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Software that only lives on a screen is really easy to copy right now.
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Like the data center is just, they're not just construction projects anymore.
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They're energy infrastructure projects that happen to have really large buildings around them, right?
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So a million dollars is kind of like a little gnat flying around your head.
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If you're a data center, like a $17 billion project, like who gives a crap at that point?
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Reality capture isn't the real hard problem really to solve anymore, right?
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The problem is turning that like observation into something useful that there's
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only let's say 200 to 500 of those projects you know that that hit that at ballywood
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right and there's 10 000 that are like,
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do i even have project controls.
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Well, so I've gotten, I've gotten a hard time for not doing intros on these
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reviewed episodes. And so I think I'm going to do intros this time,
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mainly just from how I know each of you, starting with you, Aaron.
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I knew you from, I think, Walsh time. I think I met you through Blue Collar Capital Partners.
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And then obviously we've stayed in contact. I think, you know,
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how I refer to you, to other people, you're like the only VC that makes sense to me.
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So that's how I describe you. Hanu, you were an Imagineer on a project.
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And I think, you know, if you were kind of stored as a contact in my book,
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it would be like the Imagineer that I really liked working with.
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And the one that wasn't always jumping down his throat.
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The one that actually understood the GC perspective. Yeah, that's right.
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It was very helpful. You were a good emotional support during that project.
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But, and then Tyler, you and I have just like crossed paths and then started
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hanging out. I don't really know the story, but it might've been LinkedIn.
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You were doing something cool on LinkedIn and I was like, hey,
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that's cool. Can we talk? And you were like, yeah, let's chat.
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Yeah, that's the dude that just kind of shows up places. And you're like,
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I don't know that guy. I don't know. He just kind of follows me around.
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So, yeah, it's fine. I'm good with that.
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Well, I appreciate you all
Load full transcript
coming on. I think, you know, September was an interesting month.
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We had some stories come out. I think just looking at the stories we've got
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here, so we've got BuildDot's kind of large valuation spike.
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We've got some new agentic AI stuff coming out from Autodesk.
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You know, potentially a little bit like Groundbreak, seeing kind of what's actually
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real in the strategy will be interesting over the coming months.
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New Jersey, letting unpermitted generators keep running on a data center campus.
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And there's a fine associated. We got Dodge's wild kind of mega project driven
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construction starts and record low construction unemployment,
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along with Caterpillar and Field AI announcing a partnership, which is interesting.
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So I wanted to start with BuildDots.
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I guess, Aaron, to maybe kick us off here, everyone's tried to solve for progress
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tracking in some capacity. The reality capture field is pretty crowded.
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What makes BuildDots kind of differentiated to allow them to get this $1 billion
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valuation, in your opinion?
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In my opinion, so for clarity, we're not investors with BuildDots. Okay, yes.
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And I'm not like that close with the team. So anything, my opinion here is just
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like me as an observer, not me for our fun.
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So here's what I have observed from the sidelines as not being a direct user
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of GoldDots, but, you know, kind of,
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through the channels, is they built a more comprehensive link between how do
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you tie out the video walkthrough into a reporting function with less hands-on keys, right?
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Are those hands-on keys worth the billion-dollar valuation or not,
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I think is an interesting question from a pure tech side.
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And I'm not close enough exactly to articulate that.
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I do think that it sounds like there's some wind in their sails from the data center push.
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But, you know, just and maybe Stephen, why you like my approach to venture,
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I'm always similar to a contractor worried about diversity of your client base
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and when the other shoe falls.
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Right. Most great GCs are thinking hard about what's my what's the next capital
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plan that I want in my backlog so that as the centers eventually dry up.
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I don't know if that's been three years, five years, or eight years.
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They have enough work to continue a cash flow generating, reasonably profitable,
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high-employment machine.
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And so I always look at these big valuations saying, after data centers,
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what's next for progress?
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And so that's kind of like my big quandary as I look through some of the valuations
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that we see in the market today.
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Noting there's a lot of billion-dollar companies and, you know,
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Tahuwa has been around 17 years or something like that, just crossed,
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you know, rumored over the billion-dollar valuation.
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Very different business, you know, very different timeline to get there.
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But, you know, it's certainly not unheard of.
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I mean, it's also interesting to maybe, you know, argue like how much of this
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is just inflationary of like the monetary supply is expanding.
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And so valuations are kind of going up accordingly. But I do think there's there's
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real tech behind that as well.
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Hanu, from the GC side, obviously, you guys are potentially obviously a user
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of many of these reality capture systems.
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Do you see anything kind of intrinsically true about build dots from a product
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set that's differentiated from what you guys have used?
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Yeah. I mean, I think you mentioned earlier, like it's a pretty saturated market.
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I mean, I think the one thing that the funding tells is just like,
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look, investors believe in progress intelligence.
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It's becoming an important category. And I actually do think that,
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I mean, this is kind of the future, right?
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I mean, the tech is real. It's not perfect, right?
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And the funding is real too. I mean, they're making real money on these jobs
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and people are willing to pay for them, right?
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We've actually just gone through year-long evaluation of a couple of these different
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solutions like BuildDots and Doxel and Cupix. And there's, I could probably
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name a dozen others, right?
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And I think we are trying to solve a real problem, right? I mean,
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progress tracking on construction projects is
pretty inconsistent.
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And it's, you know, the reality capture isn't the real hard problem really to
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solve anymore, right? The problem is turning that observation into something
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useful to be able to make operational decisions quickly enough that we can actually
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still change an outcome.
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But I think we're still trying to really see what the ROI actually is. I mean, based on our.
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Early evaluations, obviously it's value in the documentation itself.
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Progress reporting, schedule management, like, but those are three different
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things and you shouldn't automatically treat them as the same ROI.
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But, but just getting everything in one place is like a single source of truth.
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It's like a good start, but you know, it's, you know, these automated,
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it's not an easy button, right? Like there are no automations that are magical human in the loop.
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It still takes, you know, anywhere from like 24,
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to 48 hours to get information so there's a challenge of this lag and it's not
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really the primary differentiations between these solutions is just,
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how quickly can they turn it around how cheaply can they do it,
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and you know how accurate is the information because the reality is is if you
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still can't measure something you can't capture with a camera right so
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it's not a perfect solution with 100% accuracy by any means but it's getting
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a lot of traction and I think you know we're pretty bullish that,
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this technology is here to stay, and we're continuing to work with all of them
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to try to make them better.
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All right, spots to break. Lars, real quick, when was the last time you got
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a new set of drawings from an architect and they didn't cloud anything?
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Well, the one that cost me a couple hundred grand was back, I think, in 2017, so...
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Lesson learned there. Yeah. So, you know, what I like about what Trunk Tools
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is building is they're looking at tools to help kind of remove the mundane from the job site.
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And, you know, same as you, every time there was a bulletin or an addendum,
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I would go back to designers and ask them to at least highlight or give me a
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cover letter on the changes.
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And that was always like pulling like teeth, but Trunk Tools is now automating
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that. So you get a bulletin come in, it automatically highlights the changes.
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You don't have to do a thing.
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Well, it's also hitting RFIs, right? It's also hitting submittals.
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And when we think about standardizing ops, right, and providing that,
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you know, sort of resource to those field operators, what I see it as, you know,
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it's sort of like this, like, mentor within the company that structure standardizes,
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keeps it moving in the right direction, looks out for risk.
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And just this last week, you know, I had a QC manager just pass along the submittal
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to an owner without doing a review because he was too busy and it was wrong.
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And, you know, the classic owner statement is, did you even review this? Right.
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So this to me is carte blanche. We absolutely did.
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And think about getting that first pass before your field manager ever even
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actually has to do the first pass. Someone's doing it for them.
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So to me, it's about speed. It increases accuracy and helps standardize ops out in the field, right?
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Yeah. And this is the kind of AI that we've talked about on the podcast,
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really appreciating, right? Which is looking at ways to elevate the craftsman
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at the heart of project delivery.
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Give me time back so I can be out in the field managing risk, right? Yeah, 100%.
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So, all right. If you're a little curious, check it out, trunktools.com forward slash podcast.
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And if you mentioned construction conversations, you get a discount.
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Discount demos are free and we get, and you guys get a discount. So let's go.
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I want, can I push on the valuation? I want to push. So like the valuation side is one side of it, but.
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I think we're seeing a really big trend here with a lot of the investments that
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are being made, because like software that only lives on a screen is really easy to copy right now.
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So project management softwares and things. So I think investors are looking,
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really, really hard at what are those things that reach down into the field
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level where I actually need people to go out and capture something and bring
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it back to me for processing.
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And so
I think that's the reason why we're seeing a lot of these moves right
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now thinking at some of the other acquisitions like drone deploy and things along those lines.
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I feel like I'm just seeing more and more of a trend investors know like hey
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software only isn't as super safe as it used to be
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whereas right now I want things out in the field like I want assets out in the
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field capturing things and driving value,
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so I mean yeah we could argue about the valuation but,
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You know, I can see why the money is being raised here.
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So I guess to that point, though. Well, they need the money,
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too, right? I mean, just a quick note. They need the money. I mean,
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they're spending quite a bit of either tokens to process this data,
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and then obviously they're still this human in the loop.
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And they need a lot of this money to stay afloat, but it's also about training
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these agents, right? That's going to cost them money, and I think they're getting
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smarter, getting better, right? But the vision AI is getting smart better.
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And obviously, the more they train these machines on the construction data,
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hopefully, the better they'll get.
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And hopefully, we'll be able to bring the cost down as well.
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Well, I don't know build lots well enough, but just from the brief research
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I've done, it seems like,
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you know, the kind of the frontier for a long time was, can you accurately kind
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of translate work in progress into digital progress tracking?
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And it seems like they've kind of taken it beyond that to now,
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starting to scratch the surface of kind of predictive forecasting or being able
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to point back at your schedule
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based on trends inside its kind of progress tracking brain what that's going
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to do to your schedule have you seen any results from that or you heard any
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kind of positive stories hanu from the field of like hey We're not seeing,
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some kind of beginnings of predictive.
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I think we're not there yet. But I mean, if we can get to a place where we can
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get perfect information about what was installed yesterday, like on a consistent
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basis, because right now a lot of the
capture is done on a weekly basis, right?
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There's some constraints around doing it daily, whether it's people or whether
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it's just processing time, right? They can't, you know, none of these solutions
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can turn it around really fast enough today.
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That's why it was my comment earlier was like, who's going to get there first
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where they can give you that information the next day is really going to be
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a big differentiator. So.
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And tying that to a schedule, because, I mean, obviously the capture doesn't
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know when did the work actually start unless you're out there doing it daily.
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So it's really getting to that information that's consistent and aligning.
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There's obviously a lot of alignment between like just schedule and model and
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what's actually being captured, where it's on capture.
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Right. So once we get there, I think it'll be able to help drive those decisions.
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We'll be able to start getting much more predictive trends. Right now,
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it's just telling me was something installed or not installed, right?
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But when we are getting that consistent capture, we can start getting some trends
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and metrics around production and performance, which could then also help us
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sort of do some analysis on, hey, are you likely to meet that end date or not, right?
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So it's getting there, but it requires a lot of setup.
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I waited to minute 15 to spice it up. So taking that, like, you know,
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let's talk about the schedule piece. So we're investors in an amazing company
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called SmartPM, right? And I think a lot of you guys have probably bumped into them.
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So a big question is, is your schedule built correctly, right?
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And like you guys have seen, like schedules are just a disaster in plenty of projects, right?
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And so also there's only like three folks in the general conditions budget,
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you know, for a whole bunch of the work out there in the world, you know?
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And they got to update the schedule and like make sure the supers are paying
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attention and like arguing to get the electrician on the site and you know,
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all the other stuff that comes with just running a job.
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And so this idea of spending a big chunk of your general conditions budget to
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have this like automation for the vast majority of projects,
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which are not mega site data centers,
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is like, you know, I think pretty disconnected from reality, right?
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And that's why I'm like super long on like, let's nail the big chunk of the
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market exceedingly well.
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In the cost constraints that is general construction today, which is relatively
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lean general conditions budgets.
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Really good tech for really big projects that can do stuff in 24-hour turnaround
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might make sense, but I would guess that there's only, let's say,
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200 to 500 of those projects, you know, that hit that at Ballywood, right?
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And there's 10,000 that are like.
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Do I even have project controls? You know, do I understand the trade allocated
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to each one of the line items in my schedule so that when I see it slipping,
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I call the guy that actually makes the difference?
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That's kind of our philosophy, at least. And like, that's kind of where I see
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some of these disconnects between what can tech do and like, where is the market?
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Sponsor break. If you spend any time running a project, you know,
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the answer is almost always sitting in the contract document somewhere.
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The catch is that it's almost never in one document. It's split across the contract,
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the specs, and some flow-down clause three layers deep that nobody connects
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until it's already cost money.
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That's the whole premise behind Document Crunch. That risk doesn't live inside
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any single document. It lives in the gaps between them.
00:16:27.869 --> 00:16:32.366
And most teams never look at all of them together until they're standing in a dispute.
00:16:33.063 --> 00:16:37.617
The average construction dispute in the U.S. now runs about $60 million,
00:16:38.311 --> 00:16:40.685
according to Arcadis. It's a lot of money.
00:16:41.086 --> 00:16:45.057
And the root cause they point to isn't fraud or bad intent. It's people not
00:16:45.057 --> 00:16:46.669
fully understanding what they agreed to.
00:16:46.895 --> 00:16:49.769
So Document Crunch builds a platform around closing that gap.
00:16:49.972 --> 00:16:55.580
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00:16:55.928 --> 00:16:59.757
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00:16:59.757 --> 00:17:03.007
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00:17:03.007 --> 00:17:07.387
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00:17:07.602 --> 00:17:10.637
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00:17:10.637 --> 00:17:15.386
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00:17:15.676 --> 00:17:20.677
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00:17:24.947 --> 00:17:27.901
Yes, your point is this is potentially...
00:17:28.882 --> 00:17:36.075
Like a mal direction for where the tech is not necessarily needed it,
00:17:39.037 --> 00:17:43.345
the good thing is to take so take so take what someone said and then like twist
00:17:43.345 --> 00:17:45.387
it into something that they don't want to be said,
00:17:46.155 --> 00:17:48.815
i guess i'm just trying to understand do you think the tech shouldn't be pointed
00:17:48.815 --> 00:17:53.265
in this direction or that the tech doesn't work no no i'm sure the tech works
00:17:53.265 --> 00:17:55.303
right Right. But like, how big is the company?
00:17:55.901 --> 00:18:00.272
Right. So if there's two to 500 projects out there that need this daily reporting,
00:18:00.609 --> 00:18:05.090
how, you know, like, how big is that company? Is that a $20 billion, $30 billion company?
00:18:06.026 --> 00:18:12.358
Well, is your point also that the cost hurdle is such that it can't be pointed
00:18:12.358 --> 00:18:15.082
at every project over a certain size?
00:18:16.178 --> 00:18:19.726
Totally. Well, and the reality of how most projects operate, which are like.
00:18:21.818 --> 00:18:25.703
Just not doing daily walks. Like they're just getting the blocking and tackling done.
00:18:25.854 --> 00:18:29.008
You know what I mean? Right. And like the tech that solves the blocking,
00:18:29.008 --> 00:18:33.278
tackling at a price point that is applicable to everyone in the market and then
00:18:33.278 --> 00:18:35.102
built up with killer analytics.
00:18:36.198 --> 00:18:40.838
Wait do we do we build anything that isn't a large-scale data center at this
00:18:40.838 --> 00:18:49.058
point i thought that's that's that's all we do that's all we do now man that's the entire u.s gdp right.
00:18:50.729 --> 00:18:55.348
Well are there other buildings i'm confused yeah i know i know i uh i changed
00:18:55.348 --> 00:18:57.271
my toilet seal so yeah yeah,
00:18:58.258 --> 00:19:01.228
look steven to answer your question maybe a little bit and then i think it's
00:19:01.228 --> 00:19:05.015
an and like i think you need sort of enhancements I mean, this is why we're,
00:19:05.729 --> 00:19:10.008
kind of living a little bit of this tech boom, construction tech boom.
00:19:10.008 --> 00:19:14.194
I guess the trend has been up since 2020.
00:19:15.278 --> 00:19:19.748
But yes, you need a good plan, right? But
what this is solving is,
00:19:19.748 --> 00:19:22.008
are you even building according to the plan?
00:19:22.008 --> 00:19:26.308
Can we just get the field and the office in alignment with like,
00:19:26.308 --> 00:19:28.498
hey, where are we building and how fast are we building?
00:19:28.498 --> 00:19:31.358
Are we meeting the schedule? I mean, you got to have a good schedule if you're
00:19:31.358 --> 00:19:32.608
garbage in, garbage out, right?
00:19:32.608 --> 00:19:35.608
You've got to start with a good schedule. And I think to, Aaron,
00:19:35.608 --> 00:19:41.665
your point, yes, you need some checks to validate that the schedule is sound,
00:19:42.187 --> 00:19:44.158
makes sense, has the right flow.
00:19:44.178 --> 00:19:48.858
Because what ends up happening, if it doesn't, then the field basically goes
00:19:48.858 --> 00:19:51.478
and builds what they think is best versus following the plan.
00:19:52.444 --> 00:19:56.548
But this is solving a different problem, right? And I think both are valid problems
00:19:56.548 --> 00:20:03.209
to solve for. And obviously there's technology here that we can use for both use cases, right?
00:20:03.592 --> 00:20:06.998
Yeah. How do you sync those up though is just really, I think,
00:20:06.998 --> 00:20:10.233
what you need to set up a good process around regardless.
00:20:11.102 --> 00:20:14.624
I mean, you can't just plug chat GPT into it and just have it like push the
00:20:14.624 --> 00:20:16.987
data back. What are you talking about, honey?
00:20:19.904 --> 00:20:24.904
It's easy. It's easy. It's easy. You just do it. All right. So from build dots
00:20:24.904 --> 00:20:31.254
to Autodesk, I was actually at AU this year. Honey, were you at AU? I didn't see you. Yeah.
00:20:31.604 --> 00:20:34.264
I popped in there for a few days. Yeah. I didn't stay the whole week.
00:20:34.284 --> 00:20:36.044
There were a couple thousand people there.
00:20:36.444 --> 00:20:40.468
Yeah, that's right. I did run into a run of people. I'm surprised I didn't run into you, man.
00:20:40.961 --> 00:20:45.478
I do, I like that you helicopter into conferences. You're like in and out, pretty surgical.
00:20:46.504 --> 00:20:49.484
You're like, all right, sorry, I just landed. I've got a 2 p.m.
00:20:49.484 --> 00:20:53.924
And then I'm going to fly out my private jet later. Yeah, two days max in Vegas
00:20:53.924 --> 00:20:56.432
for me, man. I've been there. Yeah, no, that's a good rule.
00:20:57.244 --> 00:21:02.295
So I guess, you know, one of the takes I had as I walked through the floor was,
00:21:02.834 --> 00:21:09.006
seems like more space on the exhibit floor was taken up by Autodesk than maybe in previous years.
00:21:09.314 --> 00:21:14.729
And there was a big focus on kind of autodesk agentic presence i think,
00:21:15.493 --> 00:21:19.744
the the big question especially after groundbreak last year which then kind
00:21:19.744 --> 00:21:25.740
of resulted in data grids acquisition is how much of what we
saw at adu was was marketing,
00:21:26.238 --> 00:21:30.604
versus like real products did do you get you probably had some conversations
00:21:30.604 --> 00:21:32.520
with autodesk while you're there what was your sense,
00:21:33.535 --> 00:21:37.409
Well, I mean, obviously, we're a longtime customer with Autodesk,
00:21:37.409 --> 00:21:40.849
and we've been in these beta programs for, you know, probably well over six
00:21:40.849 --> 00:21:43.139
months before the announcements, right?
00:21:43.139 --> 00:21:47.129
So they are real. Some of them are obviously ready. Some are still in beta,
00:21:47.251 --> 00:21:49.853
and some of them are still in sort of the vision.
00:21:50.560 --> 00:21:54.629
But, you know, we're pretty excited about them. It doesn't obviously magically
00:21:54.629 --> 00:21:57.689
fix the fragmentation of our construction information.
00:21:57.689 --> 00:22:02.198
But you know i think everybody's sort of building these agents and their platforms,
00:22:02.754 --> 00:22:08.359
you know but you know like before like you know before they're going to be solving
00:22:08.359 --> 00:22:11.329
all of our world problems obviously we got a lot of work to do and just maybe.
00:22:12.389 --> 00:22:15.689
Entering the right information in there making sure that you know the fragmentation
00:22:15.689 --> 00:22:21.234
doesn't create more problems because now we're consuming the wrong information faster right so,
00:22:22.053 --> 00:22:26.319
but i think the fragmentation is the story Like, I think when I think of Autodesk
00:22:26.319 --> 00:22:30.819
and their kind of app environment, I think of like 10 different environments
00:22:30.819 --> 00:22:32.959
where duplicate data potentially lives.
00:22:32.959 --> 00:22:38.139
And so I'd be interested to understand within the master prompt of any agents
00:22:38.139 --> 00:22:43.179
that they're building, how are they handling elements that contain different
00:22:43.179 --> 00:22:47.297
information depending on the forum, whether it's Forma or, you know.
00:22:47.778 --> 00:22:51.039
How are they handling their own internal fragmentation? Yeah,
00:22:51.039 --> 00:22:53.206
exactly. From all the acquisitions they've done over the years.
00:22:54.089 --> 00:22:57.449
Yeah. I mean, the fact that they are sort of building, I guess,
00:22:57.449 --> 00:23:01.949
this sort of an ecosystem of information for the project construction lifecycle,
00:23:01.949 --> 00:23:03.999
I mean, it's a challenge to solve for.
00:23:03.999 --> 00:23:09.253
I mean, I think, but the fact that, you know, they are still,
00:23:09.415 --> 00:23:12.581
for lack of a better term, a system of record, right?
00:23:12.744 --> 00:23:16.809
And, you know, obviously it's how well are you managing that system has to do
00:23:16.809 --> 00:23:19.628
with how well is that information to be available and used for you.
00:23:20.400 --> 00:23:24.835
But you know I don't know that we're anywhere near really being able To get
to like,
00:23:25.691 --> 00:23:31.058
You know, what's the right baseline schedule versus the current schedule?
00:23:31.058 --> 00:23:34.288
Are we building from the contract document from the working model?
00:23:34.288 --> 00:23:38.264
Like, does it really know how to analyze, like, what is the most current information,
00:23:38.827 --> 00:23:41.348
and, like, what actually has authority over what?
00:23:41.348 --> 00:23:44.528
I think that's something that I think we're going to have to continue to train
00:23:44.528 --> 00:23:47.808
these things to get smarter. But it's going to be really good at,
00:23:47.808 --> 00:23:52.568
like, just retrieving information back to you. Think of like a chat TPT built
00:23:52.568 --> 00:23:55.600
into, you know, your construction management platform.
00:23:56.207 --> 00:23:59.448
And, you know, it'll retrieve information for you faster.
00:23:59.448 --> 00:24:02.168
Maybe that's a good problem to solve, too, right? It'll just,
00:24:02.528 --> 00:24:04.798
hey, here's all the information that's available to you.
00:24:04.798 --> 00:24:08.808
And we don't have to go try to find information buried in multiple different
00:24:08.808 --> 00:24:13.558
folders and across the different modules, right? So there are going to be some
00:24:13.558 --> 00:24:17.260
workflow enhancements that are going to come out of that regardless.
00:24:18.368 --> 00:24:23.708
I just imagine this like virtual trailer where all the different agents are
00:24:23.708 --> 00:24:30.168
going to be hanging out complaining about the humans and and they're just disparate data sources like tyler,
00:24:30.708 --> 00:24:33.665
that's already happened that's moltbook dude go check that out right,
00:24:34.488 --> 00:24:38.608
but like i want moltbook for construction i would do that all day long yeah
00:24:38.608 --> 00:24:42.042
that actually would be pretty fun tyler so when When you look at,
00:24:42.928 --> 00:24:46.906
literally everyone has an agent kind of being integrated into their systems,
00:24:47.648 --> 00:24:51.469
and you've got personal agents, you've got probably project level agents.
00:24:52.508 --> 00:24:58.088
What is the future of, I guess, as a part of the architecture of project startup,
00:24:58.088 --> 00:25:03.088
is it going to be this like orchestration layer of who owns hierarchy of decision
00:25:03.088 --> 00:25:07.294
making between the agents? Like how do we have the agents all make sense?
00:25:08.054 --> 00:25:11.343
I've been noodling on this a little bit myself. I was thinking about that last
00:25:11.343 --> 00:25:16.013
night is like, we almost need a manager of all of the agents in a way, right?
00:25:16.333 --> 00:25:20.273
It's almost like a whole other project management practice that you would need
00:25:20.273 --> 00:25:25.723
to do of, you know, how do I get this AI agent to go out and do a specific task
00:25:25.723 --> 00:25:28.749
every single time and then like slap it on the hand when it doesn't work right
00:25:29.126 --> 00:25:31.173
and solve that for everybody across the board.
00:25:31.193 --> 00:25:34.113
I mean, you don't need violence, Tyler. It's not necessary. Yeah,
00:25:34.113 --> 00:25:37.533
actually that, yeah, let's not do that because when it takes over, that's going to be bad.
00:25:37.553 --> 00:25:42.543
Grokbots they'll they'll know yeah yeah hey man physically i know i'm first
00:25:42.543 --> 00:25:47.823
on the hit list for this anyway so i just accepted my fate no i was saying about
00:25:47.823 --> 00:25:52.110
this a lot so have you guys played with grokbot at all you mess with that one yet go.
00:25:53.153 --> 00:25:56.983
Like go check that out because i think it's a really interesting sort of flow
00:25:56.983 --> 00:26:03.064
and it it's similar to an open claw it's simpler or similar to a hermes type agent that you can set up,
00:26:03.611 --> 00:26:06.753
open claw and hermes are really difficult to manage though and they're not great
00:26:06.753 --> 00:26:08.603
for like an enterprise level company.
00:26:08.603 --> 00:26:11.836
It's just, it's flaky. It's got too many things going on with it.
00:26:12.418 --> 00:26:16.365
Whereas GrokBot has been like the only thing that has come out recently that's like,
00:26:16.952 --> 00:26:20.139
it does that, but it can do that at scale,
00:26:20.751 --> 00:26:25.533
for a company to where you can have your chief of staff, you could have your
00:26:25.933 --> 00:26:29.423
marketing agents all in different threads, but then you can also put them in
00:26:29.423 --> 00:26:33.029
a group chat together and they can all communicate with each other.
00:26:33.627 --> 00:26:38.468
So it's like you have all of your employees in a Slack channel and you say,
00:26:38.828 --> 00:26:42.642
hey, how are we going to handle this? And your employees can work together to figure it out.
00:26:43.195 --> 00:26:48.333
It has been one of the, I'll say it's been more eye-opening for me to step into
00:26:48.333 --> 00:26:50.058
that and go, oh, that's where we're going.
00:26:50.360 --> 00:26:52.798
It feels like that's where we're moving.
00:26:53.560 --> 00:26:57.163
And also, if you look at ChatGPT, which they are opening eye,
00:26:57.163 --> 00:27:00.840
they just announced dots, which is a very similar concept to that.
00:27:01.223 --> 00:27:03.516
So we're going to start seeing, I think.
00:27:04.279 --> 00:27:08.139
Like anthropic coming out with their own version of this, Google coming out
00:27:08.139 --> 00:27:12.509
with their version of this to where it's, it's like Slack and you,
00:27:12.509 --> 00:27:17.189
all four of us can be in that Slack channel and we can tag in agents and agents
00:27:17.189 --> 00:27:18.859
are communicating with this as we go.
00:27:19.283 --> 00:27:24.329
Right. So it's going to be like, Hey, Tom, the RFI writing agent,
00:27:24.329 --> 00:27:26.759
you know, go out and do this for me and knock it out.
00:27:26.759 --> 00:27:30.839
That's a simple workflow, but I think that's where it's moving.
00:27:30.839 --> 00:27:33.859
And that's what I was kind of curious about with autodesk is are they doing
00:27:33.859 --> 00:27:36.697
that where they're putting agents inside of a thread,
00:27:37.179 --> 00:27:42.019
and you're able to tag them in and they go out they have no idea it's mine it's
00:27:42.019 --> 00:27:46.989
my thesis or or is it just a chat based thing where it's like where did i put
00:27:46.989 --> 00:27:48.129
this and it gives you a link
00:27:48.449 --> 00:27:52.189
and it's not really an agent workflow it's it's more of like a chat gpt type
00:27:52.189 --> 00:27:53.976
of experience what did they show.
00:27:54.841 --> 00:27:58.709
Yeah i mean i think initially it is that but obviously there's different agents
00:27:58.709 --> 00:28:03.269
being built for the RFIs, for the submittals, for the schedule, right?
00:28:03.269 --> 00:28:06.799
I think it's just a matter of time until you start actually connecting that,
00:28:06.799 --> 00:28:11.279
right? Because I think where some of this agentic AI becomes interesting is
00:28:11.279 --> 00:28:14.353
when it sits on top of like disciplined information.
00:28:14.742 --> 00:28:18.079
And to your point, like the agents can actually start communicating and creating
00:28:18.079 --> 00:28:22.770
like some actual meaningful references. And so you have a powerful reasoning layer on top of those,
00:28:23.388 --> 00:28:26.800
what are some inconsistent inputs but it's maybe able to like rationalize and
00:28:26.800 --> 00:28:30.250
be still be able to give you hey at least options and then there's i think there'll
00:28:30.250 --> 00:28:34.429
still be a human in the loop to make a decision i think that's just uh yeah,
00:28:34.911 --> 00:28:37.810
gonna have to be part of the workflow i think so,
00:28:38.390 --> 00:28:42.050
a workflow and i'll use this just in my personal life because i i play with
00:28:42.050 --> 00:28:45.546
these things on the personal side before i start deploying them into you know work
00:28:45.969 --> 00:28:52.170
and so like for grok i set it up and i have my assistant i say every two weeks
00:28:52.170 --> 00:28:54.994
i want you to look and see if i've got a haircut on the calendar,
00:28:55.540 --> 00:28:58.670
and if i don't have a haircut on the calendar i want you to go to this website
00:28:58.670 --> 00:29:05.230
for my barber book a time haircut every two weeks tyler every three you're barbed so but it it looks,
00:29:06.627 --> 00:29:09.570
it looks on a routine this is more revealing.
00:29:12.705 --> 00:29:17.410
Yeah so it it looks on a routine though and it will it will go to my calendar
00:29:17.410 --> 00:29:21.770
see if i've got two haircuts minimum on the calendar if the second one is not
00:29:21.770 --> 00:29:26.578
there it will go out of its way to book that haircut for me at a certain time that i've specified
00:29:26.927 --> 00:29:32.290
and it does that consistently it's always there it's always working so i have not had to
00:29:32.690 --> 00:29:38.010
physically go and book a hair appointment with Alejandro in weeks. Alejandro.
00:29:38.530 --> 00:29:41.910
Yeah. There we go. A little shout out. We'll put his link in the show notes.
00:29:42.650 --> 00:29:47.700
Alejandro, dark parlor, baby. Let's go. I go to him because he just like gives
00:29:47.700 --> 00:29:50.592
me all sorts of crap every time I go. And it feels like, I don't know.
00:29:50.749 --> 00:29:52.398
It feels like I get to hang out with Eddie.
00:29:53.350 --> 00:29:56.456
Yeah. Right. Aaron, how many haircuts a month do you get?
00:29:57.071 --> 00:30:00.250
I don't know. But when I forget, Lloyd texts me and says, yo,
00:30:00.250 --> 00:30:04.043
man, I haven't seen you in a bit. You want to swing by? You're like, your guy's Lloyd?
00:30:04.647 --> 00:30:10.231
That sounds like a barber. Lloyd's great. Lloyd's got a barber tattoo here. Rides a motorcycle.
00:30:10.836 --> 00:30:16.890
Plays in Blue Man. He does not have a website. And Lloyd is chatting.
00:30:17.430 --> 00:30:18.505
Our barbers are very different.
00:30:19.197 --> 00:30:24.215
Yeah yeah and i don't have enough hair left to be able to justify it yeah yeah yeah yeah.
00:30:27.535 --> 00:30:30.545
I'm showing off my fade over here you know you gotta do that was a good day
00:30:30.545 --> 00:30:32.897
i'm not gonna lie no he did great he did it's,
00:30:34.633 --> 00:30:37.395
clean yeah did you find him on instagram no
00:30:37.835 --> 00:30:41.815
no no those clips and you were like so no i drove i drove past i drove past
00:30:41.815 --> 00:30:44.825
it was like on my way to church or something i was like i stopped by there then
00:30:44.825 --> 00:30:47.505
i've been going there ever since it's great so i love it but Yeah,
00:30:47.505 --> 00:30:50.935
they have a website with a little like booking page. It knows.
00:30:51.295 --> 00:30:53.355
So it has computer use inside too.
00:30:53.802 --> 00:30:59.415
So GrokBot uses a computer that is built into it to go to the page,
00:30:59.415 --> 00:31:03.015
navigate, click through all the buttons, book it. Do you arm it with all your
00:31:03.015 --> 00:31:05.452
sign-in information already? It doesn't have.
00:31:05.818 --> 00:31:08.555
That one doesn't have sign-in information because like you don't need to sign
00:31:08.555 --> 00:31:11.565
in to book a time. Yeah, you just sign up. It's like a calendar sort of link
00:31:11.565 --> 00:31:13.684
where you just. I would arm it with a name.
00:31:14.320 --> 00:31:16.955
Huh? That's all I need. You armed it with your name. Oh.
00:31:17.455 --> 00:31:22.735
And even more fun too is that I had an issue, like a clash with when it was
00:31:22.735 --> 00:31:25.291
scheduled and I said, hey, go change the time.
00:31:25.854 --> 00:31:29.245
And it went and rescheduled it for me. I didn't have to tell it to do anything
00:31:29.245 --> 00:31:32.396
specific. It
just, it knew where to go and how to get that done.
00:31:32.739 --> 00:31:37.075
So I say all that to illustrate, I feel like those are the types of things that
00:31:37.075 --> 00:31:40.915
will be, like they're already possible, but we'll start seeing more of that
00:31:40.915 --> 00:31:45.255
type of workflow within construction over the coming months. Those are low-hungry.
00:31:45.375 --> 00:31:50.124
For task automation, workflow automation. I think we're still a little bit maybe,
00:31:50.727 --> 00:31:54.565
like predictive analysis is still a little bit further out. But I mean,
00:31:54.565 --> 00:31:56.317
these kind of assistants, I think we're...
00:31:57.136 --> 00:32:00.130
You know getting a bit proposal agents i mean you're going to see a bunch of
00:32:00.130 --> 00:32:04.960
agents getting built into the different work that's where i think like aaron
00:32:04.960 --> 00:32:10.440
from a vc standpoint i think like cash why are you laughing i'm just having
00:32:10.440 --> 00:32:12.030
nightmares of role level permissioning.
00:32:13.390 --> 00:32:16.710
Right we're role level permissioning agents and i'm like well remember that's
00:32:16.710 --> 00:32:21.380
where i think the money needs to go which is like some kind of like no no like
00:32:21.380 --> 00:32:24.898
like an orchestration layer like Someone needs to build the orchestration layer
00:32:25.212 --> 00:32:29.032
that can be customizable and modular to
00:32:29.432 --> 00:32:32.190
programs, to domains, to all this stuff.
00:32:32.190 --> 00:32:35.360
To be fair, though, I think a lot of the big guys are already starting to build
00:32:35.360 --> 00:32:37.850
those orchestration layers. So I don't think this needs to be some third part.
00:32:37.990 --> 00:32:40.190
You're saying I don't have a billion-dollar idea, Tyler?
00:32:40.590 --> 00:32:43.797
No, I'm saying somebody's already working on it, Steve.
00:32:44.697 --> 00:32:46.717
Another idea killed by Tyler. I'll shut up now.
00:32:48.990 --> 00:32:53.880
Are you seeing are you seeing ideas around that come your way and get pitched to you aaron,
00:32:55.050 --> 00:32:58.551
for what how to run role level permission across multiple agents,
00:32:59.373 --> 00:33:04.370
maybe you make it sound so basic but that does sound like a cool idea no yeah
00:33:04.370 --> 00:33:08.089
i mean we see it all like yeah totally but you know,
00:33:08.681 --> 00:33:12.150
ultimately you also have to know like what is this guy supposed to do within
00:33:12.150 --> 00:33:16.510
my company so like it's not it's not like a easy button at all ever yeah,
00:33:17.110 --> 00:33:19.681
anywhere so that's fair.
00:33:20.809 --> 00:33:23.996
All right two questions on this then we got to go to the next one um let's do it,
00:33:24.685 --> 00:33:34.636
hanu and aaron what is like is there any examples of the use of agents within your companies,
00:33:35.292 --> 00:33:42.867
that has been interesting that you guys are either a part of or
just maybe seeing hanu go.
00:33:43.587 --> 00:33:48.178
Yeah no i think one of their i mean obviously we we're starting to get better
00:33:48.178 --> 00:33:52.608
at organizing our information and We've got an incredible amount of like historical
00:33:52.608 --> 00:33:56.247
information around schedules, around cost,
00:33:56.765 --> 00:33:58.648
subcontractors that we work with.
00:33:58.648 --> 00:34:01.238
I think probably one of the coolest things we're doing internally,
00:34:01.238 --> 00:34:06.108
aside from like predicting like our resources and allocation of resources on jobs.
00:34:06.108 --> 00:34:09.815
But the other one is probably just being able to look at the different,
00:34:10.511 --> 00:34:16.598
subs and propose subcontractors for our projects based on their past performance,
00:34:16.598 --> 00:34:20.110
their availability, how many projects they're on across our different,
00:34:20.755 --> 00:34:22.048
you know, national network.
00:34:22.048 --> 00:34:25.918
So I think those are like really like practical, simple examples.
00:34:25.918 --> 00:34:30.448
But, you know, I think those are leveraging our own data essentially for to
00:34:30.448 --> 00:34:35.157
be able to, you know, either hopefully create more predictable results,
00:34:35.633 --> 00:34:38.538
understand what you're signing up for, understanding where you have risk.
00:34:38.538 --> 00:34:40.672
I think those are some good use cases.
00:34:41.391 --> 00:34:47.320
I like that. Aaron? Do you want it within my venture practice or do you want it within a startup?
00:34:47.667 --> 00:34:50.332
No, on the venture side, let's see what you guys are doing.
00:34:50.978 --> 00:34:56.118
Cool, right? So the Java venture is very much like sales and decision-making,
00:34:56.118 --> 00:34:58.808
I would say, is the two anchors.
00:34:59.449 --> 00:35:06.458
And agents are killer at sales stuff. So of our new opportunity pipeline...
00:35:07.486 --> 00:35:13.601
Half of it comes from personal relationships and referrals, meaning like founders, friends, et cetera.
00:35:14.333 --> 00:35:19.772
10% of it comes from outbound and the remaining 40% comes from other investors,
00:35:19.772 --> 00:35:21.067
particularly lead investors.
00:35:21.669 --> 00:35:25.442
And so we thought really hard about how do you maintain your relationships with
00:35:25.442 --> 00:35:26.632
your co-investor network?
00:35:27.277 --> 00:35:31.202
And we use Affinity as our CRM.
00:35:31.591 --> 00:35:39.112
So how do you help build a simple cloud project in order to link to affinity
00:35:39.432 --> 00:35:40.772
and help me create an email?
00:35:40.772 --> 00:35:45.882
So whenever I go talk with one of our co-investors, I know what they like to
00:35:45.882 --> 00:35:50.272
invest in and I can go through my affinity and say, here are the things I think align best.
00:35:50.690 --> 00:35:55.514
And it like automates a lot of that relationship management perspectives.
00:35:55.665 --> 00:36:00.651
And that sounds a lot like an SDR function at a lot of startups or a lot of people just generally.
00:36:01.150 --> 00:36:06.915
And so it's been really useful to make sure we have depth in all of our connections
00:36:07.246 --> 00:36:10.659
that is current against our kind of currency of deal flow.
00:36:11.403 --> 00:36:15.090
Yeah, that's cool. We're good. Agents in the wild.
00:36:15.462 --> 00:36:20.742
Tyler, I share a couple of them. So we actually just got done working and deploying
00:36:20.742 --> 00:36:25.223
these out into one of my clients, level five cost estimation.
00:36:25.501 --> 00:36:30.272
So we can run a level five cost estimate through their company off of their
00:36:30.272 --> 00:36:33.948
historical benchmarking for all of the data center projects that they have worked on.
00:36:34.645 --> 00:36:36.467
Are the levels based on complexity?
00:36:37.412 --> 00:36:40.172
Yes, based off of complexity. So level five is super high level.
00:36:40.172 --> 00:36:42.366
So we're moving, building towards class four.
00:36:43.652 --> 00:36:47.469
So four, three, two, one, et cetera. One is super, super dialed.
00:36:48.331 --> 00:36:53.092
The other one is bid ingestion. So get bids from vendors.
00:36:53.392 --> 00:36:57.381
We can ingest that information and then we can do the leveling of said bids
00:36:57.770 --> 00:36:59.232
all within that process.
00:36:59.232 --> 00:37:03.982
So like, but that's all, it's all a workflow and we're injecting the agents
00:37:03.982 --> 00:37:08.992
in where it makes sense for them to do the work versus having a deterministic type of work.
00:37:10.125 --> 00:37:13.879
Architecture where it makes sense there too so i mean you sometimes it doesn't
00:37:13.879 --> 00:37:17.777
make sense to burn the tokens you know there's there's there could be too much variance,
00:37:18.626 --> 00:37:23.026
but yeah those are other examples i mean things we just token strategy is increasingly,
00:37:23.499 --> 00:37:27.374
a relevant conversation so and most strategic conversations go ahead i just
00:37:27.554 --> 00:37:31.649
i just came back from yada out in vegas so i came out from i didn't go to au
00:37:31.649 --> 00:37:35.339
but i did go to yada and i was standing in line talking to a guy at a,
00:37:36.199 --> 00:37:42.029
super large company he's cio over there i was like so like tell me about your
00:37:42.029 --> 00:37:43.986
usage of ai and he was like,
00:37:44.648 --> 00:37:48.269
he was kind of venting for a moment and then he told me about this bill that
00:37:48.269 --> 00:37:53.079
they got he was like yeah so one of our people burned eleven thousand dollars
00:37:53.079 --> 00:37:54.747
worth of tokens in a month,
00:37:55.341 --> 00:37:59.979
dude legend i'm like okay well what did they do and he's like they built a bunch
00:37:59.979 --> 00:38:02.144
of agents that didn't actually work.
00:38:03.530 --> 00:38:06.239
So I think that the return on investment
00:38:06.239 --> 00:38:10.089
conversation is going to start happening up the chain of command.
00:38:10.089 --> 00:38:15.039
It has to, right? So I mean, if we're burning $11,000 worth of tokens and I
00:38:15.039 --> 00:38:19.849
make $100,000, great. But if I'm burning $11,000 and I have nothing to show
00:38:19.849 --> 00:38:24.199
for it and everybody's doing it, we've got a really big problem on our hands.
00:38:24.559 --> 00:38:29.559
So I think there's, yes, token strategy and how we let certain people do certain
00:38:29.559 --> 00:38:31.540
things. We've got to have those conversations.
00:38:33.716 --> 00:38:38.052
All right. So let's move from the digital to the physical.
00:38:38.759 --> 00:38:43.169
We're building a few data centers in the U.S. these days. And there's one in
00:38:43.169 --> 00:38:49.129
particular in New Jersey that had some issue with using some natural gas-based
00:38:49.129 --> 00:38:51.115
generators that were unpermitted.
00:38:51.759 --> 00:38:57.399
They were fined a million dollars and allowed what looks like six weeks to get
00:38:57.399 --> 00:39:00.903
permits in place while they kind of continued operation.
00:39:01.466 --> 00:39:06.247
So, you know, I was on a panel this week at the Rice University kind of talking through.
00:39:07.513 --> 00:39:11.958
Power constraints as it relates to these, just the demand for data centers.
00:39:12.298 --> 00:39:14.748
And I think the average time right
00:39:14.748 --> 00:39:19.835
now from kind of idea to completion of Interconnect is like five years.
00:39:20.387 --> 00:39:25.628
And so increasingly, everyone's kind of thinking through their bridging strategy that relates to power.
00:39:26.146 --> 00:39:29.222
And generators are a big component of that.
00:39:30.041 --> 00:39:33.098
Do we feel like this is an.
00:39:33.948 --> 00:39:41.158
Instance and a trend towards maybe municipalities feeling empowered to kind
00:39:41.158 --> 00:39:45.634
of maybe insure and protect their citizenry?
00:39:45.761 --> 00:39:52.108
Or is a million dollars on a 15 plus billion dollar contract maybe more evidence
00:39:52.108 --> 00:39:54.212
that data centers still have the power?
00:39:54.862 --> 00:39:57.548
I guess I don't really know where there's a question there, but I think it's
00:39:57.548 --> 00:40:03.298
an interesting trend where, hey, the industry and the owner side is starting
00:40:03.298 --> 00:40:06.338
to feel the effects of the constraints of power.
00:40:06.855 --> 00:40:16.212
And are we going to see more of this kind of fining for what is,
00:40:16.514 --> 00:40:19.218
I mean, I'm sure this happens in more places than one.
00:40:19.218 --> 00:40:23.138
I think reading into the story, it sounds like they only really found out of
00:40:23.138 --> 00:40:29.401
this because local residents were complaining of the noise and filed some complaints.
00:40:29.819 --> 00:40:32.850
So, I don't know. There's a question there somewhere.
00:40:33.553 --> 00:40:37.088
Aaron, there's a lot of data
centers being built. Do you feel,
00:40:37.088 --> 00:40:43.178
do you see some pressures at a municipal level to kind of get more active in
00:40:43.178 --> 00:40:45.344
pushing you back against development?
00:40:45.907 --> 00:40:49.338
Or is there an understanding that, hey, we all need data centers like China's
00:40:49.338 --> 00:40:53.335
a variable. What's, what are you, what are you seeing in the corners of, of your world?
00:40:53.959 --> 00:40:55.803
Yeah, look, like.
00:40:56.976 --> 00:41:02.976
The international competitiveness question is great irisorily,
00:41:02.976 --> 00:41:04.742
but sucks when it's in your backyard.
00:41:05.079 --> 00:41:08.556
So I don't think local municipalities are like, oh, this is cool because we
00:41:08.556 --> 00:41:09.769
got to be competitive, right?
00:41:10.994 --> 00:41:15.486
But all developments require a public and private partnership,
00:41:15.486 --> 00:41:17.284
right? It doesn't matter what you're building.
00:41:18.002 --> 00:41:24.086
Again, the city has to see a fair exchange of value for the ultimate resource
00:41:24.086 --> 00:41:30.918
impact, whether that's air quality or resource use or noise or whatever, to their citizens.
00:41:31.720 --> 00:41:35.076
And right now, I think that those asks are going in one direction,
00:41:35.076 --> 00:41:38.696
which is higher, right? You know, data centers make a ton of money from the
00:41:38.696 --> 00:41:40.107
ultimate sale of compute.
00:41:40.695 --> 00:41:45.336
And so there's like, you know, a more comprehensive thoughtfulness from a lot
00:41:45.336 --> 00:41:48.796
of local municipalities to say, like, what's our what's our condos left that
00:41:48.796 --> 00:41:51.578
makes this an equal trade to be located here?
00:41:52.090 --> 00:41:55.136
I don't know how that's going to differentiate between geography.
00:41:55.136 --> 00:41:58.576
The United States is this collection of people that like have really different
00:41:58.576 --> 00:41:59.664
opinions about these things.
00:42:00.136 --> 00:42:04.726
And like those opinions may start to have like stronger competitiveness in rural
00:42:04.726 --> 00:42:08.666
areas and certain parts of the country and not in other parts of countries,
00:42:08.666 --> 00:42:10.793
even though they both might look the same on a map.
00:42:11.069 --> 00:42:15.336
And so my intuition is this is going to have like a really widespread of opinion
00:42:15.336 --> 00:42:20.856
and a really widespread of action as a voter and as a citizen,
00:42:20.856 --> 00:42:22.863
I'm more concerned about like illegally.
00:42:23.674 --> 00:42:28.918
Like driven wells, right? A groundwater use is not as big of a deal today as
00:42:28.918 --> 00:42:35.778
it was historically, but like, you know, I'm sure that the rules have been bent around groundwater.
00:42:35.778 --> 00:42:36.978
And like, that's the one that is
00:42:36.978 --> 00:42:40.388
like, you know, really, really limited resources, especially in the West.
00:42:41.188 --> 00:42:44.918
And so like, that's going to be, I think that's going to be a hotter button
00:42:44.918 --> 00:42:48.533
issue here as, as a policy group reviews it.
00:42:49.668 --> 00:42:53.057
Yeah. Yeah. I mean, obviously there's a lot of,
00:42:53.803 --> 00:42:57.538
A lot of controversy around these things, around data centers at the moment,
00:42:57.538 --> 00:43:00.458
but I think you can't solve, like in this particular example,
00:43:00.458 --> 00:43:04.698
you can't solve like a utility or permitting problem by just making a construction
00:43:04.698 --> 00:43:06.138
schedule more aggressive, right?
00:43:06.138 --> 00:43:09.268
So we have to plan for these things well ahead of time.
00:43:09.268 --> 00:43:12.998
Like the data centers, they're not just construction projects anymore.
00:43:12.998 --> 00:43:18.368
They're energy infrastructure projects that happen to have really large buildings around them, right?
00:43:18.368 --> 00:43:22.838
So conversations kind of used to be as can we build, how fast can we build a
00:43:22.838 --> 00:43:26.528
facility? It's increasingly becoming about can we get the power,
00:43:26.528 --> 00:43:30.753
equipment, supply chain challenges, labor, obviously permitting.
00:43:31.223 --> 00:43:34.828
And like, how do we align and plan for all of that in order for that to be,
00:43:35.409 --> 00:43:37.255
you know, a smooth process?
00:43:37.859 --> 00:43:41.660
And yes, to Aaron, your point, it's a partnership.
00:43:42.066 --> 00:43:46.478
It's a communication planning problem that hopefully we can all kind of figure
00:43:46.478 --> 00:43:49.368
out how to solve. But I mean, the demand isn't going anywhere,
00:43:49.368 --> 00:43:51.508
right? I mean, I think that's just the reality.
00:43:51.854 --> 00:43:57.288
I think we're kind of in this weird midterms cycle right now where there's just
00:43:57.288 --> 00:44:00.868
a lot of information and misinformation out there.
00:44:00.868 --> 00:44:04.188
But I think it's for our industry to solve some of these problems.
00:44:04.188 --> 00:44:07.888
I mean, we have to figure out how we build these things smarter and more sustainably.
00:44:08.648 --> 00:44:13.378
And figure out how we can at least get the facts out there around this stuff.
00:44:13.378 --> 00:44:19.478
Because, yes, they consume a lot of power, but right now, I think the projection
00:44:19.478 --> 00:44:24.408
is that even by 2028, it's going to be equivalent to anywhere like 6% to 12%
00:44:24.408 --> 00:44:27.554
of total U.S. electricity consumption. So it's not like.
00:44:28.445 --> 00:44:33.473
You know, the data centers are evil and bad. It's just making sure the communication
00:44:33.473 --> 00:44:36.853
is clear and, you know, we follow the right rules. And obviously,
00:44:36.853 --> 00:44:38.800
permitting process is part of that.
00:44:40.233 --> 00:44:44.413
First of all, I would like to say I'm shocked because everything is legal in
00:44:44.413 -->
00:44:46.693
New Jersey. According to Hamilton.
00:44:47.813 --> 00:44:50.213
Okay. That was a low blow. Low blow.
00:44:52.053 --> 00:44:55.179
Hey, hey, hey. This is a Hamilton reference. Just back off.
00:44:55.452 --> 00:45:00.883
All right. So, I mean, a million dollars is kind of like a little gnat flying
00:45:00.883 --> 00:45:05.228
around your head if you're a data center, like a $17 billion project.
00:45:05.512 --> 00:45:12.333
Like, who gives a crap at that point? And I think what's funny is that a lot
00:45:12.333 --> 00:45:16.173
of these companies would like you to believe that this is a partnership between
00:45:16.173 --> 00:45:17.703
the community and the data center.
00:45:17.703 --> 00:45:22.553
No, it's not. This is, we are going to bribe the ever-living crap out of you
00:45:22.553 --> 00:45:26.254
to get this thing built because we're going to make a crap load of money off of this.
00:45:26.760 --> 00:45:31.600
And that was one of the eye-opening things of conversations that I was even seeing in the last week.
00:45:31.860 --> 00:45:37.873
There are people that are dedicated to community engagement for data centers.
00:45:37.873 --> 00:45:43.533
They go in and they talk to the community and they try to share information
00:45:43.533 --> 00:45:45.577
about what's going to be happening at data centers.
00:45:45.810 --> 00:45:50.693
But also, if there is a protest, they will organize a counter protest against
00:45:50.693 --> 00:45:55.005
that. So it starts to get pretty freaking interesting when you start getting into this world.
00:45:55.417 --> 00:45:59.833
Like that was kind of mind blowing for me when I when I sit down at lunch and
00:45:59.833 --> 00:46:03.323
I'm like, what do you do? And that comes up like, wait a minute.
00:46:03.913 --> 00:46:09.013
Stop. Really? That's what you do for a living. So I like.
00:46:10.071 --> 00:46:13.301
I tend to think it's like, yeah, OK, congratulations. You got a million dollars
00:46:13.301 --> 00:46:17.571
out of it, New Jersey. But I mean, they're going to pay you whatever it takes
00:46:17.571 --> 00:46:19.385
to get you to go away so they can build this.
00:46:19.872 --> 00:46:26.117
And I mean, but again, I do agree that it's like, what's going to happen to the midterms?
00:46:26.552 --> 00:46:30.581
Because I think that at a certain point, we will start seeing some people get
00:46:30.581 --> 00:46:33.275
more and more emboldened to go out of their way to say, nope,
00:46:33.611 --> 00:46:35.231
it's going to be more than a million dollars.
00:46:35.678 --> 00:46:37.491
And that's kind of got me worried right
00:46:37.491 --> 00:46:40.911
now. Well, again, this is outside perspective. That's got me worried.
00:46:41.351 --> 00:46:46.766
What's going to happen if a lot of these projects start getting shut down because
00:46:47.131 --> 00:46:53.203
there are people that are newly elected into office want to start making a showing of, you know.
00:46:53.871 --> 00:46:59.161
I mean, I've made the point before, and Aaron, you know, interested in your perspective here.
00:46:59.161 --> 00:47:04.411
But I think from a macro standpoint, so much of our, you know,
00:47:04.411 --> 00:47:10.419
economic output and activity is based on kind of the large category of AI CapEx. And so.
00:47:12.631 --> 00:47:17.401
Between that and federal spending, that is the economy. And so I think when
00:47:17.401 --> 00:47:21.881
you talk about demand, Hanu, I think what's interesting is we are all using
00:47:21.881 --> 00:47:24.424
the tools, but we also, none of us,
00:47:25.034 --> 00:47:29.057
according to studies, 70% of us don't want data centers in our, in our counties.
00:47:29.475 --> 00:47:32.127
And so we all, we all want the tools. We don't want the tools,
00:47:32.533 --> 00:47:35.697
like the infrastructure behind the tools by us, which I think is fair.
00:47:36.016 --> 00:47:39.923
So I think it does come down to like community alignment from a incentive standpoint.
00:47:40.851 --> 00:47:45.331
You know, Andrew Yang, the former political or presidential candidate,
00:47:45.331 --> 00:47:54.095
went to Harvard and gave a speech and essentially armed the recent grads at Harvard with the...
00:47:54.851 --> 00:48:01.324
Like ethos that the battle of their generation is to defeat AI,
00:48:01.664 --> 00:48:06.124
using his words, and talked about how AI is not their friend.
00:48:06.124 --> 00:48:08.624
It's not going to make their life better.
00:48:09.089 --> 00:48:15.214
And it got a huge round of applause. And so there's a lot of interesting kind
00:48:15.214 --> 00:48:16.991
of inputs, obviously interesting time.
00:48:17.340 --> 00:48:21.628
But on the macro side of this, Aaron, if data centers go away, what happens?
00:48:22.804 --> 00:48:27.246
Well, first of all, the bet is too big for them to go away. We're like...
00:48:27.826 --> 00:48:32.685
You know what I mean? That ship is sailing. So...
00:48:34.070 --> 00:48:37.705
I, I, I'll bring this back to like a first principle of American culture, right?
00:48:38.078 --> 00:48:44.350
Like a big part of American culture is like, we're not super happy when someone
00:48:44.350 --> 00:48:46.854
does something without asking our opinion, right?
00:48:47.086 --> 00:48:51.330
We love to vote. We, you know, we became a country because we didn't love people
00:48:51.330 --> 00:48:53.551
just arbitrarily taxing the shit out of us.
00:48:54.132 --> 00:48:58.775
And so I think there's this piece that I tried to make a point earlier,
00:48:59.211 --> 00:49:05.760
which is each community is going to have an opinion very locally that matters
00:49:05.760 --> 00:49:07.380
to its citizens most locally.
00:49:07.380 --> 00:49:13.734
And this is the wonder of the American governmental system, is most power is your exact community.
00:49:14.152 --> 00:49:17.230
And the layers of government above that, right, county, state,
00:49:17.230 --> 00:49:22.349
federal, have decreasing amount of
influence on what is your day life on any given Tuesday.
00:49:22.964 --> 00:49:26.750
But your local community really impacts what your life is like on any given
00:49:26.750 --> 00:49:30.391
Tuesday. And so I think there's going to be a spread of opinion for that.
00:49:30.989 --> 00:49:37.210
And I think that the folks that advocate for it to happen in their community
00:49:37.210 --> 00:49:40.570
to have a data center, because it fits their.
00:49:41.403 --> 00:49:45.360
Approach to zoning, their approach to economic development, their approach to
00:49:45.360 --> 00:49:49.160
employment, are going to benefit from whatever the, you know,
00:49:49.160 --> 00:49:50.900
as Tyler so eloquently put it,
00:49:51.417 --> 00:49:54.944
incentives that they come with having it locally.
00:49:55.531 --> 00:50:00.558
And I think that mutual agreement between a local community and a developer,
00:50:01.098 --> 00:50:06.977
is the ethos to this but just blanketing our country with these without having that back and forth,
00:50:07.569 --> 00:50:10.535
is counterculture to a lot of what
00:50:10.965 --> 00:50:15.450
regardless if you're left or right kind of view of like the american approach
00:50:15.450 --> 00:50:19.860
to development which is like very much we have to agree to let you be in our
00:50:19.860 --> 00:50:24.646
backyard and so that's my intuition is you're going to see a very big spread on who says yes.
00:50:25.268 --> 00:50:28.650
Yeah, but it starts with people being able to actually get in the same room
00:50:28.650 --> 00:50:33.680
and talk about facts, right? And like really agree on what's real and what's not real. And,
00:50:34.475 --> 00:50:39.551
Hopefully, I come to some kind of an understanding that there are obviously
00:50:39.551 --> 00:50:43.901
benefits to the community, but then there are the right ways and wrong ways
00:50:43.901 --> 00:50:45.421
of building these things too, right?
00:50:45.421 --> 00:50:50.921
So we are lucky to work with a lot of clients that are taking a much more long-term
00:50:50.921 --> 00:50:53.965
view and sustainable approach to these buildings.
00:50:54.377 --> 00:50:57.929
And they are working with the communities and doing a lot of good things for the community.
00:50:58.469 --> 00:51:02.451
And genuinely doing that because they actually do care.
00:51:02.451 --> 00:51:07.281
Obviously they have incentives to build these things but you know aaron i think
00:51:07.281 --> 00:51:08.661
to your point earlier i mean these.
00:51:09.781 --> 00:51:12.852
Demand isn't going away ai is not going away and,
00:51:13.457 --> 00:51:17.941
you know i think the reality is is that this is the new new revolution of our
00:51:17.941 --> 00:51:23.441
age our time and yeah the the way we do work now from where it's going to be
00:51:23.441 --> 00:51:25.856
five ten years from now it's going to be quite different.
00:51:28.371 --> 00:51:33.841
I think that the interesting thing, if we were to zoom out, is I think
that,
00:51:34.541 --> 00:51:39.661
if we were to bifurcate and categorize AI as like the narrow use case,
00:51:40.461 --> 00:51:44.939
the narrow model trained versus like AGI in the pursuit of AI.
00:51:45.948 --> 00:51:52.179
Like the most utility, most of the utility that you and I and a majority of,
00:51:52.179 --> 00:52:00.491
I would say, the population can be had from open source, non-frontier models, AI.
00:52:00.990 --> 00:52:05.409
And yet, and so I think there is a question that I haven't heard a good answer
00:52:05.409 --> 00:52:14.478
on of other than like, we can't lose to China, of why the pursuit of large AGI?
00:52:15.099 --> 00:52:20.689
Which in theory, if they're telling us that it's going to take most of the jobs,
00:52:20.689 --> 00:52:22.402
doesn't serve the citizenry.
00:52:23.244 --> 00:52:32.594
And yet narrowly trained models do, what is the benefit of the pursuit of AGI to the population?
00:52:33.035 --> 00:52:36.299
You know, taking that question like head on, which is like the dumbest shit
00:52:36.299 --> 00:52:39.791
I've done in a while, is, you know, I...
00:52:40.572 --> 00:52:45.216
I think there's three reasons. One is frontier models, you know,
00:52:45.216 --> 00:52:49.896
have evidenced the best results from deep academic research, right?
00:52:49.896 --> 00:52:57.516
So, like, how do you, like, create a new GMO-modified corn or wheat or whatever
00:52:57.516 --> 00:53:03.355
that could potentially be planted in arid environments and solve starvation?
00:53:03.848 --> 00:53:09.563
You know, like, that is found on a frontier model, not on a desktop model, you know?
00:53:10.068 --> 00:53:15.226
And so you get like a new corn but potentially maybe like all the banks are
00:53:15.226 --> 00:53:17.236
hacked right like there's also risk on,
00:53:17.716 --> 00:53:22.414
the oh oh my god like totally like we're building in my fair city like you know
00:53:22.722 --> 00:53:27.496
the biggest installation of quantum computing right and like yeah this is like
00:53:27.496 --> 00:53:32.262
a ball of string that i do not want to unravel and you know it's it's,
00:53:32.916 --> 00:53:35.768
i'm trying to argue the upside here versus It's just the downside.
00:53:36.796 --> 00:53:40.786
But on the flip side of that, though, Aaron, it's like if we took all of the
00:53:40.786 --> 00:53:43.856
money we're investing in data centers and actually went out and bought food
00:53:43.856 --> 00:53:46.796
for everybody, then, oh, my God, we just solved world hunger.
00:53:47.616 --> 00:53:50.643
So it's like we're building AI so we can solve world hunger.
00:53:51.269 --> 00:53:55.376
What the frick, man? We just go solve world hunger with the money that we're spending on this crap.
00:53:55.776 --> 00:54:00.606
So it's a little bit of a balance. So could Elon personal, you know? Right. Exactly.
00:54:01.296 --> 00:54:06.226
Exactly. So this isn't this isn't for for any sort of generosity sake here.
00:54:06.226 --> 00:54:07.320
Let's not kid ourselves.
00:54:07.575 --> 00:54:14.346
This is for money, money. That's it. This is the key, the key to a good conversation
00:54:14.346 --> 00:54:16.876
is to open the can of worms right before the end of it, you know.
00:54:18.076 --> 00:54:19.469
And have to have to cap it.
00:54:20.576 --> 00:54:23.956
I think I would love to have a conversation just about this because I don't,
00:54:23.956 --> 00:54:25.681
I don't think we're like, we could stop.
00:54:25.814 --> 00:54:30.458
Like we could not build the thing we think is going to take all the jobs from our kids.
00:54:30.592 --> 00:54:35.036
And, and yet, like, there is a nuanced way of having that conversation yet.
00:54:35.036 --> 00:54:40.006
And I don't think it's, you know, I'm not saying we need to stop building everything.
00:54:40.006 --> 00:54:41.679
But there is a there's a nuance there.
00:54:42.004 --> 00:54:44.116
The one thing I want to get a take on before we go is,
00:54:45.037 --> 00:54:48.119
Caterpillar, one of the largest kind of equipment manufacturers,
00:54:48.578 --> 00:54:53.979
is partnering with Field AI, which is essentially building kind of the brain behind robotics.
00:54:55.061 --> 00:54:58.791
And if you look at some of the other raises that have happened in the last few
00:54:58.791 --> 00:55:04.101
months, there's definitely money coming into, and it seems like the frontier
00:55:04.441 --> 00:55:08.169
of equipment getting smarter and autonomous is maybe here.
00:55:09.019 --> 00:55:15.301
Hanu, what are you seeing on the GC side? Are you seeing heavy civil contractors
00:55:15.301 --> 00:55:18.504
come with an autonomous plan for projects yet?
00:55:19.260 --> 00:55:23.962
We haven't seen that yet. I mean, the physical AI is pretty interesting, but...
00:55:25.205 --> 00:55:29.085
When we're looking about it in the context of robots and gadgets.
00:55:31.758 --> 00:55:37.655
It's starting to supplement some workflows, but I think we're still pretty far
00:55:37.655 --> 00:55:42.845
from fully autonomous workflows. It's a workflow standardization problem.
00:55:43.905 --> 00:55:48.155
We've had that for ages. How do you make a construction site like a manufacturing
00:55:48.155 --> 00:55:50.065
process? Yeah, these sites are semi-variable.
00:55:50.785 --> 00:55:54.485
Yeah, and there's a lot of... Well, they're not the same.
00:55:54.485 --> 00:56:00.049
And all the same and it's not a there's a lot of volatility in all sorts of things so,
00:56:00.676 --> 00:56:05.565
you know i think construction autonomy i guess just isn't it won't be just an
00:56:05.565 --> 00:56:09.445
ai problem i think we need to be able to figure out how we can get more consistent
00:56:09.445 --> 00:56:11.516
with construction make it more predictable,
00:56:12.213 --> 00:56:16.285
maybe more modular i mean i think we're trending in that direction and that's
00:56:16.285 --> 00:56:20.205
where we can hopefully maybe introduce some of these solutions that,
00:56:21.273 --> 00:56:26.425
are become part of our production system yeah good stuff well we're out of time
00:56:26.765 --> 00:56:33.001
guys appreciate you hopping on this has been fun yeah it's been a good conversation alright guys,
00:56:33.770 --> 00:56:38.005
we're in the age of AI man computers we thought computers were going to take
00:56:38.005 --> 00:56:42.565
all of our jobs right but here we still are on the next episode we're going to talk about,
00:56:43.348 --> 00:56:45.002
256 encryption,
00:56:46.345 --> 00:56:49.737
yeah just get into quantum alright you guys.