Engineering's Spatial AI Moment — Campfire & Gravity Sketch

Episode Summary

What happens when virtual reality, spatial computing, and AI stop being demos and start becoming real engineering workflows? In this episode of AI Across the Product Lifecycle, Michael Finocchiaro speaks with Jay Wright, co-founder and CEO of Campfire, and Oluwaseyi "Shay" Sosanya, co-founder and CEO of Gravity Sketch, about where immersive technology is actually delivering value in design, engineering, manufacturing, and collaboration. This is not another "metaverse" hype conversation.

Jay and Shay explain why spatial tools are starting to feel less like experimental VR and more like the next interface for product development. The discussion covers AI agents inside 3D environments, why geometry is still hard for LLMs, how startups are moving faster than legacy engineering software vendors, and why the real breakthrough may come when engineers can move from idea to manufacturable product faster than ever. Key themes include AI-assisted software development, immersive collaboration, design-to-manufacturing handoffs, digital maturity, IP and security concerns, and what young engineers should learn now to stay relevant in the AI era.

For PLM and engineering professionals, the episode underscores how spatial AI is starting to reshape the front end of product development — but emphasizes that workflow integration, IP protection, and human-first interaction design will determine which tools become production substrate versus which remain demos. Both founders argue that startups can compress the design-to-manufacture loop in ways legacy vendors cannot, particularly when AI is woven through the development harness rather than bolted on as a chatbot surface.

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Full Transcript

Speaker

We're live. Uh hello everybody. This is welcome to the AI across the product life cycle podcast now sponsored by AWS. There's a link uh to download their white paper on agentic AI. I'm joined uh by Jay Wright, founder of Campfire and O was I can never get that

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of the amazing gravity sketch. I finally got I got to meet him finally at the CD fam conference in uh Barcelona which is pretty awesome. I have not had the pleasure of meeting Jay yet. Um why don't you gentlemen introduce yourselves to everybody.

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Go ahead Jay.

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Sure. My name is Jay Wright. I'm uh co-founder and CEO of Campfire. I've spent a lot of years in this immersive tech space and uh got a lot of learning. Looking forward to our discussion this morning.

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Awesome. Thank you.

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Yeah. Hey everyone, I'm Olawash Sosa. I go by Shay uh co-founder and CEO of Gravity Sketch. I've spent about a decade in product development, physical product development from furniture, consumer electronics, um to car interiors before leaving and and starting out Gravity Sketch also about a decade ago. Uh I just find that the the technology itself is not the thing that I'm focused on, but actually what it provides and it enables the individuals to do is like it's just like really groundbreaking. And we've always been trying to to help everyone understand the potential of this technology given its maturity curve um and how it can offset some of the complicated and unnecessary back and forth that happened in the product development process. I think there might be a little bit of bandwidth over there. Um, well, it's it's such a pleasure to have you both and it's I I was also excited because I have two people that are both experts and leaders in the this whole field of virtual reality, which a lot of people haven't even tried on Google glasses or the vision.

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Oh, don't say that.

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Well, they're they were expensive, right? I I wore them once at the Google headquarters like 10 years ago, and I remember they burned in a hole in the side of my head because the battery was in the right wrong place, you know?

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And it was Vision Pro. I mean, it's not everybody's got three grand to drop on a pair of

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dark glasses.

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Yeah.

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Um I was just so I usually start this interview asking about um to ask you guys to think back to November 2022. You know, there's a before and a and an after to Chad GPT, right? I mean, it changed the way we think about everything basically. Um, I'm wondering, were you guys when you first saw you were both software people? You saw that happen. Were you guys initially bullish or skeptical in terms of how that was going to change uh engineering? You know, did you think, okay, well, it's going to change the consumer side, but engineering is is engineering is going to stay the same. How did Were you guys bullish or skeptical on on how that was going to be transformative?

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I I was pretty bullish. I mean, uh, LLMs were sort of not my first AI rodeo. Um, building the Euphoria business at at Qualcomm and then at at PTC, I I'd seen what AI, then we were calling it deep learning, had done from or done for computer vision. It was just completely transformative and changed the algorithms and the way we were doing everything. So I kind of looked at LLMs as the next wave of what was happening this time with language and and I think for me the thing I was most taken with is okay uh we got this we got this natural language interface thing down now now right like that was the big big takeaway is we can actually talk to a computer with natural language and and clear also that it was going to make it accessible to a lot more people. So I I think where where my head went first was wow, you know, working with 3D and engineering, we got a lot of mouse and keyboard gymnastics we do to move 3D around, um, if we can at least start by just bringing a natural language interface to 3D, we can make this stuff a lot easier to work with and accessible for more people, which is just really critical to what we're doing with Campfire. So I think like when those first uh LLMs came out, I think ChatGpt had an API with a couple in within a couple months and and we started running our first experiments. So bullish bullish then more more bullish now.

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We'll get back to that. How about you Shay? Were you also uh super enthusiastic or maybe a little bit more reserved?

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Uh definitely curious. Curious but also cautious. I mean you know it's what what are we actually dealing with? what's the kind of uh I guess what's driving it? What's the logic that's behind all all these uh these systems that are running? And I'm I don't come from that background. So I don't have a whole lot of you know predisposed information around it. Um but also we've been promised this future of AI for a very long time and I think that's where like the caution came from. It's like, okay, this is what, you know, the the the videos and on and the the movies are telling us and and so I, you know, I really was hoping to to wait until, you know, we actually see something more substantial, which we have. And I think the thing I wasn't really prepared for was the pace.

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You know, it was actually like so fast we're seeing iterations

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and the improvements and also the whole world now is exposed to this, right? Like my my pension is exposed to this whether I like it or not. And so I think there's just like this momentum that has come along with it that um has has really driven a lot of awareness and

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I would say whether you you like it or not you're you're part of this journey. And so for me like now I'm thinking a lot about how do we offset some of the tedious tasks similar to what Jay said um to the LLMs but also this world of 3D. It's a very unique world and most of our customers don't have data floating around that could be trained on. Um they they actually don't even have their data accurately logged inside of their organization to train against and you know this data that is generated in 3D right now is really depth. It's not bre information. It's not nerves based information. It's not mathematically driven. And so I think we still have a ways before we can get to the point where the models are actually going to drive mathematically resolved models that can then be natively adjust adjusted using you know our our current geometry kernel or you know a um a Simmons kernel or or or something of that sort. So we're seeing a lot of adoption our customers is happening a lot at the front end and what what we're seeing is that there's a lot more optionality in the front end and so taste makers are really important you know really deciding which models you want to move forward with and actually put into the more uh formal 3D development process

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because I would say I'm cautiously bullish. I would say I'm cautiously and not not because of the hype. I think that there's a long-term potential here. We just need a lot of people to to to start aligning on what are we going to feed this thing? How are we gonna actually get some real meaningful information out of it for for engineering workflows.

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I guess maybe we for the people that um are not as as AI7 maybe we need distinguish mention that you know AIs are are a language model. They're dealing with language and 3D has its own formats its own unique way of working right. So that's sort of where the rub is for engineering. How do you get that in and particularly when you guys are using virtual reality which is another level of 3D is not just on a screen I need glasses or some kind of augmented device which makes it even harder to make AI because you've got to somehow well you got to use other techniques than just a pure large language model because geometry today is still not code it's not a language right

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it's it's not and I think in general when the first large language models came out I said thought you It's going to be a while before these things are going to be useful in 3D because large language models were trained on language, right? Like not 3D. It's not like there's a bunch of CAD files out there in the corpus of training data that the labs are using. Um, but I' I'd say I've been I've been extremely surprised what people are pulling off. Um, campfire included with without having true understanding of 3D but using current models to manage essentially scene grass. Um, there's a lot of power, a lot of power that can be derived. And you've seen a bunch of examples of of this, too. So, I'd uh I' I'd say my my my learning over the past six months is just sort of expect it to go even faster than than you thought. Uh capabilities I thought a year ago were going to take two years, you know, happened in in six months and and actually not the way I thought.

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So, um I love it. It's so it's so exciting. This is like the tech hasn't been this exciting since I was 10 years old typing, you know, a basic program into a TRS80 and seeing it go. It's unbelievable.

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It's it's I treat it like akin to when polygon modeling came out like in full effect. And so it's another way of using this technology to maybe drive a result, but you you nerves based model and you solid based model much different than you polygon model. And I imagine there's going to be a world where you are, you know, discussing with the AI and getting some initial models or or revising a model. I think that will be a slightly different way of of operating and a different mental model. Like when I approach I I've been using CAD tools pretty much my whole professional career. When I approach a problem in Rhino, I approach it differently than I approach in Solid Works and I approach that differently than I approach alias. So, you know, having AI at as a companion on all three of those SKs, I would probably approach those things even differently at different stages. um potentially I won't have to set up a scene anymore. Um I just get stuck into, you know, a an existing uh template or something like that that I can generate through through language. So I think there's there's just a a way of approaching it as another technology or another geometry type potentially in your tool set.

Speaker

I wonder if um implicit might be one of the ways we get there, right? Um because that's that's already a mathematical expression of geometry. Um I wanted to ask now like of course you guys are both developers or and uh well you've been in the software world AI is absolutely completely transformed the way we do software development right I mean now uh it's just the insane velocity at all I I'm wondering how quickly did you guys add that to the stack of the what your developers were using and how much has that changed is it is it you know probably you started maybe doing the um the uh the specification documents and moved on But I I'm just curious to know how uh how you guys started adopting AI in the development process.

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You can start if you want. Go ahead.

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Oh, I can start. Sure.

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Yeah, go ahead.

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Yeah, sure. um straight away. I think even before specification documents like our devs were the first at the forefront of this and so um we really quickly started to explore like changing different things in the product really quickly to prototyping things to you know figuring if we can kind of bug fix or or solve some really complicated parts of our of our um stroke algorithm. things like this where you just you have someone to kind of ping ideas uh against that has an infinite amount of knowledge or at least you could point it into like a researching area of deep knowledge and now it's kind of spread across the whole the whole company like we use it in every stage of the of the process. There's still part of our code base that we do need to like architect so that it could work better with the LLMs. I think there's like that there's like this legacy code that we didn't build with the mindset that these ALMs will come into play and we'll be able to kind of use these as like a companion in the process. So, we're working on that at the moment. Um, but also it's starting to kind of bleed into what we present to customers, right? We're now getting a much more rich understanding of some of the domain challenges for our customers and building out our presentations as well as how we might structure some of the settings and the product to better meet a company that's making excavators versus a company that's designing cars, right? Like there's we can kind of get to the granularity without the cost, the human cost that we had in the past.

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How about for you, Jay? Uh we're pretty uh we're pretty AIDS right now. Um it was definitely I think devs devs jumped in real quick with the tools that were there. Uh we were I mean experimenting just with it in product at the get-go, but I mean we're we're now at the point where the entire process is is all automated and and controlled with AI. I mean I I can actually get in now instead of reporting a bu a bug to others. I can jump in root cause create an issue fix it and er right and boom I mean so the the entire process just getting compressed is

Speaker

it's just uh it's just it's just unbelievable and I think the rate of progress is has changed pretty dramatically. you know, it's moving. It's moving so fast that you have to kind of spend dedicated time just to sort of share learnings within the team, make sure everyone's getting aligned because everyone's got some new tick or trick that they they've figured out.

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Um, but uh it's been it's been a lot of fun. It's just been a lot of fun and seeing the results has been uh been tremendous.

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So, you guys inviting uh your agents to the scrum meetings now?

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Oh, 100%.

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All the meetings. All the meetings. How how are you guys putting in guardrails though so it doesn't start putting pink elephants in the middle of your scene or whatever?

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I mean we have a

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review that's a I mean we have a review process. We all the engineers do kind of like a round robin when everyone reviews each other's code. We have a a QA team that's really thorough and combs through everything in the product. Um it's not like we just kind of set it loose. I think that day will come but I think it needs enough of like working with us to understand you know where it can push the boundaries and where it can't. So I think we're again we're in the very early stages in my mind of like what this technology will mean for the development process and with things like codec pod like

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I think they're also learning as they're developing you know the next tool sets and the next models and so I think anyone that's just letting it loose on the codebase right now will most likely need to spend a bit of time doing some hygiene in the future.

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So for a early stage startup who doesn't have like the legacy that we have like it's probably amazing. It's just like you could just crank out product left, right, and center. Um, but I think over time you might want to put a little bit of structure because maintenance is a really big thing and if the if you don't have enough of context of what needs to be maintained, what could what's tends to break, what the user behaviors are, um, I think there could be like a little bit of a a kneel in a hay stack kind of approach. So yeah, I guess the reason the way that we can maintain it right now is by by just being a bit human in terms of the curation process of what actually goes to production. And uh Jay, has um has AI changed like the the way you look at organized the developers in terms of agile versus waterfall because those were the two ways we used to do it. Is there a new model emerging with the agentic stuff in the middle?

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Uh I think I think waterfall has gone the way of the dodo. Um everything everything's agile. Certainly roles have changed. Certainly there's fewer folks that are just sort of building software, right? We're converging more more and more to the same people that can define the requirements can make the changes in code and then having the just architecture and and governance being in the hands of a few to make sure that you know the there's no pink elephants showing up. But it's it's super it's super important. You know, I've been doing software for for a long time and um definitely bad things can happen and it's incumbent I think on everybody using this technology to make sure that they've got uh they've got safeguards in place. Um there's a question in the chat u my friend James hey James uh is asking many designs start with existing assets current design bombs legacy bombs supply chain sourced content etc. How will AI be able to leverage existing diverse content and make new stuff?

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So yeah, existing 3D content.

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Yeah,

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because it it already references existing 2D and language, right?

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Um

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yeah, I think right so there's there is approach right now

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exploring and playing with which is just putting a bounding box around whatever geometry is there and you get six images out. You could then the AI could then read that and say okay like this is a vehicle um this is a vehicle this is a you know a vehicle with a uh a stance of this x y or z and then you can crank out a couple of different con constructions of that. So I think for iteration like quick iteration there's like already well established tools for that.

Speaker

You just feed in what you currently have in the scene. um in terms of that being exactly the same topology um and the same geometry set that and even the same scale to be honest is like that's there's another hurdle into that uh domain and you know we're still trying to figure out how to like isolate things that you want to change like maybe you don't want to change the whole thing or you just want to change the face or you want different wing mirrors like there's a lot of different things that we we hope but I think hope right now is not a matter of years it's a matter of months so um just being ready for that kind of really quick iteration cycle once

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models can help distinguish parts and I already see a lot of that happening but like parts or or um maybe more of the anatomy of the product that you're actually designing and developing. I think then we'll see like an explosion of how these things could just feed in tons of information and get more context because right now if you prompt something and you say I want to get you know an SUV for sevenseater that has the the similarities of you know a Range Rover. It's it's kind of going to give you something okay but it's not going to give you the right proportion and stance. And that's that's tough but I think that will come.

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And how about for for you Jake? because you're dealing more with collaboration than than design, right?

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Yeah, we're we're dealing we're dealing with a wide range of what I describe as spatial workflows, right? So, some of those are going to be in engineering design, some of those are training, some of those are sales and and generally those workflows depend on all different types of assets, right? Like for example, if I'm trying to create guided instructions for an assembly procedure, I'm going to have some 3D assets that define where I need to move things, maybe some animations. I might have some documents or specifications that have the rules by which this is done. I might have a reference manual. And I think the amazing thing in immersive land when you're spatial is it brings all that context together. I've got 3D context, 2D context, and even some context of the world around me, uh, depending on the device I'm using. So now in in Campfire, right, you're using AI to bring in your 3D assets. And we treat different types of 3D assets just like you treat different types of images in PowerPoint. you can just bring them in, move them around just by talking essentially to the AI. And then you can also bring in external documents. So if you want, for example, your trainer, your virtual agent, we call it a spatial agent in Campfire, if you want it to be able to take questions from people going through the training, it'll do it using the documents you provide. So, it's uh it's just tremendously powerful in being able to use 2D and 3D context. Bring all that data together in an experience and a workflow that's just incredibly easy for people to use, right? You don't have to be you don't have to be an engineer to to use this thing or or even build this thing. It uh it's it's incredibly simple.

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Awesome. Um just wanted to change gears. So like uh my next question is always about where does AI sit in the stack of your software? Is it does the user encounter it directly in the UI because there's a chatbot or something? Is it just the in the DNA are using foundational models that are AI based? I'm just wondering where how uh how AI native uh the applications are.

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Yeah, I can kick kick off on this one. I look for us a AI is a first class user and in fact AI presents itself just like another human user does in in campfire. It actually appears as if another remote user were in there in there with you. So we call it a spatial agent. Um you might talk about it as an embodied agent too. It's like another kind of head that's floating around. It's aware where you are. It's aware of where the models are. It's available. Understands all the tools that are in Campfire and can use them. But when it comes to our stack in our development process, that means now every feature that we implement, we think about exposing on multiple surfaces on on one that new feature has got to be exposed through the UI for a human user, but it also has to be exposed via tools for our own agent as well as third party agents. But the reality is that means that the AI and and I'll be more specific and say the harness the harness is woven into every aspect of the stat all the way through. So um and and in fact I' I'd say most of of what you spend time on now with in the world of AI in agents is is sort of development around that harness um and and less around kind of the 3D stuff, right? That the the harness is where the action is.

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Yeah. you. Mhm.

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Yeah. In a spatial environment, the the interface is so critical. I can't stress this enough. Um, and so there's there's things that are inherently physical because we are almost like teleporting our our physical self into a digital space and there's like AI which is or AR which is overlaying. And so I think there's things that natively feel intuitive to the human and we want to always make those a priority and then there's things that don't feel intuitive because it's more of a computational thing and you're sitting down in front of the computer with a keyboard or something like this. And so we try to offset those things to kind of natural language. And so there's a kind of a delicate dance and we find that a lot of our customers our workflows are really deep into we need to deliver this product in a certain time frame. we need this type of buyin and so there sometimes are human feedback which needs to be driven primarily through the human and then there's just really about capturing that feedback and then turning into a bullet points of executables right and so there's that element that that overlays as well so for us it's it we're still kind of finding that right balance but we prioritize human first interaction and then AI is supplemental to help enhance the communication just like we use AI now for our all of our meetings. We use AI to summarize things like this is really the way that we're thinking about it in its current form. As we move forward into the future, we think iterations, uh we think simulations. There's like a lot of like white space there still to explore. Um, but yeah, dealing with geometry, dealing with a physical product that needs to reach the market, you're always dealing with a human being. And we want to make sure that the human being is represented and the AI is helping the human being rather than um kind of offsetting the need for you to validate something visually or physically, if that makes sense.

Speaker

Yeah, it totally does. Are are you guys actually using your own foundational models at all or and I I didn't ask before, but I think uh Shay, you actually you built your own graphics kernel. You're not um dependent on uh somebody else's kernel. I believe

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we have our own Yeah. our own geometry engine, our own kernel.

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Yeah. I mean, we we're we're using just a lot of the off the self shelf stuff if I'm honest. If we're like 3D gen, it's it's the trellis and huen all the different kind of models that are readily available to anyone. Um and then on all the all the natural language stuff, again, offtheshelf stuff. Um but you know, this stuff is quite smart like you could kind of get a feedback loop. You could pre-prompt it with stuff that you really want it to kind of take into consideration so it behaves in the way that a a Gravity Sketch user needs to to experience it.

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Nice. How about for you Jay?

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Yeah, we're not we're not training anything. Um we're we're based on foundation models that are out there and in use today. I'd say in in general now when when you talk about AI, it's maybe not just one model, right? It's an entire stack or harness of agents and tools that are using different models at different places. So depending on what you're doing, there's different stuff going on under under the hood. But I think that's that's where the magic is is sort of uh composing them appropriately and and creating AI that that gives accurate results, right? I mean, before you talked about sort of the pink elephants and and making those things show up, right? Uh in in engineering, there's there's no room for hallucination. uh we like to take pride in the fact that you know we we make AI that knows how to say I don't know and and that's critical right it's it's really it's really important so um yeah use use the models that are there compose them appropriately and give grounded results um that makes me think of another question which is uh you know the the cost of AI because I I use cloud code all the time and I'm always bit shocked at the end of the month at the anthropology So how are but and there's also the fear particularly when you're developing software of cloud training itself on your data without actually telling you. So how are you guys um doing your users can they bring their own a uh their own LLM and their own keys so that they don't maybe uh uh spend yours or how are you gating the data so the IP isn't leaking out to cloud or open AAI? Does that make sense as a question?

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Absolutely. Yeah. I think in in our in our case um there is an option where the customer can bring their own. So we have we have two different deployment models for the cloud. One that we call like a managed cloud

Speaker

where a customer's data lives in a a multi-tenant architecture and then there's another hybrid cloud where the customer's data is managed within their own sort of cloud account and in that hybrid cloud architecture the the customer brings their own. So they are they are getting their their own bill um for AI but they're they're using the same campfire on top of it. Yeah. on our side um we have like just one one kind of a model for our customers and so we go through like kind of the extensive security checks and so forth so we can get into these big OEMs like you know it's really it was really a lot of work in the very beginning like 2018 to kind of get into the doors of Ford and and uh and GM and the likes and so we've kind of gone through all that regulation and certification and if they want to bring in their own stuff we are just making um we're marrying like what you're currently using and paying for with our software so it can almost be used in conjunction with one another. That way we don't have to have any exposure to some of those things. So if you've already signed up for service X or Y, um you can use that in tandem with Gravity Sketch and you're buying into the the security of that of that particular provider knowing that we have our our own security layer as well. So, uh, Jay, you were super enthusiastic and bullish. Uh, Shay, you were also enthusiastic but a little bit more um cautious. Um, we're four years into this AI revolution, right? Um, so one part of the question is, are you has your opinion changed? I think Jay, you've already said you're actually more bullish than you were before. Um, which is fine. The so the question is like how you know what's next and particularly have we seen or well the the answer is obviously no if there was an open AI moment in engineering we'd all know right because there would be a before and after and I don't think we're there yet. I think that when people see what you guys are doing with campfire and gravity sketch they can actually start looking at what the future looks like but you know that it's not super wide adoption so we're still kind of on that on the verge. So, do you guys think like the open AI moment for engineers is months away, years away, or maybe we'll never have one? And what do you guys think about uh well, the future of of of this whole AI thing? Who who wants to go first?

Speaker

Yeah, I can I can take it. Um, with engineering, at least with us, physical products um primarily are are what our products being used to develop and design. And you know it's not as fast as hitting a publish button and it all going to every single user on your platform. Um you you're you have a lot of different different considerations. It's materiality really. So you know you're going to make something out of a sheet metal. Um you're going to have ejection molded components. And so what we're see I think in in this kind of AI moment is less of an AI moment and more of a gradual roll out across different stages of the workflow. We've obviously seen it in design. It's rolled out quite aggressively. Um, but you know now how do we take that AI generated content and push that through the pipeline and use AI where we're needed you know whether it be simulation or virgins or whatever that the kind of the case may be to the final product that reaches the shelves. And you know, I can say with confidence, we've seen a couple of uh footwear designs come from, you know, the generated AI asset through the process to the the the kind of the shelves of the of the foot lockers, JD Sports of the world. Um where AI had an influence on each one of those stages is still a little bit up in the air. Definitely in the front end, it was huge huge help. But how are the injection tooling manufacting modelers using AI? I'm not sure yet. you know, I don't know if there's enough data that that's been trained upon that. So, I don't think there's like going to be a single moment. I think it's a series of shifts that lead to a more robust workflow. And what we probably will be seeing and thinking about is time to market for product development will collapse quite quite aggressively. And so, we'll see that products are hitting the shelves a little bit faster, more wellresolved, potentially customization and variety. So that shift I think is going to be this kind of ripple effect as AI has this kind of injection points at every stage of the process. But you could think about bringing a physical product to market. It takes a lot of people. It's not just a single design team that's able to publish and push on their own autonomously. It really does take a lot of different uh a different moving components. And so each one of those components leveraging it in their own way to make a more efficient pipeline. I like the point you bring up about the manufacturing because that's one of the major issues I'm seeing is just this this gap between engineering and manufacturing and I did a couple of podcasts recently about that. Um I uh when I was in the PM components conference up in Cambridge last week um materialize was talking and they that was interesting because he was um at least they're starting to fusion additive and subtractive manufacturing together with the molding. So, you know, when you're doing additive, you're always gonna have too much material. So, rather than going to another tool, the same tool can say, "Okay, I need to come in with a miller and take this piece out and do a chamfer over here." So, at least some of that stuff's coming together, but there's still a big gap between engineering, manufacturing. So, I guess uh Jay, maybe uh maybe Campfire is there to help bridge that gap, right? In terms of collaboration.

Speaker

Yeah, we definitely we definitely bridge that gap. I think generally when products are done, they get handed over to manufacturing to try and figure out if they can build the thing and being able to validate the build process is pretty tough. So, um if if you're able to take both the the CA models from your products and the CA models from your manufacturing cells, throw them all together and simulate that workflow, you are going to save yourself millions and millions of dollars and months and months of of headache. Um, maybe I just I wanted to go back to your your previous question because I I think we might be closer than you think on just the OpenAI moment for engineering. I mean, to me the the Open AI or the chat GPT moment what wasn't when it started replacing all of our workflows and was totally deterministic and did everything well. It was it was kind of the holy moment of like, oh my god, this changes the game. This is all about change. And and if you if you define it with that metric, I think I think we're we're pretty we're pretty close in that we're starting to see like mainstream tools and I'll just point to I think Blender Fusion 360, right? Get get like uh MCP and like cloud connectors and and so I think once that happens, right, we've all seen the ton of videos on LinkedIn now of what people can do once they start connecting those tools. But I I think that's the analogous moment, right? the one where we're using AI to just control the tools we have. Is that replacing the modeling or the engineering process with AI and expecting to be deterministic? No. No. It's just it's really just about I think using that natural language interface to be able to do things faster and automate things that are that are happening happening today. I

Speaker

I wanted to agree with Jay on that point because I I when I saw the connector thing, I was kind of blown away as well. Started playing with it and I was like, "Okay, it's almost there. It's almost to the point, but I I think as a whole, because I' I've spent so many my years in manufacturing like as a whole, I still have this longing to and desire to have the expertise of an injection molding engineer, like the guy that's making the tool. I want that in the AI as well. if that makes sense. Like I want to be able to confidently know that this thing could be injection molded and like it could kick out a tool that has all the moving components so I can have this, you know, injection molded out of ABS without the the tooling overhead and cost that I would normally incur. So I guess my my holy moment is probably um still at the physical I want to hold the thing in my hand knowing that I was able to kind of like compress that timeline and and the dependency I have on the on the tooling engineer

Speaker

and not not trying to put them out of a job. I think they're still valuable, but could they do like 12 tools at once rather than, you know, focusing on doing one injection tool at a time, I think.

Speaker

Well, okay. So, that's um another question I didn't want to forget is a lot of there's my audience is a pretty big segment of rather young engineers that are probably having a bit of anxiety over this AI thing like, oh my god, will I actually have a job? So um from your perspectives as as uh leaders and and people that are hiring engineers and developers, how what kinds of things are the does this younger generation of graduates needs to focus on where they're going to be essential to the process and not replaceable?

Speaker

Uh I'll go ahead and start. I I think look the be the best thing you can do is just fool around and experiment with everything you get your hands on as fast as you can. uh hit hit YouTube, watch videos, download tools, experiment. The people that are going to move the needle the fastest are the ones that understand it the soonest. It's it's also it's also very very clear to me that the the gap between high performers and low performers is just going to change dramatically with AI because the productivity gains from people that understand how to use it and apply it are are just orders of magnitude um greater than than those that those that don't. So just jump in with both feet. I don't I don't know that it really matters where you start. Just uh just jump in and play learn. Is that the same thing you'd say, Shay, or would you have a different twist on it?

Speaker

Oh, no. I' I'd echo that exactly. I I take it a little bit further as well. Uh, you know, a little known fact, I I had a creative agency many years ago after leaving university. Um, I did a few uh buildouts for a couple buildings. Um, but it was just it was so much work. It was just a two-man group, right? and the the process of actually making the interior like we actually manu we designed manufactured design presented and manufactured to our clients and the work that I did back then that would take me months could now take me a couple afternoons right like after work I could even fool around with this the making process and the sourcing the material the delivery of you know the material to from one vendor to the next is another big component and so I feel anyone that's like stepping into the space that has a bit of fear I think there's there's so many moving parts. How do you extend yourself beyond being a single cog? And I think that's like that's what I learned about having my own creative agency is like I had to be all these different cogs moving at different gear at different speeds, right? And so if you're just breaking out of university and you're wanting to break into this space, I would say make stuff. Use the tools to develop everything. You know, get the presentation right, get the deck, do some simulation, and then try to get that thing physically made. Even if it is just a small gearbox assembly or something like that, you have 3D printing now. You have online resources where I never I didn't have this stuff back in the day. I can just upload a file and I can have something CNC mil for me and shipped to my house to my specifications. Right? So that all builds a better understanding and a cohesive knowledge of how materiality works, of how assembly works. And so eventually you're going to be talking to these tools at a much higher clock speed than hey I want to make this and I want to present in this way. It's like hey I know that this material is going to be used. It's going to be you know uh 720 or 660 aluminum. It's going to be you know these types of tools I want to be using against it like this quarter quarterinch mill or whatever it may be. And so you're actually having like a much more sophisticated conversation. So your results and your throughputs are going to be better. So if you are joining um an organization, they're bringing on someone that knows how to have a very deep conversation about the the beginning and the delivery phase of a product. So, I think it's it's almost like I've been playing with this idea, so this is the first time I'm talking about it out loud, but it's almost like going back in time where we go to a cobbler and they would know exactly how to design a shoe for your foot because they were they were making shoes for your family the whole time or they know exactly how to create, you know, the saddle for your horse. I think now the designer, the engineer can almost have like a very expansive understanding of the whole process for specific use cases and and that's how you become dangerous because you can then speak at a different level and level of customization I think that's going to come in is actually pretty cool. So pretty soon we're going to be able to just have custom product for individual.

Speaker

Very cool. Yeah, I think the I think I was seeing some of that at the Nike demo at CD Fan, wasn't it? That was pretty awesome. And by the way, I um I did summaries of all the CD fan presentations if that's a conference in Barcelona just happened a couple weeks ago for those didn't who hadn't heard about it. Um uh Shay's presentation I reviewed as well. So feel free to look on my LinkedIn for that. Also AWS is our sponsor. So please click on the link uh and download the white paper for them. Um, so then the last section of this interview, I like to talk about digital transformation and I I because I think that, you know, AI is moving a lot faster than the Fortune 500 is, right? Um, and AI adoption is well complicated by a lot of things. Um, but I I when I think of digital maturity because obviously a company has to reach a level digital maturity before they can actually use AI, right? because you have all that the the legacy cost of having um data to train on. Um well, when I think of digital material, I think of a scale of one to five. Like one is basically using Excel and and you know, email to do um collaboration, which probably makes Jay's skin crawl because he's got such a great collaboration system. It's so much better than email. And then you have the companies that could be at level five, which would be like autonomous, agentic, digital twins. And I don't think anybody is at five. So, first of all, first of all, the question is your customers that you're selling a gravity sketch and and and a campfire to, do you see them between one and two, closer to one, closer to three? I mean, where where do they sit today in 2026?

Speaker

I I could start. Um I we're dealing with with mostly kind of industrial manufacturing. So, you know, automotive, aerospace, industrial equipment. So, as as you know, this this one skews pretty low. Um maybe uh maybe a two-ish for most of of what what I see. Um I I would say that um I probably see more customers that want to make sure we're not using any AI um than than I see customers that are at like five where, you know, they got the the fully agentic digital twin. I I actually think there's probably not a lot of customers at five. Five might just be vendor vendor territory. Um but yes, it's generally it's it's generally it's generally low and and I think it's just because we're in a conservative industry that moves very very slow and is is regulated and and it's just very very cautious in their approach. It's it's not also due to the cost of like you guys are both in VR so that there's a certain cost associated with the headsets and stuff. Is that also a bit of a drawback or that's not really a concern?

Speaker

No, it's huge. I I think that's a I would describe that maybe as a different axis of maturity. You know, there's there's digital maturity around let's just call it like digital thread and aentic workflow and and I think that's really in like the thrillseker early adopter kind of space right now. like they're kind of you know innovation folks are trying to understand what it is and what it means but the the bigger concern is is really just uh infosc processes and the ability to adopt new technologies. So bringing in something like an immersive device or a headset is you know it's a new headache for a lot of people and and I think that that takes time before you can get that to be you know standard issue in a company with tens of thousands of people that they can just order and have supported by it and you know as crazy as it sounds like the cloud just being able to put proprietary data and store it store it in the in the cloud a lot of lot of people that really want to demand that that's going to be on prem whatever the cloud uh solution is so you know th those hurdles those hurdles remain.

Speaker

Thanks man. Um what about you Shay? What's what's your take on it?

Speaker

Jay covered it pretty well. I mean like a lot of customers are still trying to fight with trying to get stuff on prem and you know I I'll break it down into two different ways actually. So the the customer as a entity versus the individuals within the accounts. So the customer as an entity they h I think they have to be conservative. I mean you had you know the Firestone incident with the tires and so forth like you we're putting human beings into these products and they have to protect the human being in the event of a fault and if the fault is introduced by the manufacturer that could your company right so I think they are right in having this a conservative approach uh headset cost is negligible if you think about it a car from start to finish is $ 1.5 billion like this is actually a cheap thing but to get it to say, "Yes, we're going to roll this out." As Jay said, you need to work with a supplier. And we don't really have a supplier in our industry like a Dell or or an an HP that rolls out fleets of of and refreshes of hardware that include any kind of spatial device. It just it just doesn't exist, right? So, you end up going through different um different vendors that are are able to supply at that level and include kind of the warranty and so forth. So, I think that's like another part of the industry that we need to need to kind of continue to to work together and try to unlock. But if it comes to individual account, like they're already using this stuff and they're using against I won't name and shame, but they're using against their company's policies, right? So, I walk in, people are already having headsets, they're they bought them, brought them on on board. They're already using a slew of different AI tools on their personal computer and then just copying text over or, you know, copying the imagery over. So like the human being seeing the value in this technology in these organizations that move extremely slow is already there. So I always try to encourage our customers like at least get a task team out in front of this stuff so you guys can actually start to see what the minimum viable integration is because the teams are already adopting it and they're adopting it against company policy purely because the pressures on them to deliver in the time frame with the accuracy it only increases like you increase the timeline you just increase the number of projects. You're not hiring more people. You're just throwing more projects at the same group of individuals. And so of course it's human nature to to kind of look at what is the best tool for the job and if my company doesn't have it I'm going to figure it out and bring it in in house. And in our industry I I wonder if this kind of also parallels with Jay. Um people are choosing to go into these creative disciplines and I I include engineering as a creative discipline. This is a lifestyle for them. Like a lot of these folks at home are tinkering with stuff or designing stuff. they're continuing to creatively output anything. Maybe they're renovating parts of their home. And so for them, finding the best tools for the job and the most exciting tools and the things that really help them stay creative and get locked into that that flow. Um, you know, that is that's just part of their lifestyle. So these organizations I think um you know the the technology is moving faster than they control it but I think trying to find a halfway house where they can introduce things maybe ring fence a couple of other things but you know giving people a little bit of potential to to explore beyond just innovation teams would be would be very valuable.

Speaker

That's a great answer. Thanks a lot man. Um appreciate that. Um, so my thesis is that uh the the the big three, the ones that really dominate our industry, right? Daso, Zemen, PTC are well, that's, you know, they're they're really not uh caught up to where AI is today, right? They're they're sort of in catch-up mode. You guys are on the vanguard of this. You guys are a lot more agile. You have a lot less technical debt. Um, and you're able to go at almost the velocity of of of all these tools. Um, it would seem to me that customers that wanted to move their the needle from one to two or two to three would tend to do that better with a with an agile startup like a campfire or gravity sketch. I'm wondering have you actually seen that when when the customers start using your tools that are AI informed and AI native is there a bit of an epiphany from people outside the project like oh my god if I was you know if I had data governance right and I had connected my data silos and I got the departments of of talking to each other rather than saying oh those bastards they don't know what they're doing is is there sort of an epiphany where like oh my god I I can actually achieve this I can actually move the needle and become digitally more mature um and that epiphany comes thanks to using your software.

Speaker

I um I I don't think any of our our customers are using our software because they they think our AI is going to be implemented better or faster than incumbents. I think generally they're they're using it because they can they can get a job done that they can't get done with that that other that other software, right? We're not trying to do the same things or duplicate the same same workflows. I think I think generally the the wow the wow moment for for our customers versus versus incumbents is the fact that you know our our software probably feels more like a video game than it does engineering software and and it feels more like just you know modern collaboration tools in sort of the 2D domain um than anything collaborative they've used before from from in in combat. And then generally, you know, I don't I don't I mean, while everybody's trying to figure out what AI is for, I think I'm always cautious when people are looking at AI just for AI's sake. You know, if there's not a specific problem they're solving, but for for us, AI is about about being able to deliver more workflows and make them easier to use. Um, full full stop. And and if it does that, great. And at the end of the day, that's what that's what resonates with the customer.

Speaker

I agree. But I've had a couple customers reach out to me and say, "Well, Feno, uh, management is saying we've got to do more AI and and uh, you know, the the portfolio from the big three doesn't have that in there. Um, can you help me like which what startup should I use so I get a little bit of that AI stuff and I can prove that this stuff works?" So that that's where that question is coming from.

Speaker

Yeah. Yeah. Yeah. I mean, look, when when I get that, I still I I do love that, but I want to get them anchored on the use case as soon as we can. just AI for AI's sake, right? So, 100% here's something that you can start and it is AI today and and I don't want to leave that behind because I I see that too. But at the end of the day, if they're not looking for the use case and they're just looking for AI, then then uh you know, we're we're sh

Speaker

Yeah, sure. Our company mission uh is to help people bring better products to life and we're leveraging these technology tools to do that. Um I would I would wager that it's not too far off from some of the big guys in terms of their mission. Um but you're right, we have this flexibility and we don't have this baggage and this legacy that the others have. And so I think when customers are seeking us, it's not so they can deploy the technology faster. is more of like, okay, here's a problem that probably has persisted in some of these legacy technologies for like legacy CAD tools for a very long time or 3D environments for a very long time. You guys have seemed to open up the hatch on that. And whether it's just being spatially to Jay said to Jay's point, like just being spatial, being in that environment opens the whole door to like anyone that wants to get into 3D because you don't have to worry about navigating with a mouse, right? So I think it's those kind of things that are bringing people closer to us and it's our ability as a small startup to to really pick a couple of workflows and work aggressively against like we're not trying to boil the ocean. If you think about you know a do system I imagine most of the products on the shelves in stores have gone through one of their products right and that is a wide range of use cases. I mean, holy cow like that's so many different use cases that they have to take in consideration and they have to work against have to build a product that can service all of those whereas we are narrowing down into one part of the tool chain and we're really going to make that excellent and you know over time we have big ambitions to go beyond that but I think that's why we get some attention from customers now I won't you know mute the point around AI I think a lot of the these customers are getting AI budgets to go even we've given a budget to our team right like go and explor explore some of these tools so you can get more efficient. Um, but I I too like Jay, I don't want a customer to come to us to say like we have this AI budget, let's use it for gravity sketch, show us what you can do with AI. Um, I think that that that can lead to um a churned account and I think we want to drive value. We don't want to drive novelty. And so it is hard to compete against those budgets because you do have a few players in the space that are just creating really um eye candy type of AI experiences. Um, and I think they'll, you know, they'll have to kind of true up to to the value and the workflows at some point. Um, but I for us, I I'd rather us grow um I'd rather us grow with more confidence that this is going to be used in perpetuity than try to capture um the wave right now, if that makes sense. I I'd rather capture the wave as part of workflow delivery rather than capture the wave as part of the hype cycle.

Speaker

Awesome. Well, those are great answers. Thanks, guys. Um, I just wanted uh to close um just before we say goodbye to everybody on the audience. Um, where uh where can we see you guys? I mean um I got to see you uh Shay and um in Barcelona, but where can people find you guys in trade shows uh before the summer or during the summer or in the early fall if if they want to come meet you and you and use Gravity Sketch and and Campfire?

Speaker

Yeah. So, uh, October, mid mid-occtober, Atlanta, Augmented Enterprise Summit, uh, probably the best place to be for the intersection of of enterprise engineering and and immersive be there.

Speaker

Awesome. So, midocctober, you said? Yeah, I think it's October 13 through 15 in Atlanta.

Speaker

In Atlanta. Nice. How about you, Shay?

Speaker

Um, yeah, for us, we come to you. I was just at a customer onsite actually today. So if you are in in Europe and in the UK, we uh we love to just kind of come on site. What we find is like just walking through the halls, walking through projects together with uh with clients is really helpful to give us context to like how we can actually help them. So when we come on site, we usually come with someone from product, someone from our our um business development team, and then we have design consultants in house. And so we're just always trying to evaluate the real challenges and see if we can match make that with the technology. We've done um a few road shows. We'll probably do another one in June for for June uh for Munich area. So happy to kind of stop by any of you all out there in Munich um who are working in the industrial design field and and and kind of chat through that. Um you can always ping us anytime directly through the site um directly through LinkedIn for me and we've done a lot of virtual demos. We do virtual demos probably like um at least a dozen a month or so. So you know we are we're we're constantly kind of hopping on. We have a webinar coming up relatively soon. Sorry, the date just slipped to me. It's this next week, I think. Early this week, uh, yeah, we do webinars very regularly, so catch one of those. Um, and then in terms of like the next thing time that we'll be actually speaking at an event, it maybe will be sneaker week in August in in Portland, Oregon. Um, that's probably like

Speaker

publicly where we'll be next, but um, you know, sometimes I just take opportunities as they come. If there's something really interesting that we want to show up to, We'll rock up. But

Speaker

well, you want to keep the thread at Frankfurt when I announce that, right?

Speaker

I mean, if you want to specifically check out what we're doing, just just uh ping us and we'll make time for you. Like I I I think it's such an interesting space and um it's really hard to to kind of get a lot of enthusiastic people in an organization. So, if you get a if you gather a few of your folks in your organization that are really enthusiastic, we'll give you the time. For sure. Absolutely.

Speaker

Awesome. Um, well, that's been a great I think I learned quite a lot and uh you guys gave some really original and excellent answers. I appreciate your time. Um, and uh, once again, we're sponsored by Amazon uh, web services marketplace. There's a white paper if you don't mind clicking on the download and checking that out about agenti. Um, thanks once again to Shay and to Jay Shay and Jay. Um, that was awesome. Thanks to the audience. Um, we'll be back in a couple in about two weeks. be some more um have some a AEC vendors talking about uh some people that develop their own graphics kernel like you did Shay um KIC has their own graphics kernel as well um so we'll be talking about that and um trying to get some machining ones and some uh some more factory uh mees kinds of ones uh as well so um once again thanks to to my uh to my my guests uh thanks to the audience and we'll catch you on the next time on the AI across the product life cycle.

Speaker

Awesome.

Speaker

Thanks Michael. Thank you.

Speaker

Yeah.

Speaker

All right.