 50 people and I asked them, what is your biggest fear for this industry? And a pattern that emerged was the slow pace of change in the industry.
There are lots of new solutions and tools and things are coming in, but our industry is, you know, very you know, some parts of the industry is very fixated the way that we used to work and breaking that is really hard for people. So at Jaga Tech, my company, we are trying to help architecture, engineering, construction companies to look broader, to find areas of opportunities for themselves and help them to create a [00:10:00] strategy around ai, create a a plan, action plan for AI and help the people also in the organization to come along.
Because if we can't change people's mindset, nothing is gonna change in our industry.
Evan Troxel: I just want to point out too that I had a conversation with Sam, your partner at YegaTech yesterday, and so I'll put a link to another podcast that I'm participating in called Confluence, where Randall and I interviewed her and the, the topic there was around the governance of AI and ethics and copyright and, and it was very much the other part of this very necessary conversation that all is intertwined as companies are dealing with adoption.
Right? Uh, so definitely check that out For, for the listeners of this show as well. Scott, can you give us an intro to
yourself, your background and, and where you're coming from?
Scott Thompson: Absolutely. You know, I, I've started digging [00:11:00] around with computers, not because I was passionate about computers in, in about 78. It was just, it was a job that I could work at night while I was going to school. And, you know, I found that, uh, I'd probably make more money doing something with computer science than sociology, which was my passion and my first, uh, major. And, uh, I just kind of, I, I, I loved it because of the pace of change, because this industry does change all the time. And I, and I love to be, uh, you know, to be put in front of, of, of things that are always moving. Um, and, you know, long story short, you know, that was doing mainframe computers, et cetera, uh, I ended up working in, uh, field of Education.
In fact, got a master's in educational technology, which does kind of work its way into computer science. And why I love this work, because when you look at education or education, technology, it's all about identifying. I. A performance problem or a learning problem, there's something that needs to be done, and it's not always gonna be done, uh, through education.
It could be a process, it could be environment, and, and you [00:12:00] break things down. And so it's like, that really resonated with me, which got into algorithms and doing, uh, coding, et cetera. Well, you know, I, I ended up with an engineering firm, uh, many years ago. Moved up to Portland, Oregon and, and, uh, love it up here and have stayed in the engineering field, uh, mostly industrial engineering, working with engineers and architects in really helping them automate and become more efficient in utilizing tools for the built environment. And as Mehdi said, it is, it's a challenge. It's a mindset challenge more than anything else. Sure, there's a technical challenge, but we all know that technology will change. It's that, it's the, the adoption and it's the people side of things that I find, uh, maybe this goes back to the sociology. The most challenging part of this is getting folks to get excited by the opportunities and not be fearful of 'em. So,
I think it was about a year or so ago, um, I was coming back from business trip and I was listening to a podcast. I, I don't even know what it was, but, uh, Mehdi [00:13:00] was being interviewed and it's like, wow, this, because at that time there's a lot of stuff coming out. You know, we're just getting the, the, the sig the, the, the signal to noise ratio is been, you know, absolutely horrible. But it's like, wow, for the first time, here's someone that's in my industry that understands this huge world, but in this space. And he spoke to it from, from perspective, like who knew something about the industry. And I had never heard anything like that. Um, I reached out to him and, and, uh, found out he had a book.
I read the book and then I said, boy, you know what? He, he hits the nail on the head here, and it really is a people problem. Yes, there's all sorts of things you can do and you can build it, but if you don't handle this people side of things, um, it's like any other technology, you're not gonna get the value out of it. So, you know, fast forward a little bit. We, uh, you know, I, I set up a meeting with him and our CEO and, uh, our COO, uh, down at his offices in, uh, San [00:14:00] Francisco probably about six, seven months ago. Uh, introduced them, uh, to, uh, Sam and to Mehdi and, uh, we decided we're having an annual business planning. Um, let's bring Mehdi in.
'cause we knew, I knew that we wanted to do something with ai. Just wasn't sure what it was. Recognized that I could have all sorts of good ideas. And so thought, let's get some common language amongst the leadership
and get folks to understand what it is we're talking about before we start talking about it. And, um, you know, what we discovered, um, was that was a really critical part of this. It's a really
critical piece, is getting that language and getting people to start not being fearful of it. And we can talk more about how that went because it was a, it was a phenomenal day. Um, and it was, there's a methodology that, uh, ya tech uses and, and I know they've repeated it over and over again and I've talked with other customers of, of ya Tech. It, it works [00:15:00] in getting to a point where now the problem is not, I'm afraid of ai, I don't wanna use ai. Now it's like, I want AI and I need ai so two sides of a problem. And I'm not sure which one I like more because now are so high. So, uh, we've been, we've been in, uh, involved in a relationship for, you know, a good year or so, one way or the other.
And, um, it is been a game changer for us. Um, and I, I just love being able to see how we can make incremental and, uh, continuous improvement in an industry which is slow to move.
Evan Troxel: So there's some themes here that, that mimic what I saw at the workshop that I participated in, that you led Mehdi at the Confluence conference, right? And you took a poll at the beginning and you took a poll at the end. And, and maybe you can repeat the question here that you asked and the sentiment that you heard and the shift that occurred from beginning to end.
And then we'll figure out what happened in the middle of, of how we got from here to there.[00:16:00]
Mehdi Nourbakhsh: Yeah. So I, I typically ask this question at the beginning of our workshops that, Hey, when you think about ai, what are the emotions that comes to your mind? And there's a list of emotions that, uh, mostly people use and we have a word cloud. And, uh, and I be asked the same question at the end of the workshop. And, and typically, you know, at the beginning, um, depending on the audience, there are, there's a mix of excitement. And also, uh, on the other side of it is fear and, you know, curious. And so all, all different sorts of emotions. And when we go to the end of the workshop, this is typically different. Um, and really the, the idea and the, the, the message here is that there there are two things. One is, um, by learning about something, [00:17:00] uh, and by acting on that, we can change our emotion. And so the learning is a critical part. And the second piece of it is that Um, a lot of people in the organization are fearful about AI and now that we create that base level for the executives, how we can help other people in the company, uh, to do that. And lastly, it's, it's about, uh, being able to, uh, move people from a fearful estate into excitement estate so that we can have a better conversation about what we can do and how we can, what are the new opportunities that we can build for the, for the company? Uh.
Evan Troxel: Yeah, I, I feel like this is a great strategy and AI just happens to be the technology we were talking about, but you could put . Insert any technology into there, and this is a great strategy to get the gears turning right, because if, if everybody's coming at this from a different angle, which is [00:18:00] traditionally what's happening, right?
Everybody has their own newsfeed online. That's it's algorithmically fit, fed, just to you, you're the only one who sees that timeline. Well, that that's how we start to derive this worldview that we have of whatever the, the subject matter is, right? AI is no different and other technologies are no different, whether it's BIM or Auctioneering, or generative design or any of the topics that we cover on this podcast.
It's a great way to build a foundation like we were talking about earlier, of getting everybody on the same page so that you can then have a real discussion about it. And you don't continually have people pulling in different directions, which is what we see time and time again in all sizes of firms, right?
You've got, you've got people who like live and breathe this stuff and then you have other people who won't touch it with a 10 foot pole and everything in between, right? So I feel like it was, it was really successful in that through the learning process [00:19:00] about the branches and the tree and the roots and, and the different pieces of it, and really starting to educate people around what these subjects are that are, that make up the field of ai.
It gave everybody way more comfort that their wildest dreams or their are the wild, the biggest problems aren't gonna occur. It's gonna be, it's gonna be somewhere in the middle. And so, Scott, I assume that you, you, you already alluded to the fact that this happened with your leadership, right?
Scott Thompson: Yeah. And you know, you make, you make a really good point, Evan, you know, you could not only any technology, you know, I, I think about, you know, some of the challenges right now that, that I'm having in trying to understand, you know, what's going on in the Middle East and I'm doing a deep dive, it's education, right?
If you can
get enough information and move away from that narrow casting, which, you know, it's interesting as it comes back to the whole idea of large language models and what's gonna happen there if they continue to feed themselves with their own,
you know, I think of like how chewing its own cud on, you know,
where, where's the growth there. Um, [00:20:00] but if you can get, if you can get, um, some education, you're gonna be able to have some good conversations without education. You can't, it's not just the, the language, the taxonomy. Um, it's, it's being able to have enough knowledge where you can now engage in conversations and, and
that the one thing that I thought was really great besides the outcome is in the workshop itself. Um, it's, it's, it is not presented as like, Hey, this is going to solve all your problems. I mean, it's, it is very clear. It's like you don't walk outta it saying it is gonna take care of everything. There's a, there's a real element of like, okay, you know, it's a technology, it's got flaws. Um, so we were able to talk about that as well. So it wasn't a sell job on ai. It was, okay, this is what AI is. Um, here's the, here's the opportunities, here's the risks, here's the challenges. Um, here's some areas [00:21:00] where it might be good. Here's some areas where it would be horrible. Um, so there was enough information where it could then be applied in our environment about risk. And, you know, talk a little bit about SAM and governance and, you know, this is a big deal. Our company, I, I, one of the few folks that I was at a conference not that long ago, and I was EFCG and, you know, everyone was running their chat, GPT, and I asked like, well, how many of you have any kind of policies around this? And none of 'em did. It's like,
man, there's a lot of risk there. So there's, it is just having
enough knowledge to be able to move forward with a strategy and knowing it's not gonna be perfect, but you've got a path that you can, you can start moving down.
Evan Troxel: It, it, it does come across Mehdi that you're really excited about AI and the potential of ai. And so maybe let's just, let's just go there first because I feel like, uh, there's a lot of people in this industry who are like this. Let's stand on the sidelines and watch, right? Let's see how this plays [00:22:00] out before we even think about wading in or adopting this, this kind of stuff.
So. Maybe just give some ideas upfront, because you have such a, a big view of, of the potential of what AI can do in AEC domain specific. Can you just give us some, you know, high level overview of, of what you think is possible with
Mehdi Nourbakhsh: Yeah. Um, absolutely. So I, I'm really excited about innovation. Um, so that's what really, that's my big
word. And, um, AI happen to be a tool, uh, or automation, you know, could be a tool that can, can serve that. Um, and when you look at the, the kind of the trends in the market in the, um, you know, past. Five, 10 years, we moved from the era of small, shallow, shallow AI models into the era of deep models.
And that was the, you know, invention of, uh, deep learning back in 20 10, 12. [00:23:00] And then from 2020 to now is the era of foundational models. And these are the models that could be used as a foundation to develop a lot of different tools. Uh, on top of, you know, in fact, uh, OpenAI open its own app store now. Um,
so this could be used as a foundation that can help us do a lot of things.
So if you look at the capabilities of AI models, their capabilities have significantly improved over time. And at the same time, the cost of experimentation and working with this AI system has significantly reduced. So we kind of see a curve that is going up in terms of capability and also, uh, another curve that is the cost of implementation that is coming down. And this brings a new opportunity for our industry. And now, so this is more on the solution space. On the problem space, we have a lot of problems that is still unsolved in, in our industry. [00:24:00]
Um, when we work with companies, we don't necessarily, we don't tell them, Hey, uh, focus on like common industry problems.
We work with them to find the areas and opportunities that gives them is unique to them. This is opportunity coming from your annual business planning that if we could solve, can help you with X, Y, and Z. So this is a unique opportunity to you. So we, we create a portfolio of those opportunities and then we look into, okay, if we want to solve this opportunity, what is the really, the core problem here?
What is the maybe root cause of, of this problem? And how automation or AI could be helpful here to address this, you know, challenge that you have or this build this unique solution that you have. So combining like the, where we are in the, in the technology space, which you know is technology is [00:25:00] cheaper and you know, a lot more, uh, capable with some of the unique problems and challenges that these companies have, this could give them an area, a good starting point. To, you know, invest in and to bring those capabilities in their companies. And the goal is not to do it once and you're done. You've got to
harvest these opportunities with your people over time. Every quarter, every six months, you do this again and again, and eventually you're gonna improve your companies and bring your people along and, you know, help this industry to move forward.
Evan Troxel: It's interesting to think about the order that you presented that in, which is you identify the opportunities first, and then you figure out the tool. It's not like you're saying, we're gonna use AI no matter what. What are the opportunities? Right? You're, you're actually going the other way around. And I think that's really important because AI is a tool and it could be one tool in a [00:26:00] stack of tools to accomplish those goals.
And I also like how you're differentiating it. To specificity for the business rather than, because this is a disruptive technology. It is democratized access to the tool. Everybody has access to chat, GPT, everybody has access to a number of tools. Mid journey. They could be image generation, they could be text generation, they could be built into Oath, office 365, as we've seen, everybody's got that, right?
And it's just like, it's like the iPhone. The richest person in the world has the same iPhone that you do, right? And so that's not a differentiator anymore, just having the device or having access to this technology. It's how you use it, right? And so if you can really be specific about the opportunities that you need to solve for in your business, AI may be one of the most incredible tools that we've ever seen to help solve that problem.
Is that what happened between you two, [00:27:00] Scott and Mehdi? Is, is, is that how it went? And I'm, I'm curious because we have a real world case study right here,
Scott Thompson: I actually ask me a question I'll ask at the end of this. Um, so, you know, I mentioned earlier about, um, the annual business plan where we had our, our leaders and we, you know, all of our, uh, business units pr present their plans for the next year. Um, well prior to that, you know, started working with Mehdi, uh, shared with him our strategic, uh, plan.
Um. Five-year plan for the, for the company. Uh, he looked at that, um, and then as these business plans will be being developed for this, for the next, uh, year, uh, gave him access to that. And then simultaneous, we, we did a survey of, of all the people in all, everyone in our company about, we're about 1200, then we've grown a little bit since then. And we consciously did not ask, we didn't use the word ai. We just said, Hey, what are some areas? And there was a series of questions, but what are some areas where you think, um, technology [00:28:00] and automation would, uh, make a significant difference in your, uh, daily experience?
Evan Troxel: Mm-Hmm.
Scott Thompson: But we did it in such a way, but we asked enough specific questions that we ended up with a, just a massive amount of Okay.
And didn't mention anything about to AI presented that to, uh, to Mitty. So now he's got the, uh, enterprise strategy. He's got a list of basically voice of the customer, the people that are out there, whether they're uh, uh, uh, designers, drafters, engineers, managers, whatever. Right? Things that just like, man, you know what?
I shouldn't be doing this. This is just as mundane work. Um,
and it really would make a difference. So with that, um, at this business, uh, workshop, um, we put together I think four or five different scenarios based on that. And we had randomly people sitting at tables, uh, and they each had [00:29:00] one of these scenarios. And after all of this baseline understanding of what is this, then we had basically an exercise where each table had to come up with a poster of, here's the problem, you've learned a lot about ai, how would AI potentially solve this problem? And it was fascinating 'cause we ended up with some, uh, pretty interesting ideas.
There's no way we ever would've gotten them, mostly because you don't get people together and do that kind of like, uh, brainstorming very often. Um, and we actually, uh, many might feel different, but we actually thought, okay, well this is gonna be the foundation of the work that we're doing. We're doing well.
There were BHAGs. I mean, obviously, you know, everyone was dreaming really big and they're just like, you know, as soon as we saw them, it's like, no, we're not, we might be able to do some of these things, et cetera. But coincidentally, after this workshop was over, I mean, I was inundated as was others, as were others with. Well, wait, I want to talk about this. We didn't get a chance to talk about [00:30:00] this problem and this problem. So we did a bit of a pivot and this was not part of the original plan. And I don't know if me's done this with any of his other, uh, customers where we had basically what I'll call it an eight week sprint. Um, where we took three to four people from each of our business units and each of our corporate departments and did a, a pretty, um, guided step through of okay, for your business unit, for your department, let's do the same thing. Come up with three problems that you'd like to solve. Okay? And so ya tech help these individuals.
We had a facilitator that, uh, That Mehdi and, and, uh, Sam trained so they could kind of help lead people through this. But Mehdi and, and ya tech were, were there to kind of walk through this with certain deliverables. Um, so at the end of this, they had basically three ideas that had been, you know, we've identified what the problem is and here's where AI might fit into it.
Some really interesting ideas, things that I never would've thought of, but they
were very clearly coming [00:31:00] from our customers. And so where we are right now is we've kind of selected the, the best of those and we're starting to evaluate a, you know, we've actually put 'em in front of our, our leadership to look at how real, how, how real of a business problem is this. Um, and now we're going down the path of, okay, is this something that AI really would solve? Um, because these were not AI specialists, you know, they're engineers and
IT folks and, um, administrative assistants. Um. But we're taking those, and now we're starting to do some, some basically rating of those of okay.
Capability, possibility with the data, et cetera. And, you know, Mehdi and I had a conversation this morning. Okay. A lot of these things, they're definitely problems. There's no question about it. Do you need to add for it? Maybe, maybe for that last 15% if it's
worth it. But what we've
gained is enough knowledge about the problems and how AI could potentially do it.
I'll go back and say one more thing. This, this whole idea of [00:32:00] focusing on a specific problem for the industry, um, or for our company, I think that really is critical because
Evan Troxel: hmm.
Scott Thompson: even, I mean, from an industry level, there's going to be solutions that are out there that are, I mean, they're being developed right now. Um, you know, some of the ideas that were, were brought up, they weren't even AEC industry specific, you know, it was just like, okay, well we, because it might be from a, a corporate department. Great. You know, we're not gonna build that thing. There's there's other people that can do that. Um, but even in our own industry, I think of like one of 'em that, um, mean, we've talked about clash detection.
You know, if everyone could use clash detection, it would be great. But clash detection is a horrible, horrible, um, set of tools right now. I mean, people don't use it because you get too many false positives. Right. And, you know, I think that, uh, Mehdi is talking the book and you hear it in other places.
It's a classic cat, dog, cat, dog. You know, is it a clash? Is it not a clash? Is it a clash? Is it not a clash? Well, if there's ever any one area [00:33:00] where you could get some value, it's like, man, if you had a learning tool that knew what a clash was because these things don't learn, then people would use it and quality would be better. And then you'd have far less RFIs. Uh, your customers would be happier as well. But then you get to this point of going, okay, well, we're not the only ones that are suffering from this problem.
Evan Troxel: Right.
Scott Thompson: someone's gotta be working on that. So is it worth our time and investment to look at building a clash detection AI tool? So now we're at this point of like, and it's a really interesting point of trying to forecast where the industry is going. So we're not necessarily inventing something that Microsoft with billions of dollars or Autodesk with, you know, millions of dollars
is,
Evan Troxel: And and sitting where? Sitting where I sit, I've seen that exact thing happen where . , all of the firms have identified this problem and they've all gone about solving it their own way. And they're all duplicating the effort and they come together at an annual meeting [00:34:00] and they're like, everybody, is anybody else having this problem?
Because they think they're the only ones and everybody has the same problem. It's like, oh, well I, I designed this bespoke thing to accomplish that task. And oh, guess what everybody else did too. And so it's also, as an industry, AEC industry, it would be fantastic if there was a way that we could communicate with everybody else out there to, to throw these ideas out, to say like, what's going on here and who's tackling this and who isn't?
And, and, and is this just something that we should just buy rather than develop? Right. And, and that level of communication is lacking as well.
Scott Thompson: And, and you know what? If I, if I can, it's, that is a real challenge because there's, again, you, you talk about that, uh, that, uh, signal to noise ratio, there's, there's no way you can keep up with everything. You know,
there's just no way. And, you know, another example that's like,
Hey, we're not gonna do this.
And now we're evaluating a, a commercial product is, you know, boy, if you could have a large language model for codes, right? So
you can start out.
Evan Troxel: to keep track of all that. Yeah.
Scott Thompson: it was like, okay, wouldn't it be great? Well, we're not [00:35:00] gonna build it. Someone's gonna build it and we're going to, you know, subscribe to it. So we're about ready to start an evaluation of Uptime's code, uh, co-pilot, um, because
Evan Troxel: of codes.
Scott Thompson: out there, you know,
so, but it's hard, hard to forecast what's gonna be out there, and you don't wanna be too tentative. And if you can get enough gain in a short period of time before product. You know, is, is, is, is out there,
then maybe it's worth it to do it yourself.
Evan Troxel: Mehdi, you have anything to add to, to what Scott was
Mehdi Nourbakhsh: Yeah, it is. It, you know, it's just wanna echo what, what Scott said is really when it comes to the end, like when you have a portfolio of opportunities, that's like a decision time, uh, what are the things that you need to invest in so that it can accelerate your business strategy? Or what are the things that, uh, you got to kind of hold off? Um, you know, Vince, the, the CEO of uh, SSOE. Uh, has a, you know, uh, code that I really, really like, which is like, AI is not your strategy. [00:36:00] AI is the accelerator of your business' strategy. And, you know, thinking about what are, how some of these opportunities might give you that, you know, differentiation in the market, um, is the key.
So when it comes to it, um, you've got to think about where the industry is going, where the all the tech trends are moving to, and, uh, what are the things that is unique to you and can help you differentiate yourself in the market.
Evan Troxel: How important is it to start small? With this, so I, I can only imagine, Scott, like the, the number of projects that came out, the opportunities and the variation of scale of those projects, right? There's like the moonshot projects, but there's also like the really small automation stuff or the AI based stuff and or any other tool I guess, but, but Mehdi when it comes to small wins to build momentum and also to start plugging in issues with [00:37:00] governance and risk and all of those things along the way.
I. I mean, I guess I'm kind of painting a picture here. I want you to actually paint the picture of, of how important is it to start small or is it, is it like all in, like, give us an idea of, of the types of recommendations that you make. Firms who, because we have to recognize that adoption is hard. We have to build traction over time so that we can get to scale.
Uh, and, and I think this will lead us into a, a, an interesting area of conversation.
Mehdi Nourbakhsh: Yeah, absolutely. You know, in, in the book I talk about, uh, like in the, the ponder phase of the augmented, uh, framework is all about how to find these, you know, how to, uh, form your AI task force, how to find these opportunities based on your business strategy. And, uh, you know, towards the end of it, it talks about how you can prioritize, uh, some of these opportunities based on their business viability or business
importance and technical difficulty. [00:38:00] Um, so. You know, typically when you look at this, the opportunities through that lens, you know, if you plot them in a graph, uh, you, this graph will have four quadrants. And two of the quadrants that are really interesting are the one that has the highest business importance and the lowest technical difficulty.
And we call them quick wins. Uh, so they're super important for the business, but they're easier to do. So we typically look into these areas for the first AI project that you, you want to tackle. And the next quadrant that is very important is, uh, you know, the ones that are, have the highest business importance and also they're more difficult to do.
And we call them a strategic, uh, business pro strategic AI opportunities. And I. You know, if companies wants to take one or two [00:39:00] projects, we typically recommend looking into the quick wins. But if they want to have tackle a bigger project, we say, okay, which of these ones in the strategic quadrants, uh, might be the right fit for, for them? So, um, if they have a bigger budget, you know, one or two quick wins, and one is strategic projects, but if they have a smaller budget, uh, maybe one, uh, or two quick wins that would give them a good starting point.
Scott Thompson: Yeah, if, if, if, if I can. And, and I'm, I'm, I'm really fortunate to work for a CEO that, um, recognizes the potential of this. So a lot of it has has to do with budget, which is tied to, um, your competence in, um, this, this new environment. And so, uh, Vince, our CEO. Um, you know, he is pretty bullish on this. Uh, he's been in the industry for a while, but he sees this as a pretty transformational time, uh, for the industry and some real really good opportunities.
And so he, the approach [00:40:00] that we're taking is, know, we wanna have maybe three or four projects this next year. And his a portfolio, and he's, he's flat out said, if every one of these things is successful, then you failed. Okay? The idea is, listen, you gotta go big. You know, sometimes you just have to swing for the fence and, and if, if you're gonna learn stuff along the way.
So don't go in there with this expectation that every dollar you are investing is going to result in a dollar of savings, real savings with the solution. Because what you're building is you're building an environment which you're going to continue to develop. And that's one of the things that, uh, y tech has, has really emphasized like as, as, as, as many said, it's not a one-shot deal. We're, we're creating a culture. Which really, it's almost fast forwarding because we can't even get to a point where we're in this data culture yet. And now we're talking about let's put an AI culture on top of it. And, you know, maybe we'll talk about this later, but you know, [00:41:00] a good a 60, 70, maybe even 80% of an, any ai AI solution's all about the data. And, and, and that's gonna be the biggest challenge here is if you're gonna have the data standardized, which you have to have, um, forget about the technology, you have to have processes which are standardized to ensure that that data is being collected. And I mean, on an ongoing basis, you can create a pilot with, you know, formula, uh, uh, manufactured data, but getting folks to go, yeah, we will succumb to a common process because in any AEC firm with more than one sector that they're dealing with, their sector is unique.
And yes, there's unique factors. but if you can't get to a point where you're able to get the data in there, then game over. And so it's really driven something that I did not expect. The enthusiasm for AI and the recognition that it is data driven and [00:42:00] the importance of having standardized data in a common data environment is absolutely a prerequisite. And the only way you can get to that is having some common standardized policies and or procedures. So now all of a sudden I have people have said, no, you know, our world's different. It's like, yeah, but it doesn't be that different if it's gonna provide us this. So it's really, I bring this up because no matter what we do, we're gaining something as an organization just from the data perspective alone.
And that's, that's been the, you know, my biggest struggle is getting folks to understand it. Listen, we, if we're gonna be data-driven, you gotta have good data.
Evan Troxel: Yeah. Yeah. You gotta start with that foundation. And, and so it, that's interesting to me to hear you say that just by going through that process, it's made you a better organization. Right. It, you don't even know if, if you're gonna be successful with whatever. Initiatives that you're gonna go because you do learn through failure.
I think it's really interesting that, that Vince is, is coming at it [00:43:00] with that attitude, which is like, swing for the fences and don't, of course we're gonna fail along the way. We have to assume that we will and not, and we're not, because one of the things that I've lived through in the past is what's the ROI on this and it, and, and that is a crystal ball kind of a question.
And to me as a designer of architecture, I, my response is, cynical response is, well, what's the ROI of design? Like you, you can't really put a number on it, right? Like it's, and you have to go through it even to find out whether things are gonna work or not. And again, assume things are gonna fail along the way.
So I, I think that all of that is, is really interesting. And it's great to hear the real life experience that you're sharing there, because I think a lot of listeners are going to be. about all of this, and it's great to hear kind of the things that they can expect to encounter along this path.
How important is it, I, I'd love to hear both of you respond to this. [00:44:00] How important is it for the leader of the organization to buy into this vision? Uh, is it, is it critical or, you know, because there's oftentimes we either see like a top down kind of initiative, but we also see bottom up grassroots kind of initiatives.
And, and this seems like it needs a little bit of both, but I, I would be interested to hear Mehdi, what, what do you think as far as leadership's buy-in and vision in this process for successful outcomes?
Mehdi Nourbakhsh: Yeah. Um, you know, typically the way that we see, you know, results in the best outcome is, you know, having the leadership support, uh, this initiative and give the employee, uh, autonomy to
bring forward the best ideas and create that culture in the organization. So it is both top down and, uh, bottom up. Um, oftentimes the kind of the wrong way of doing this is that Uh, the, [00:45:00] you know, people at the high level get together and say, okay, these are three areas that we should be focusing on, and people in the organization, which are, you know, really busy and, uh, they're just, uh, doing all the deliveries. Why do we need this and why do we need that? Um, so give it the, giving them some time, some slack to focus on these critical initiatives and bring their ideas forward that later, you know, some of the, the companies we work with, people are discussing their ai, why shouldn't we collect this data? I think this is best for our company if we collect that data. So they're, they're the one that are aware of the importance of data and discussing that and bringing those ideas forward to the technology team. Uh, the wrong way of doing it is that the technology teams, as I know everything and. These are the things that you need to do it.
The ownership really should be coming from the operation teams [00:46:00] and from the people in those, uh, you know, uh, segments. And then really the, the technology team to orchestrate that, uh, across the organization.
Scott Thompson: And, you know, one of the things I would say is, is, and I would agree with you a hundred percent, um, and it's not necessarily they have to, that the leadership has to embrace ai. It's certainly that's important,
but there's gotta be within the leadership, um, they have to embrace change, right? And there's a lot of AC firms where that's not the case.
Well, if you don't have that change mindset, well then, you know, forget. But that impacts everything. So the change is important to ai. Um, yes, having enough knowledge because there is some, some, some other concerns about that with, uh, jobs, et cetera. So being able to be able to communicate this, uh, you know, it was interesting when this actually came, came up for the first time, it was at shareholder meeting. A year ago, I guess it was [00:47:00] Vince, um, I got, I got advanced notice of what he was gonna say during his shareholder, uh, speech. And he said, oh, it's all about ai. And I was like, you know, advanced notice means about 10 minutes before it. And I go, I went to the board. I go, okay, this is going to, basically what he did is he, he lit a match in a room and I don't think he knew what was gonna happen,
but uh, you know, he basically said, listen, it's not gonna be other, um, AEC firms that put us out of business.
It's gonna be technology firms. If we don't get involved, someone else will take it. And we're seeing that there's a lot of technology firms that are now getting into business because it's a lot easier than trying to sell this technology to the businesses. So this idea of having a change mindset, someone who's looking forward, um, someone who's willing to take some risks.
I mean, clearly yes. We, we wanna swing for the wall, we also wanna have some small wins. So it's a portfolio side of things, but
what Betty said there is absolutely critical. the folks that are gonna be impacted most by this are the folks that oftentimes are not [00:48:00] spoken to. And if you don't get that buy-in, or a level of excitement or a sense of ownership of, yeah, they're addressing my problem, then it's not gonna work. My number one goal. I remember Vince asking me, um, what's the ideal outcome from this, uh, uh, business planning workshop with ai? I said, I'll be honest, the best outcome for me is that you've got the leadership of the organization sitting at tables, working through a business problem collaboratively. I don't care what comes out of that,
Evan Troxel: Yeah.
Scott Thompson: that process, which is
we can get people to start stepping away from, I've got this deliverable, I've got this deliverable, and start thinking about we've got a problem and work across. Across the, uh, the aisle with other engineers or even administrative folks and get their ideas. That to me, that that has been the biggest win. [00:49:00] I mean, I'm really looking forward to some of the solutions, but if we can maintain and build upon that cultural shift which has taken place, then that's gonna make us a better company. AI, or not ai, because a lot of
this stuff
Evan Troxel: transformative.
Yeah.
Yeah. It is transformative because it, it is one of those things where it . It, it, you've enabled the, the, the leadership or whoever's at that meeting to work on the business rather than just working on your client's problems. Right. And I think that's a hard thing. We talk about that a lot on this podcast, which is like, I, I went from working in the profession to working on the profession.
I, I really see my role through communication, through capturing conversations and getting them out there to everybody. As helping a stepping back and saying, look, these, this is industry-wide kind of stuff that we should be addressing. We should be having these conversations in the open. And that's exactly what I'm hearing you say is, is [00:50:00] because everybody's working on projects, right?
Even if you're in hr, you're working on your projects, which are it, it could be bonuses, it could be onboarding, whatever it is. And then you've got design teams that are working on projects. And as soon as that project's done, you got the next project and there's all these deadlines. And rarely do we have space or time to step back and work on the business, the design of the business.
Right. So I, that, that's what I, I took away from that. And that, that's incredible, right. To, because this does lead to like, it, it is a mindset shift, right. That, that you referenced earlier in the conversation. And I, I would be interested to hear a follow up, you know, like you've been going through this for the last year, but like.
I, I, I think later on it would be cool to hear like, is that still working for you guys? Did did it stick right? Because the stickiness of that is also something to measure over time and see if it actually did change the culture of the company.
Mehdi Nourbakhsh: Yeah.
Yeah.
And you know, we, we, you know, Scott and I talk, talk about [00:51:00] this
often, that what we are really doing, you know, is, you know, it's about ai, but it's not about, AI is really
building that muscle for the organization.
And, you know, at the beginning we, we gonna, you know, take, do it with the small lifts and weights and then over time, this muscle, when the muscle is being built, uh, we can lift, you know, heavier things.
And this is how you can. Uh, you know, have a leadership position in the age of disruption. Um, this year happened to be ai two years from now, who knows what's gonna come
and being able to continue that path, uh, forward is critical.
Evan Troxel: I that that idea of building the muscle is, is key because this has gotta be one of those things where Scott, like you, you had a little bit of a vision of the best possible outcome of this, but, but what is the ROI on hiring JA Tech to come in to do this workshop?
Scott Thompson: [00:52:00] Right.
Evan Troxel: you could have never have foreseen the transformative change in your business and the way people get together and the way that you ta are starting to tackle problems versus the way that you used to.
And I don't know how different it is, but it sounds different,
right? Like that is a, a business that's an advantage that
you have now that you didn't have.
Scott Thompson: Sam had actually put something on a, it was one of her LinkedIn posts, and, and it, it, it stuck with me at both. She and I use analogies maybe to a fault. But she had this, uh, very interesting analogy about, um, you know, when, when the movie industry went from, from, um, silent to the talkies and how it just disrupted everything and that You, you're going down this path and you have to recognize, you don't know what's gonna happen and you have to get a certain level of comfort of, well, it's classic, you know? Yeah. Be agile. Right? Now when you start dealing with an engineering firm and you're asking them to be agile, we're, you know, we're, we're we, we [00:53:00] do, you know, lean, uh, we're try to be as lean as possible using, you know, lean technologies, et cetera, and, and the lean, uh, methodologies. But now when you're starting to talk about, hey, you're successful only if you, um, have some failure, right? You try to tell an engineer
Evan Troxel: Yeah, totally.
Scott Thompson: basically are doing this iterative stuff and it's not gonna be perfect. It, it is a, it's a, it is a, it is a cultural clash.
Evan Troxel: Yeah. It is uncomfortable to
Scott Thompson: and,
Evan Troxel: Right?
Scott Thompson: it's because some of them pick up on it and some of them don't, and some of 'em never will, and that's okay. But it's, it's those things that I did not expect to encounter of like. Okay, I'm, I'm been doing it. I know that you do these iterative things. You don't do the waterfall approach anymore. That, but trying to bring that to your cu to your internal customers and go, now we're engaging you in the process. And they have to get comfortable with stuff that's been the sausage making in the back.
They've always been given, you know, this, this nice sausage that's like, Hey, it tastes great. They have no idea [00:54:00] all the misery that you have to go through and the failures and, and again, engineers do not want to fail.
And so that's something I didn't expect at all. Just even some of the
verbiage we use in terms of, you know,
can't using the word failure,
Evan Troxel: it, it's interesting to me because you mentioned it early on in the conversation, Scott, it was like the, the . It has to, you have to focus on the people in this problem. You don't focus on the technology. You don't even necessarily have to focus on what the opportunities are. And the, the risks are, it's like the, the goal is to get back and, and get to the people.
And Mehdi, this is something that came up during the workshop that I participated in as well. Right. And this, this is really like the big takeaway was you have to focus on the people. And, and I'm interested to ask you, how did you get to, to realizing that that is the thing that you need to focus on? I know you've been through experiences through your trajectory in AEC to recognize that.
So [00:55:00] can you tell the audience how you recognize
that?
Mehdi Nourbakhsh: absolutely. Um, so the kind of the, the mindset shift that, um, um, Scott talked about from Waterfall to Agile, so I used to be a structural engineer. You know,
I felt that, and when I went with working for a tech company, I was like, oh my God, what is this? And, and I. You know, as I work more and more on projects, um, I realize that most of AI problems are not AI tech problems.
They're people problems.
Um, people don't share data because they're afraid that if they share their data, they're gonna go outta job. People kind of hoard data or put bad data in the system and, you know, it's easy to say, Hey, yeah, this, uh, project failed. But if you go deep and ask why question five times, most of the time you get to people. [00:56:00] And if you think about the level of complexity, you know, technology, uh, process, and people, the most complex part is the people part. And that is often the root cause of all the problems. And until we don't address that, you know, we have the best data pipelines and technologies and everything in the world of it is being built. And there's no question around that. They're, they're being built. We can use them, we can leverage them, but until we don't solve the people problem, nothing is gonna change.
Evan Troxel: I, one of the stories that you told ha, I think it had to do when you were at Autodesk, and it has to do with kind of adoption of technology, right? Like we've been through this with bim, right? That there's the true potential of bim and then there's kind of like the very crappy versions of BIM that we've adopted that never really got us there, right?
It's, and it does always come back to the, the people [00:57:00] issue. It could be training, it could be job security like you mentioned right there. Like people intentionally sabotaging something to take the focus off of them and, and it gives them job security. I mean, there's all of this weird psychology going on, but, but.
I mean, you correct me if I'm wrong, but I think you shared a story about it had to do with adoption and just realizing that like, no, we actually have to focus on the people. We, you can't just keep selling this beautiful vision of, of the thing at the end if we can't actually help people get from here to there.
Right. And so I, I, to me, that that was kind of the nut of what you were talking about. There was like, no, we have to focus on the, the people who are actually gonna be operating the technology to get to that vision of the future.
Mehdi Nourbakhsh: Absolutely. Yeah.
Scott Thompson: Yeah.
interesting. Because, you know, like a lot of AC firms, I mean, we've adopted bim, we've, you know, gone from the, you know, BIM 360 to acc all of our projects are running out there right now. And, and there's, as, as, as you mentioned, there's just so much more [00:58:00] potential, right? Um, and, and I would say there's a lot of reasons that, that, that people, that is a struggle for people to change.
But I'd say the primary reason is most people are thinking like this, what's in it for me? Now, when you're starting to talk about a lot of these solutions, um, you're talking about the greater good of the company as a whole. You may have a solution. BIM is a great example. If someone's got a process for doing RFIs through the, through the mail, and it's working great for 'em, uh, why should I change this?
New thing's not necessarily gonna make my job any easier, specifically. It may not, it may even make my job a little bit more difficult. But if you step back a little bit
and you try to figure out how you connect. The individual to the mission of the company. And that's a whole nother issue. It's like, well, why do I care about the company?
I care about my job. Well, because you don't have a job if the company's not moving forward. So trying to close that gap and saying, listen, we're asking you to change. It may not necessarily can make your day-to-day job [00:59:00] more efficient. That's a classic theory of constraints, right? Not everything's gonna work at an optimal level for an optimal system to work. So you have to help people understand that you, you don't wanna use words of cog in a, in, in, in, in a system, but we're all cog, right? And somehow they have to step back and look at the overall design delivery process and where they fit and how they contribute to these other pieces. And yes, your, uh, gear may move a little bit slower now because of this, but the overall system is moving faster, and that's a really difficult message to get to an individual.
It's that classic what's in it for me?
And that's a, that's, it's, it's an important thing to. to. not forget because any changes that require someone to become less efficient, certainly in the short run, certainly in the short run, and no one wants to become less efficient when they have more work coming at 'em.
Evan Troxel: right. Mandy, what are we missing here? That, that is a, a major point that [01:00:00] really makes sense to talk about in this podcast regarding the content that's in your book and or the workshop. Um, you know, I, I keep thinking, I keep rethinking about the shift that happened in sentiment from the beginning to the end, and how you reinforced that shift the whole way through and really held people's hands and worked directly with us as groups of individuals to talk things through.
Uh, but what else is there that we, that we really need to talk about today? Just to start wrapping things up here.
Mehdi Nourbakhsh: Um, I think, um, one of the thing that is missing and we talked about a little bit, uh, today is about. Um, at the, at the industry level because as we are working with other companies, you know, as I said, they all have the same, uh, they're looking for the same problems that somebody else should be, should, should solve that. I think [01:01:00] what we did during the workshop, and, you know, I'm a big believer on that, is to having a space for conversation. To create a space where industry leaders like Scott, Vince, and, and you, Evan, and all of us can come together and talk about things that really matters to, to the industry, to learn from the lessons, to see what is working and what is not working, and having that space. You know, we go to these conferences and, you know, we are in the Consumption, you know, era when
you have three seconds after watching a movie to not go to the next movie. And we just consume, consume, consume. But we don't have time to reflect and we don't have time to
think and we don't have time to talk to each other. You go to a conference, you get bombarded by, you know, all the information. And for that, we are [01:02:00] creating a small community of, uh, people in the industry, AI practitioners to come together and talk about things and, you know, have a discussion about what is working and what is not working. And I think this is critical for, for our, our industry. And, uh, you know, I think, you know, early later this year, early, you know, early later this year and early next year, we are gonna be launching this community and. gathering people together to really talk about things that matters to the industry, and really helping each other to move this industry forward.
Evan Troxel: That's fantastic. I hope that you'll pinging me when you're ready to do that, and I will help you get the word out about that community, about getting people involved in it, because I'm sure people who are listening today will want to be a part of that if they are interested. Uh. What you were just saying there reminded me of something I wanted to bring up earlier, but then forgot, which was, [01:03:00] I had a, I had a leader in, in a company that I was working at, and it was at this point in my life when it became clear, the difference between leadership and management, kind of going back to the earlier part of our conversation where I was asking about the importance of vision and leadership and, and Mehdi, you said that, you know, create, create the vision, create the, set the problem, and then let people act and have their autonomy in doing it.
Create that space, right? Is how you put it. And this leader in my life said, look, you can do whatever you want to do. Like you're gonna think of things that I have never thought of. It's my job to you achieve those things. What, what he didn't say was. I'm just gonna step back and watch from the sidelines.
What he said was, I am going to help clear the path so that you can get there. [01:04:00] Right. And to me, like there's, there is a sense of giving autonomy to people so that they feel like they can own the process and they can fail and they can succeed and do all of those really important things. But to have, have that advocate there as well, who actually, if there's roadblocks, they clear them on your behalf so that you can achieve the vision that you have, the trajectory that you have, the ownership that you can, the, the full potential of that I think is super, super important.
And to me, like that's what I think of when I think of leadership. I think of somebody who says, I've got the vision, or I, I loosely see what the possibility here is. You're gonna execute it, but I'm gonna help you. I. Execute it by clearing the path for you so that you can actually make it happen. That we don't see that enough.
And so I, I just want to throw that out there because those are the kind of people, the technologists, the doers, the people with rolling up their sleeves and getting their hands dirty, [01:05:00] need to look for those people. It, it really helps if you can identify who those people are in your company so that they can help you get to where you see things needing to go.
Scott Thompson: A hundred percent. A hundred percent. You know, it's, and it's, it's interesting just, you know, because we're at this stage of, of our project right now where, you know, you know, Mehdi has done a tremendous job of getting to this point of, okay, the ideation and getting to a point, it's like, okay, these are projects you should pursue.
Well, you know, YA tech, um, you know, they're not gonna implement it for us. So we're, we're working with another firm and possibly looking at doing, having them do the, we're not gonna hire a bunch of ML engineers. That's not, you should talk about starting slow. The last thing you wanna do is hire a bunch of AI specialists, you know. There's people out there that do that, and there's good people that do that. But this whole idea, you, you just said something about, you know, clearing the path and making sure that things are going fine. Um, and I haven't even shared this with Mehdi yet, but you know, one of my biggest concerns is going from this state of [01:06:00] enthusiasm, ideation, opportunities, creating this, this environment. And then you go into the implementation
and, you know, that is a radically different space. And how do you maintain that leadership, which Ja Tech has provided and keep this thing going, um, you know, let the implementers implement, but put it all in the context of, listen this all, you know, someone who's going to have that context of the whole journey. And, you know, I'm hoping that me and I can spend some time next week in, in, in Vegas at AU and maybe talk a little bit about what does that look like for AgTech? And you, you've probably been through it Mehdi. Um. But I do think about this, this, this can't be a handoff and then see you later, right? As you said, it's got a stain and you, you know, I wanna make sure that we keep that going so we can continue to build upon
this culture of.
Evan Troxel: Yeah.
Mehdi Nourbakhsh: Yeah,
absolutely. Um,
Evan Troxel: Yawning Mehdi. [01:07:00] You can't yawn
Mehdi Nourbakhsh: no, uh, I was coughing. Uh, sorry. Um,
Evan Troxel: So.
Mehdi Nourbakhsh: a allergic reaction to dust. Um, and yeah, so you know, the journey continues. You know, when you start this, there is no stopping point. And, um, I always think about this journey as like the way that Warren Buffet think about the investment. You know, in the first couple of years, you know, your investment is, is going to look like flat, but as you do this more and more, you get your exponential return on investment. And that is
creating true culture of innovation for the company. And creating that true environment where you don't need to hire any other, you know, employees and people beg to work for your company. And this doesn't come like quickly. And you've got to keep working and keep building that environment and that culture because these are the companies [01:08:00] that the young generations wants to work on, not the other companies that we've been doing this for 50 years. So we're gonna keep, continue doing that. So the journey
continues.
Evan Troxel: Absolutely.
Scott Thompson: Yeah.
Evan Troxel: Absolutely.
Scott Thompson: if I, if I can, and you can edit this out if you'd like, but I, I would say something, you know, 'cause one of the things that, that, that Mehdi is looking at doing is building this community. Okay. And, and our industry is, is as paranoid as any industry in anywhere, right? I mean, there is so much paranoia about working with each other. And we have an opportunity here with AI because everyone's in the same boat. Everyone's trying to figure this out. And I've had some great conversations with other, um, leadership from other AEC firms and I said, listen, let's not be protective. Let's share what the opportunities are, what the challenges are, let's learn from each other. And, and so much so that, I actually had a meeting yesterday, I set up a meeting with another, uh, firm to bring my [01:09:00] security folks and their security folks together. Okay. Again, here's something that's facing the industry and we're all working in our silos thinking that
we've got it figured out. And if we can cross that, it's, it's all about, which is one of the things that, you know, you're doing, uh, with, with this, is you're building this community.
And if, if we can build that community and not be so fearful of competition, uh, how this is gonna impact us winning a project, and there's ways to do that. There's some real important things that have to be addressed in this industry that are not gonna be addressed by a single company. It's just not gonna be solved.
And I would encourage, you know, all the listeners to, to start reaching out to other firms and say, Hey, what are you doing over here? People wanna share and they wanna learn. And it's not like I'm an expert and you're not. It's. Let's share some of the miseries, some of the excitement, some of the challenges, how we've addressed 'em, whether it's security, whether it's ai. It's really critical to the industry that we join forces and, and really make the industry much
Mehdi Nourbakhsh: and,
and, and
Evan Troxel: always think about it as a parent. [01:10:00] I think about my kids and I think about how I give them advice, and I give them shortcuts and I, because I've learned things throughout the years, and I want them to pick up where I leave off, right? I don't want them to have to reinvent the wheel of family and finances and all of this stuff, right?
I wish we'd treat business more like that, which is like, I'm gonna be as helpful as I possibly can and not protect my own stuff so that I have the security, but I'm, I'm actively looking to make sure the next generation is successful. I wish we could see a lot more of that.
Mehdi Nourbakhsh: Yeah.
Scott Thompson: there's enough work out there for everyone.
Mehdi Nourbakhsh: yeah.
And, and, and just wanna add to what is what Scott said. Um, one word that came out for me was competition. And so I wanna double down on that. Uh,
what is really this competition? Who are we competing against? Um, I don't think that we are competing against each other. In the AC [01:11:00] industry, I think we are competing against a tech company who hasn't entered the industry and will be interested three years from now, five years from now, with $20 billion budget to enter this industry.
That's the competition. So, um,
Scott Thompson: Yeah,
Mehdi Nourbakhsh: we can choose.
Scott Thompson: you are spot on. You're spot on.
Evan Troxel: Yeah, I, I, I agree with that, that that's a great place I think to, to wrap this up, Scott, I absolutely will not cut that last part out. That was fantastic, . I appreciate you bringing that up. And, uh, and, and this was a, a really fantastic conversation. Y tech.com is the website where you can get in touch with Mehdi.
I'll put a link to me's, uh, LinkedIn. Scott, I will put contact information in the show notes as well, if you want to talk to Scott and, uh, get an idea of, of even more of the story of maybe what they went through, because I'm sure he's an advocate, uh, of the process. [01:12:00] And the book is augmented and Mehdi. This is, this has been a fantastic journey.
I can't wait to see where this goes. I mean, this, this is one of those moments in history and people have said this is not original at all. It's like in the, the next iPhone moment is how people are kind of categorizing it, or, and, and it's, I think it's really interesting, right? Because it's. I can't even imagine what the next three years are gonna be like at the pace that we're seeing things come out.
And so it's, it's really exciting to watch and it's really exciting to get to talk to experts like you two about how you're actually implementing and dealing with this change that needs to happen and, and having success with that. So I applaud you both. Thank you so much for joining me on the podcast today and, uh, until next time
Scott Thompson: Great.
Take care. Thank,
you very
much.
Mehdi Nourbakhsh: you so much. And, uh, and, uh, if, um, you know, if, um, there's a chance that, uh, your audience can go to our website and download the AI workbook, [01:13:00] which has all the instructions
on how to bring AI to your company on your own pace and mention your, uh, podcast, that will give them signed copies of the book, uh, US only. So that's also an offer that we put on the table.
Evan Troxel: Awesome. That's very cool. All right, well YegaTech.com And is there a, is there a specific addition to that URL where people
should go to get in touch with you?
Mehdi Nourbakhsh: yes. I'm gonna put that in here. YegaTech.com/free-resources and
Evan Troxel: Okay, great.
Mehdi Nourbakhsh: destroy.
Scott Thompson: that's an offer that anyone listening. You'd be foolish not to take 'em up. I mean, I'll, even though because I had the workbook and that's free. But to get a copy of the book, uh, it, it really is a valuable resource, uh, on, on learning about this journey. So I would really encourage all your listeners get the book. Don't be afraid. Reach out to, to, to Mehdi talk with me. I'd love to share our stories and I'm [01:14:00] sure that you can share some stories with me as well. So
here
Evan Troxel: Yeah, absolutely. Well, thanks for writing the book, Mehdi. It's, it is a fantastic resource, and I also encourage the listeners to grab a copy of that, and I'll have a link to that in the show notes as well. So, until next time, thank you both.
Mehdi Nourbakhsh: Thank you.
Scott Thompson: take care.
Mehdi Nourbakhsh: Alright, ​