As AI compresses the distance between idea and execution, the abstractions that once made design tools necessary are becoming points of friction. In this conversation, Knapsack leaders Chris Strahl, Evan Lovely, and Robin Cannon make the case that the future of digital production starts in the medium products actually ship in, code. They unpack why design systems are infrastructure, not artifacts, how context becomes the critical input for enterprise AI, and why creating directly in code unlocks faster iteration with higher fidelity. This shift changes who gets to create, how teams work together, and what it means to scale ideas instead of just processes.
In this episode, you’ll hear about:
- AI as an enabler of human creativity, not a replacement
- Why prototype-first workflows are breaking down
- How the Intelligent Product Engine supports real product creation
- What it looks like for designers, developers, and product teams to build, refine, and ship together
Transcript
Chris Strahl [00:00:00]:
Hey, everyone. Before we get into today's conversation, I wanted to share a quick update about the show. After more than five years of the Design Systems Podcast, we're evolving. Our work at Knapsack and the conversations happening across the industry have grown far beyond design systems, and the podcast needs to grow with them. Starting in January 2026, the show is going to continue, but it's going to have a new name, the Patterns Podcast. I'll still be the host, we'll still continue to feature the kinds of conversations and guests you're used to hearing from, but the focus is going to broaden to include the full digital product life cycle, how teams design, build, and deliver modern products. If you're subscribed here, there's nothing you need to do. The feed will update automatically, and the first Patterns episode will arrive right in your podcast app.
Thank you for being a part of the community and for helping shape the conversations we've had on the dsp. And I can't wait to share what's next. Hey, everybody. Welcome to the Design Systems Podcast. I'm your host, Chris Strahl, and I get to hang out with two awesome other Knapsackers. One of them we've had on the pod before, many times. Evan Lovely, my co founder. And then another that we've had on the pod, but not while he's been a part of Knapsack, Robin Cannon.
Chris Strahl [00:01:04]:
Hey, everybody. Welcome to the Design Systems Podcast. I'm your host, Chris Strahl, and I get to hang out with two awesome other Knapsackers. One of them we've had on the pod before, many times. Evan Lovely, my co founder. And then another that we've had on the pod, but not while he's been a part of Knapsack, Robin Cannon so welcome, y'all1
Evan Lovely [00:01:05]:
Thanks for having us.
Robin Cannon [00:01:06]:
Thank you.
Chris Strahl [00:01:07]:
Yeah, and so we're going to get into Robin's transition here in a minute. But just starting out, this podcast is really special, especially for Evan and I. So we've been running this company now as a venture backed startup for about four years, and it's really exciting that we get to announce that, that we were able to secure our Series A funding. And so that's huge. And it's huge in a lot of ways. Like, first, it's a big show of support from the institutional investor community around our direction, around our future, around the way that we think about this space. And then secondly, it means that we've been growing and we've been getting bigger and we've been doing all of the right things to secure that funding as a stepping stone into what's next. And so I'm really excited to talk about that today, to have my co founder here to talk about it from the perspective of a visionary person in this space.
Chris Strahl [00:01:58]:
And then Robin as our senior Director of Product to talk about it from how we're actually going to get this product into market and so that's what today's journey is all about. I wanted to kick it off, really, talking with Evan first. You know, this is a big milestone for us. Like, it's a huge exciting moment. I'm obviously super energetic about it. It means we all have jobs for a while longer yet. And as a part of that, we get to also go continue to pursue this vision. And we've talked about this a little bit before, but I've wanted to hear just in your words, the startup journey that we're on.
Chris Strahl [00:02:29]:
I like to say that you cornered me on a ski lift and that's the reason why this company exists. But from your perspective, tell me what it looks like to be here. Looking back at four years of history.
Evan Lovely [00:02:42]:
Yeah, I mean, I think a lot of it just kind of boils back down to that. We're building the product that we wish we had and a lot of why we made this and some of these first steps were kind of born in pain. I mean, I've got my origins as a front end developer who was turning Photoshop comps into like HTML and CSS and integrating them with cmss and just saw a lot of inefficiencies in that process and something where you kind of like look at it and you're like, there's gotta be like a better way. And one thing I'm kind of always fond of saying is it's kind of mind boggling that the first time anybody used a web browser to view HTML it was like December 1990. And that kind of makes me always feel that there's gotta be a better way. We can't be doing it perfect just yet. So I think that that first step of being like, what if we did it different? What if we made it a little bit better is one thing that kind of always been like a driving force in a lot of this, I think for all of us, but for me especially, definitely.
Chris Strahl [00:03:38]:
And I think that this kind of leads also to why Robin joined. So Robin, we've been working together, known each other for half a decade or so at this point. Right. And so from patterns in Santa Fe to speaking at our events, to spending a bunch of time with us, talking about the future and some visioning stuff. Why did you come on board? I mean, you knew that we were in the process of doing this fundraiser. We'd pretty much gotten there when we decided that we were going to carry and continue to work together. What brought you on board? What made you want to join?
Robin Cannon [00:04:10]:
I think because talking about wanting to do things right I've led the IBM carbon design system. I've helped IBM build a design system consulting operation. I've joined JP Morgan and helped them build out a design system. And even when you're doing that right, even when you're getting everything as efficient as you can, things are operationally great, culturally great. It's still a clunky process. And from the things that we've talked about over several years now, I think that Knapsack is going in the right direction. And Knapsack has the right idea of how can we fix this and potentially change the game, not just the process.
Chris Strahl [00:04:51]:
Yeah, I like that when you couch it in this idea of the the gate.
Evan Lovely [00:04:54]:
Right.
Chris Strahl [00:04:55]:
Because it's not about the tool. It's not about the idea that, like, something is horribly broken. It's that there's this evolution that we can go through to get to a better place. I think that there's this really sort of interesting reflection I have on all this, where back just before COVID when Evan and I were kind of planning all this stuff out, we were sitting in this office building in Portland and we had this giant whiteboard in front of of us. And in front of this giant whiteboard, we were sketching out what we thought might be a software product. And it was couched in this idea that we'd been doing these sorts of system builds in this bespoke way for a while now. We've been working with other vendors in the space, folks like Figma and Envision and whatnot. And there was always this part that seemed missing to us.
Chris Strahl [00:05:42]:
And what Evan and I sketched out was kind of like a baseline architecture. It's like a lot of boxes and lines on a whiteboard that looked at the idea of how do you connect code, how do you connect it to design, how do you connect it to documentation? But one of the things that was not super well fleshed out on that whiteboard was you had this giant cloud that we drew up there, and we said, ML goes here. And I think that that's the thing that since then and now, we've seen a tremendous advancement in the world of AI, to the point that most people refer to as AI these days instead of ML.
Evan Lovely [00:06:16]:
Back then, it was also component driven development, and before design systems were even a thing.
Chris Strahl [00:06:21]:
So as we've kind of like clarified what that cloud looks like, that's what I want to talk about next. And this is what's so exciting about a raise announcement. Like, I'm sure if you're listening to this, you're like, cool. They raised money, awesome. Good for them. But, like, what does this actually mean that we're able to go pursue? We can be excited about the fact that our company is taking the next step, but what we're excited to share is, like, what that next step means for our product. And so, Evan, why don't you lead us off, tell me about the future that we want to build before we.
Evan Lovely [00:06:50]:
Try to dive into the future just a smidge on like the past of basically, like what we've been building. It has always been this idea that end users experience the result of code is the source of truth. Design or code. Like, it kind of answers that question. It's like the source of truth is what users experience. And so it's all about basically getting it. So builders, creators, designers, engineers are shipping in the medium it's destined for so users can be able to see that. And so being able to know about all of these code pieces, right? So like, what we've been working on for a long time is have structured data about all of the components and how they can fit together and being able to use those for composition to put some of that stuff together.
Evan Lovely [00:07:36]:
And that's a lot of like, that we've been working on and a lot of the foundational, the current, current product up until this point. And I think one thing we had always said back then is the interesting things happen once you already have the design system. So that's kind of where this is all going now. It's like, okay, once you do have that design system, once you do have all that structured data, once all those pieces do represent your brand well, how can you put them together without having to, like, know how to code? And I think that AI is going to make that even easier than ever before there, because an interface can fade away to come much more workable with, like, natural language, for example.
Chris Strahl [00:08:16]:
Yeah, and I want to talk about the design system thing for a second. Right. We've always kind of talked about our context as one that is a design systems context, largely because that's what the market called the thing that we were making or the nearest thing to it. I've always had a problem with the idea of design being the first word in design systems and design because, like, people innately think of canvases, they innately think of the tools that exist right now where you have this ability to go, like, draw boxes imbued with glorious purpose and then send those to a developer that ultimately then makes that thing that's real. I think that that world has Always been something that we've simultaneously had to embrace and push back against, where, like you said, making something in the medium it's destined for. I think that we're finally ready to start talking about the future of Knapsack as a replacement for Canvas tools, where we want to be able to have designers do designer things by actually directly manipulating code. And that's a really important distinction from, like, we want to get rid of designers or we want to get rid of that process. Right.
Chris Strahl [00:09:22]:
Why do we have design tools in their current iteration? And my hypothesis on this is that we have them because a bunch of the things that it took to be able to work with code were complex and technically challenging and very cumbersome and slow. But now that we have the cloud and things like containers and the ability to very easily spin up CI and all these systems that we can interact with, design systems aren't the interesting part. And I think that, Evan, this is kind of what you're alluding to is like, the system is the foundational infrastructure that you need to go be able to do a bunch of really interesting things.
Evan Lovely [00:09:57]:
Yeah. And I'm going to actually toss this ball over to Robin on this one, because I think that you've mentioned some interesting things on this where it's more just like that's how you build product. That's what you need to be able to have to build product, is to work with these small reusable pieces. So that way you get consistency throughout. Rob, I'd like to hear some of your thoughts on that.
Robin Cannon [00:10:17]:
Yeah, I mean, at the simplest, nobody builds a design system for the sake of having a design system. It is a path to something else. And it's a system of record. It's a system of truth. It's got your design and your code, at least the building blocks of that. But we're still creating this abstraction. And a lot of the reason we're creating that abstraction is because it's so difficult or it has been more difficult to move down that process or down that pipeline.
Chris Strahl [00:10:47]:
So explain what you mean by system of record for a second, because we use this all the time inside of the four walls of our company. It's a term in industry, but usually you apply it to something like a CRM or an accounting system or something like that. So, like, when you talk about it from that perspective, what do you mean?
Robin Cannon [00:11:01]:
So when you think about a design system, it's different than just the stuff that's in it. You could take a bunch of components, even very good components, and create Something that is a terrible experience. But when you're talking about a system of record, and I'll use IBM as an example, because I was part of Carbon for so long, yes, it's your designed components and your coded components, but it's also your user patterns and your flows that you've learned about over time. It's how you strive for accessibility as well as specific accessibility rules. And it may even expand beyond that if you're in a regulated environment, to compliance and regulatory pieces as well, so that there's a much, much broader context, that source of truth for how you're delivering your brand and your function to the market in a digital form.
Chris Strahl [00:11:54]:
So when you think about this future vision, and we want to talk about that core problem that we're solving of, hey, we're doing a bunch of work outside of the medium that it's destined for. We're doing all this process that is involved in taking something that is in somebody's brain and making that a product that a user can touch. There's this huge amount of tooling and people and roles and process that that goes through that are all these different abstractions. And I've kind of thrown out there that they're the wrong abstractions. What makes Knapsack and this idea of working directly in the medium, it's destined for the right abstraction. Why is this moment, the moment that this gets figured out?
Evan Lovely [00:12:32]:
Well, because it's the least amount of abstraction. So, I mean, I think that what designers and creators want is to be able to take what they imagine and then get it into the hands of users and for it to remain and keep its fidelity. It's like, oh, that's like what I imagined it would be. Yeah
Chris Strahl [00:12:52]:
This thing in my head is what somebody's actually touching.
Evan Lovely [00:12:55]:
Exactly. And so it's literally the source of most human misery is this difference between expectation and actual experience. That's when a designer's like, okay, you know, there were a lot of details sweated there, and then the developers were off and the spacing is all off, for example. I think that's one reason why design tools work well, is because they can get it out of their head. Now, it's the wrong medium, but at least we can basically all objectively look at it and see what they're doing.
Chris Strahl [00:13:25]:
Yeah. And it's fast and it's easy, right?
Evan Lovely [00:13:26]:
Exactly. It's the least amount of abstractions, there's the least amount of steps, and so it's that translation layer. So we're not talking about designers coding. We're talking about them being able to have it in a web medium or Android. And so that's what we're talking about. And being able to go, all right, since it's in that medium, it's going to resize like it will. It's going to basically have like animation like it will, things like that. And so reducing the number of steps, reducing the disposable artifacts, you know, a Figma file ends up on the cutting room floor on its way to production.
Evan Lovely [00:14:02]:
It has a use. I'm not saying it's not useful, but it's not something that ultimately goes to that end product. It's kind of similar to how in movie making, principal photography is done in order to figure out what kind of video shots were done, because photography was cheaper than video. And so eventually you kind of get to the spot that it's not cheaper than video. So you may as well just cut out that step.
Robin Cannon [00:14:24]:
Right. And I think you use the term translation layer. We're using abstractions to be able to translate intent, because we've had to. And now I think we're reaching the point where we don't and we can get back. I don't know whether this is apocryphal or not, but I have an old boss who told me that Steve Wozniak comment that designers should start by designing in prose, basically writing out what the thing they are designing is supposed to do, and then everything after that until it's built is abstraction and translation layers so that we can get to the creation of that thing. And design systems and other things are about scaling and making it as efficient as possible, the discipline necessary to create those things. But actually, AI and technology in general, we're reaching the point where we can compress that process and we can scale the ideas themselves, not the disciplines necessary to get to those ideas.
Evan Lovely [00:15:20]:
Yeah, and also the path towards high quality output is almost always based in iteration and feedback. And so it's not just how quick can I get my idea out, but how quick can somebody tell me how that idea can be better? And then, of course, how can I update it and get it out again? And so basically, going through those translation layers can slow that part down. And so having that rapid feedback cycle is the other part that really, really helps out. And we're getting to the world where that feedback is either given or implemented by humans or AI.
Chris Strahl [00:16:02]:
Hey, everyone, I'd like to take a quick break and tell you about Knapsack's leadership summits. Every month we host an exclusive in person Event in different cities all around the country, bringing together design, engineering and product leaders. These summits are all about sharing our learning with tailored discussions to address the challenges you're facing. The best part, it's totally free. Head over to Knapsack.cloud/Events to find an upcoming summit near you and apply to join us. We'd love to see you there.
Chris Strahl [00:16:54]:
So what I'm hearing is that we're in this place where canvas tools or traditional design tools as an abstraction are less meaningful because we can do a lot of the same things that those tools were intended to solve directly within code. And a big part of the way that that's changing is because we have systems that back these things up as a way of creating a consistent, reliable context. We have a bunch of code models that work well with this, and then we have AI that can understand that context, those constraints and those code models, and actually help people make things faster at the speed they would be able to make them, or faster than what they would be able to do in.
Robin Cannon [00:17:10]:
A canvas tool, make them to the point where humans can refine them. I think sometimes we have too high an opinion of what AI might do. You're like, oh, it just makes the thing and go. And maybe if it's me or you playing around with some Vibe coding tool and just creating a little app for myself, that's one thing. But when there's hundreds of people or thousands of people involved in that, it doesn't work in the same way. So it's, how can we engage all the context we already have, the processes we already have, accelerate them in an effective way. So everybody is looking at the real thing, and then humans are touching that real thing and refining that real thing rather than abstractions.
Chris Strahl [00:17:53]:
I think the Vibe coding thing is fun to play on, right? Because it's obviously something that sort of captured the imaginations of people out on the Internet. And so when you think about Vibe coding, one of the things that got brought to me as a potential message is like, Knapsack's Vibe code for the enterprise. And I think that when you think about it in terms of Vibe code for the enterprise, what is the for the enterprise part of that really intended to talk about? Because there is this question of, hey, look, Cursor, Windsurf, all of the gentic frameworks that are out there, are you all going to go compete with them? Are you all going to go compete with Figma? And there's all these open questions about us in market as it relates to that. And you as the person running product here, your ability to understand how we relate to those systems is pretty paramount. And so when we think about that positioning and especially relative to agentic tools, how do you describe us?
Robin Cannon [00:18:46]:
I think the biggest thing is to be tool agnostic. So it's as much that we are providing context and can provide context so that other tools can effectively use that context in terms of the direction AI is going. Being able to understand specific contexts is really, really important. So that if you are creating, it's like, I want to create an app and I ask Cursor to make an app or make a page or whatever, and I do that without any context, then it's going to create something. And that might be cool or it might not be, it's non determinative. But if I can give it all the context in an enterprise environment of my design system and my regulatory environment, then what it creates is going to be much closer to the real thing that we needed.
Chris Strahl [00:19:35]:
So if you're thinking about this in the context of like, hey, look, there has to be an agnosticism, our position in the market is somewhere in this neighborhood that is not about canvases and not about the ability to do wholesale flowcharting, mood boarding, et cetera. But it does have this place where like, there's a bunch of digital product design work that you can do. And we have this place where like, we want to work with a bunch of these agentic tools. But we're not necessarily defining our own model. We're not necessarily doing this thing where we can say, hey, we're going to go compete directly with Cursor. How would you then define what we're doing? Because it sounds like it's something wholly different.
Robin Cannon [00:20:13]:
Yeah, there's two aspects to it. One is we have the potential to be able to cut out the steps in the product delivery process as it has been for decades. And I think even if you look at other things that are happening in this area at the moment, a lot of it is agentic tooling and teaching to just make those steps easier. But actually, I think, you know, the canvas is the perfect one. You could skip the canvas if you have this underlying understanding of context. So you ask Knapsack MCP that is aware of a particular enterprise's design system because you're working for that company. Company. I would like to create a new sign in page, then it's going to understand the context, it's going to help you deliver in code an initial, I don't even like to say prototype an initial iteration of that page.
Robin Cannon [00:21:11]:
That Designers and developers can then vibe upon as humans to make better and more refined to the point you can move much, much quicker in that initial delivery process. That also means you can much, much quicker in the iteration process as well.
Chris Strahl [00:21:27]:
That sounds a lot like leveraging Knapsack as a design system to provide context to some other sort of system. I think that's one aspect to it, but there's something more when you think about it in terms of, yes, this is context, and having an MCP server is great. And your ability to take all the stuff that exists inside of your design system, the discipline that lives there, and be able to bring that to other places. That's a really great step. But where are you ultimately seeing this? And I kind of want to understand, not just where does Knapsack get to you before the end of the year, but with this fundraise, how are we really living that vision of the future?
Robin Cannon [00:22:02]:
So when we live that vision of the future, we're creating, and I started off by calling it the AI product engine, and now I call it the intelligent product engine. Because agents don't need to be artificial or human, they can be either. But the idea being that you use that underlying knowledge of a particular enterprise's design system and potentially universal knowledge about a design system, and you deliver an iteration that is not just code. It doesn't just need developers to change. It's like, here is the product. You can view it in different ways, you can manipulate that product in different ways, you can deliver that product in different ways. This is the designers and product owners and developers. They can all be involved in the initial concept.
Robin Cannon [00:22:50]:
They can all be involved in the refinement before deployment. And it's fundamentally, whoever you are, if you have a product idea, you can deliver an iteration of that product that is the real thing to work on.
Evan Lovely [00:23:06]:
Yeah. I think that's what a lot of what our mission has always been. Right. Is that democratization of creation. Right. It's basically being able to get back to the thing I mentioned earlier, where we believe that since users experience your brand from code most of the time, that being able to create in there, and so you wouldn't want it to be like, oh, you must code to be able to create. That's a barrier to entry. Right.
Evan Lovely [00:23:28]:
And so being able to lower that barrier allows it. So different disciplines, different viewpoints, different people can be able to put out what they think should be up there.
Chris Strahl [00:23:39]:
Yeah.
Robin Cannon [00:23:39]:
And it's not just code as a barrier. It's if you have the ability to think of something and just be able to narrate what that thing is and what it should do. Then you can have something that is delivered that is close to, that is adherent to your idea in an enterprise environment, adherent to all of your enterprise guidelines and context, and work from that to ship the final product.
Chris Strahl [00:24:06]:
I love the idea of if you can think it, you can ship it.
Robin Cannon [00:24:08]:
Yes.
Chris Strahl [00:24:08]:
And I think that that's a pretty powerful concept where if you take a design system that you've built and a bunch of data sources that are associated with your products, so your git repositories, and then a bunch of things that are associated with your design, like your figma files, you can gather all that up and create a really great context. You can also have an engine that is constantly updating that context in the background, enriching it with other data, pulling in a bunch of all these other sources to build this really amazing base of raw materials. And then you should be able to compose something. You should be able to say, like, I have a product idea. I want to go solve this user's problem. This is how I want to solve it. And Knapshack should be able to make the first iteration of that for you, and it should be something that you could ship. Now, of course, you'll want to have people that are able to modify those control points, those contexts, to be able to refine that first brush at something.
Chris Strahl [00:25:01]:
And I also think that there's an interesting idea of what happens if you're just iterating on something that already exists. Right. So how does a big enterprise call up an existing experience, have an understanding that's automated of how the system they've built relates to that experience, and then allows them to modify it with prompts or modify it visually, directly in code?
Evan Lovely [00:25:21]:
Right.
Robin Cannon [00:25:21]:
And you're going to have legacy interfaces that maybe those teams or the company as a whole doesn't have the resources to create an audit. Maybe the design system or the design language or the brand has changed and now there's an opportunity to have composition advice, how to go about making changes, how to go about making improvements that you don't even necessarily need a human to be able to trigger. It's like, hey, these are the things in your product ecosystem that can be improved in particular ways. You still always have these human control touch points, but it doesn't necessarily need a human trigger. A request for advice.
Chris Strahl [00:26:04]:
When we think about this from a tangible perspective, when can people put hands on this? Like, when can they touch it? When can they experience it? Because I think there's so much excitement around this idea that the way that we build product is changing. AI is a big part of that change, but bringing that to enterprise is kind of coming fits and starts. And this is what we're going to go solve, right? This is our key premise as a business and, like, where we're headed. And so if I think about what six months in the future looks like, what are people going to be able to do with Knapsack six months from now? And how do we basically just say, like, look, you know, I guess in March, when we're looking back on this podcast, like, what promise should we have achieved?
Robin Cannon [00:26:43]:
I think Knapsack makes everybody a creator. I think whether you're a designer or a developer or a product owner, you can move your idea forward to something real. You can scale your ideas. You're not just scaling the discipline, you're scaling your idea forward. You're making your imagination real. So I think if you open up Knapsack, sure, you can see your design system, but you can ask Knapsack to create your idea. And you don't even need to know about your design system for it to build something that is brand adherent, design system adherent that you can touch and feel and start refining and moving around and then deploy it and ship it, and users can get it.
Evan Lovely [00:27:30]:
You know, there's several elements to this as well, where all of the knowledge that's inside your Knapsack workspace is also informing other AI workflows at the company, doing things outside of Knapsack. And one thing that's always kind of wild about AI is how did it come up with this answer? And by being able to have an area where people can edit that content that informs that AI, it's how people can be able to influence a lot of what AI does in other applications across enterprise.
Chris Strahl [00:28:01]:
So it sounds like the design system almost becomes more like this backend infrastructure where, like, yes, there's figma files and there's code that's been written in vs. Code that exists there that creates a bunch of data sources. But the layer on top of that is kind of what really matters. And that layer on top of that is feeding a context to whatever system you need it to, or you're actually able to create within that system directly and make whatever you want to make.
Robin Cannon [00:28:26]:
Design systems are infrastructure, and they need to be embedded infrastructure because they are ultimately a set of rules and guidelines. The problem is to create effectively with those rules and guidelines today, you need to know them. If we can get to the stage, which is what we're going to do, where you don't need to know those rules and guidelines in order to make successfully using them.
Chris Strahl [00:28:50]:
That's great. I love the idea of hey look, design systems are all this structure about what you make and how and so being able to leverage that in a way that works with AI, that works within a gentic workflow to just make the dang thing. That's pretty cool.
Robin Cannon [00:29:05]:
It's really fast as well.
Chris Strahl [00:29:07]:
Yeah. So like Evan, if people want to touch this or get involved early or see what this looks like from a conceptual standpoint, how do they do that?
Evan Lovely [00:29:14]:
Well, use knapsack in a workspace near you. So I think that basically that's going to be the main area obviously. And I fully expect our marketing team to have all sorts of YouTube clips as well and hosted demos. Fortunately, we are not like a self serve signup situation because we focus mainly on enterprise there. So I think that basically being able to see it the easiest way is either, you know, already being NASDAQ customer obviously or come to a lot of our like marketing events either virtually or in person.
Chris Strahl [00:29:44]:
Yeah. And I mean there's definitely a patterns event near you in a major city and so come on, try it out. I think also as Evan was mentioning, we're going to be hosting a series of events related to the work that we're doing here and so expect to be able to see it take shape over the next couple of weeks and months. I think that one of the things that is really interesting about this, that got me thinking as we were talking about intelligent product engine and about this vision for the future, the fundamental math here gets pretty crazy pretty quick. If you think about the idea of inside of a big enterprise company, you're able to take and compress or cut out all of these different steps in what the traditional product development process or lifecycle looks like. That changes a lot of the ways that we think about how we invest in our product ecosystem. And there's kind of two ways to think about that. There's the way of like, hey look, we can reduce costs, which is like a little bit in vogue right now.
Chris Strahl [00:30:35]:
But there's the other part of it is that we're onboarding this new capability where procs become much, much cheaper to make. And when you think about it in terms of that, you could make a lot more product or do a lot more with your product. And what I think that we're on our way towards in terms of these big enterprise product ecosystems is reimagining what a digital product really is for a user and where you meet them with it. Of course, we all carry agentic tools in our pockets now, where more and more search results include AI, more and more ways that we interact with include AI. What if we were able to build experiences that could travel with individual people? What if we were able to get into a point where we really start to think about a future, where we're able to build an experience that's unique to each user because they're so cheap and so fast to make. And that's where a lot of these kind of fundamental pieces of how we think about business start to break down is instead of just building this one monolithic application, we have this opportunity in front of us to really change the way that we think about what a product is. And I think that this kind of investment is really genuinely inevitable and getting to be at the forefront of it and a part of it is super exciting.
Robin Cannon [00:31:49]:
It's unavoidable because the numbers are so crazy. It goes beyond just, oh, we can make you 100 times more profitable. It's not that. It's not we can make you a hundred times more operationally efficient in terms of just spend. No, it's. We can make you a hundred times faster at doing stuff. And that means that you are able to do lots, lots more stuff. And different companies are going to be different things, but it Is, you know, UIs that are tailored to individual people or we're going to release every week and that's our new product cycle.
Robin Cannon [00:32:27]:
Not every quarter. Things like that change. Not just an industry change. Every industry that is delivering digital product.
Chris Strahl [00:32:36]:
Yeah. I think about this, as we've thought about AI as this series of experiments and in terms of real enterprise readiness for how you can take agentic products and really, truly vibe code for the enterprise. Everybody's sort of been lined up on the edge of this pool and the pool's kind of cold and there's been some concern about who jumps, but once one person jumps, it tends to be that everybody jumps at once. And I think that we've just started to watch the first couple of people really jump into this. And so I'm really excited for our future and our prospects and our way of attaching ourselves to this.
Evan Lovely [00:33:12]:
I'm excited to see more ideas get out into the world. I think that lowering that barrier of entry and getting more viewpoints out is going to be really exciting. Yeah.
Robin Cannon [00:33:23]:
Because I think people get scared of the idea of AI as a replacement for people. This is AI as an empowerment and an enabler of more people to do more things faster. It's going to make it more important that you have good ideas. It's going to make that last 5 or 10% of human refinement to what gets shipped more important because that's your differentiator. And I think that's what makes me really excited about it, is that this is AI to empower humans.
Chris Strahl [00:33:56]:
Well, looking forward to building this future with you all. If you want to check out more about it, come on over and visit us at Knapsack Cloud Go to Knapsack.cloud/Patterns if you want to attend one of our mini conferences in a city near you, look out for us because we're going to start showing up everywhere. Well, this has been the Design Systems Podcast. It's been great to have you on. Evan Robin, thanks for your time. Looking forward to chatting more soon. Have a great day everybody.
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