Season 3
|
Episode 2
How Loom design went 0 to 1 on their new AI product
Loom
Design Team
Oct 12, 2023
Oct 12, 2023
|
49 min
49 min
music by Dennis
About this Episode
In this episode we get to go backstage with the design team at Loom! They teach us all about their design process and share takeaways from their recent AI launch including stories about:
Prototyping and researching early concepts
Collaborating with engineers and other cross-functional teams
Using Figjam to gather feedback live
Developing a visual language for AI
Documenting edge cases and all the potential user states
Pivoting mid project 👀
Learn more about Loom AI and you can also connect with Sean Thompson, Sarah Olushoga, Helen Jing, and Sean Goodwin from the Loom design team ✌️
Deep Dives
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Free lessons from the top designers 👇
Fonz Morris
Lead monetization designer @ Netflix
Mia Blume
Past leader @ Pinterest, Square
Jorn van Dijk
CEO @ Framer
Femke
Design lead @ Gusto
Kenny Chen
UX lead @ Google
Join 8K+ designers
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HC
HC
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Deep Dives
Get every episode
Free lessons from 👇
Fonz Morris
Lead designer @ Netflix
Mia Blume
Past leader @ Pinterest, Square
Femke
Design lead @ Gusto
Kenny Chen
UX lead @ Google
Join 8K+ designers
HC
HC
HC
Deep Dives
Get every episode
Free lessons from the top designers 👇
Fonz Morris
Lead monetization designer @ Netflix
Mia Blume
Past leader @ Pinterest, Square
Jorn van Dijk
CEO @ Framer
Femke
Design lead @ Gusto
Kenny Chen
UX lead @ Google
Join 8K+ designers
HC
HC
HC
HC
Transcript chapters
Meet the team
Sean Thomson: Hey, my name is Sean Thompson. Really excited to be here and talk about, , Loom AI with, with this crew specifically. And I'm based in, uh, Boulder, Colorado,
Sarah: hey, I am Sarah. I am a brand designer on the team and I was originally born in Houston, Texas, but I've kind of bounced around the world since then. So I'm currently in Charlotte, North Carolina and yeah, looking forward to talking to you all about just the visual branding of Lume Eye.
Sean Good: Hey, y'all. My name is Sean. I'm a staff product designer here at loom. Um, I'm based out of Washington, D. C. And just really excited to chat today. There was a lot of great work that went into this project.
Helen: Hello, my name is Helen Jing. I'm a staff user researcher on the Loom Design team. I'm currently based in San Francisco and also very excited to chat. I think Loom Design is a very user oriented team. So, I think we'll get into that later.
Ridd: Amazing, well, thank you everyone for joining, it's a little bit of a different format, but. I think loom AI is like one of my favorite product releases that has happened in the design [00:01:00] community lately. So I wanted to just get the story. And I think a goal of this conversation is to help people almost just be like a fly on the wall to see how it worked.
What were some of the challenges that you overcame and, you know, trying to pull different takeaways out that they can apply to their own team. So let's start by going all the way back to the beginning. Take us to those very, very early conversations where you were first kind of tossing around these ideas and trying to figure out what your AI play was.
Meet the team
Sean Thomson: Hey, my name is Sean Thompson. Really excited to be here and talk about, , Loom AI with, with this crew specifically. And I'm based in, uh, Boulder, Colorado,
Sarah: hey, I am Sarah. I am a brand designer on the team and I was originally born in Houston, Texas, but I've kind of bounced around the world since then. So I'm currently in Charlotte, North Carolina and yeah, looking forward to talking to you all about just the visual branding of Lume Eye.
Sean Good: Hey, y'all. My name is Sean. I'm a staff product designer here at loom. Um, I'm based out of Washington, D. C. And just really excited to chat today. There was a lot of great work that went into this project.
Helen: Hello, my name is Helen Jing. I'm a staff user researcher on the Loom Design team. I'm currently based in San Francisco and also very excited to chat. I think Loom Design is a very user oriented team. So, I think we'll get into that later.
Ridd: Amazing, well, thank you everyone for joining, it's a little bit of a different format, but. I think loom AI is like one of my favorite product releases that has happened in the design [00:01:00] community lately. So I wanted to just get the story. And I think a goal of this conversation is to help people almost just be like a fly on the wall to see how it worked.
What were some of the challenges that you overcame and, you know, trying to pull different takeaways out that they can apply to their own team. So let's start by going all the way back to the beginning. Take us to those very, very early conversations where you were first kind of tossing around these ideas and trying to figure out what your AI play was.
Early conversations
Helen: There are kind of two simultaneous tracks, if you will, led by design and research and I can speak to the research happening before, uh, well, The research happening that led up to some of this work. So, um, I guess like in H2 of 2022, I had done an audit of the creator and viewer experiences with Loom, mainly to understand, you know, how users are using Loom as a tool and to understand their pain points and key inefficiencies in their [00:02:00] workflows.
And I think our learnings there really We're very powerful in that way. We understood that creators, many of our creators have this emphasis on efficiency of communication you're not really titling your videos. You're not really sending out much And I think the interesting consequence of that is that the creator who's recording these rooms directly impacts the viewing experience. And so there are many viewers who shared with us that they're experiencing the pain of like, This, my teammate is sending me this loom.
I don't really know what it's about. Um, should I watch it now? How urgent is it? And what is sort of the context around this loom? What do I need to do as a result of this loom being sent to me? And I think that research highlighted just this direct link between creators and viewers and the various pains born inefficiencies in their workflows.
Sean Thomson: Um, I, I Think another thing that was going on as well is, you know, AI was very much, you know, the talk of the industry when we, when we were thinking about this or starting to think about this, but I think we weren't [00:03:00] necessarily sure, like, what our play was at first, and, um, there were a variety of things that, that led to, to the work, but I think one thing that I reflected on was actually just some conversations on, um, on Twitter or X or whatever we call it, but, uh, I actually saw some parents of, of, uh, children in school who are from neurodiverse backgrounds talking about how Loom actually is this, this like huge win for, for their children, uh, from a communication standpoint and, um, kind of reflected on that and thought about, you know, using Loom even myself, um, and how it's really empowered my ability to influence organizations, you know, what if everyone could, could use it in an effective way.
And I think.
I started thinking about, um, you know, what, what could we do to a loom to really help someone? Um, we have this advantage that live live, um, forums don't have where we can do all this processing. We can [00:04:00] really help someone look and sound their best maybe. And that, that was kind of the, the initial pitch, like, Hey, like how far could we go?
Um, you know, with things like generative AI, with things like generative AI long term in the video space, so not just impacting text around it, which, which we've certainly invested in, but longer term, like, what can we even do to the video itself? Um, and that just turned into a lot of, a lot of great conversations.
Our CEO was really bought in. I actually pitched it to him via Slack, um, had my partner read it before, like, does this sound crazy? Um, and he, and he was, you know, he was super pumped. So we actually called it, um, initially it was called Communications Assistance, and the idea was exactly what I described, like, how can we help someone almost see a recording of themselves, and they don't believe it's them, because it's like, wow, I just sound so good.
Early conversations
Helen: There are kind of two simultaneous tracks, if you will, led by design and research and I can speak to the research happening before, uh, well, The research happening that led up to some of this work. So, um, I guess like in H2 of 2022, I had done an audit of the creator and viewer experiences with Loom, mainly to understand, you know, how users are using Loom as a tool and to understand their pain points and key inefficiencies in their [00:02:00] workflows.
And I think our learnings there really We're very powerful in that way. We understood that creators, many of our creators have this emphasis on efficiency of communication you're not really titling your videos. You're not really sending out much And I think the interesting consequence of that is that the creator who's recording these rooms directly impacts the viewing experience. And so there are many viewers who shared with us that they're experiencing the pain of like, This, my teammate is sending me this loom.
I don't really know what it's about. Um, should I watch it now? How urgent is it? And what is sort of the context around this loom? What do I need to do as a result of this loom being sent to me? And I think that research highlighted just this direct link between creators and viewers and the various pains born inefficiencies in their workflows.
Sean Thomson: Um, I, I Think another thing that was going on as well is, you know, AI was very much, you know, the talk of the industry when we, when we were thinking about this or starting to think about this, but I think we weren't [00:03:00] necessarily sure, like, what our play was at first, and, um, there were a variety of things that, that led to, to the work, but I think one thing that I reflected on was actually just some conversations on, um, on Twitter or X or whatever we call it, but, uh, I actually saw some parents of, of, uh, children in school who are from neurodiverse backgrounds talking about how Loom actually is this, this like huge win for, for their children, uh, from a communication standpoint and, um, kind of reflected on that and thought about, you know, using Loom even myself, um, and how it's really empowered my ability to influence organizations, you know, what if everyone could, could use it in an effective way.
And I think.
I started thinking about, um, you know, what, what could we do to a loom to really help someone? Um, we have this advantage that live live, um, forums don't have where we can do all this processing. We can [00:04:00] really help someone look and sound their best maybe. And that, that was kind of the, the initial pitch, like, Hey, like how far could we go?
Um, you know, with things like generative AI, with things like generative AI long term in the video space, so not just impacting text around it, which, which we've certainly invested in, but longer term, like, what can we even do to the video itself? Um, and that just turned into a lot of, a lot of great conversations.
Our CEO was really bought in. I actually pitched it to him via Slack, um, had my partner read it before, like, does this sound crazy? Um, and he, and he was, you know, he was super pumped. So we actually called it, um, initially it was called Communications Assistance, and the idea was exactly what I described, like, how can we help someone almost see a recording of themselves, and they don't believe it's them, because it's like, wow, I just sound so good.
Initial research + prototypes
Ridd: I mean, that all sounds really exciting. And I think the jump that is difficult for me to make as someone actually who was in a similar position where AI [00:05:00] came out and I'm like, Oh my gosh, how do we incorporate this into? How did you go from high level vision to actually figuring out what's possible?
And maybe you could talk a little bit about what some of those early explorations look like.
Sean Thomson: , I mean, one thing, um, to really get that early signal, and to get quickly from vision to something more practical, especially, this is a startup environment, we're moving fast.
Um, vision is... It's days, not months, um, of, of works, usually. Um, so we, we kind of transitioned from this, this high level vision of communication assistance for all to these practical ideas, um, around, uh, like what could we possibly do today and then, like, what's maybe a stretch, you know, but we still want to learn about it and, and we partnered with research to do so.
So we came up with concepts around. Uh, there was AI coaching, so like, you know, what if we listen to a recording and we tell you after, like, what could be better, um, what's great, [00:06:00] um, and then we did auto chapters, auto titles, auto summaries, which you've seen, um, we've talked about filler word removal, uh, silence removal with customers, and further out we've talked to customers about being able to just edit video via text, so, you know, if you, if you say, if you say something and you want to say it differently, what if you could just type, so.
We package those all as like really high fidelity concepts to put in front of customers super early.
Helen: Yeah. And as Sean mentioned, we had various rounds of UXR validation. So I think even just the earliest steps were before the holidays back at end of 2022. My research manager, Margie, actually partnered with Sean to take some of the earliest concepts like auto titles, chapters, um, you know, like communication assistance, as he mentioned.
And really, just to, to gut check with users, do these resonate? Do they not? Like, are we headed in a totally wrong direction? Um, but we did get a lot [00:07:00] of positive signal. I think, in particular, users thought that having that automated context could be such a powerful add to their workflows, in terms of efficiency gains, which I think relates to what we were saying earlier.
Sean Thomson: Another really important thing early was, I think, I think some folks have been really interested that Loom's AI play was actually like very research and design centric.
Um, versus it being a very technical play. Um, that said, um, collaboration with Eng was just like so critical. Um, just like learning, like learning what, what was feasible, what could be our first experiment, what needed more time. Like for example, doing a lot of the editing of the video via text. It turns out it needs a lot of time.
Um, it's really hard to, to get right. Um, but we were really confident with things like auto titles and summaries. And we, and we had. I'm not confident that there would be a high impact. It actually turned out to be, as little as we thought it was, in terms of our first [00:08:00] step, it actually turned out to be like our biggest metric mover.
Um, and I think the reason for that is like what Helen touched on from a research perspective. There's just so many folks out there sharing stuff, but then they're not contextualizing. They're not telling people like, hey, I need you to watch this for this reason. This is why it's relevant to you. And that really hurts their ability to get viewers, so.
Um, that, that project really just helped them immediately start to get more viewers.
Ridd: One of the things that I'm curious about is like, if we go back to some of those interviews. My gut is that a lot of it probably was pretty exciting for the people that you're talking to because it's like all of these shiny new AI features and things are happening that previously literally were not possible to do, at least at scale.
So how did you narrow down this list of all of the shiny experiments that? Show some level of promise to ultimately, like finalize this road map and maybe even know where to draw the line for that [00:09:00] initial closed beta release.
Initial research + prototypes
Ridd: I mean, that all sounds really exciting. And I think the jump that is difficult for me to make as someone actually who was in a similar position where AI [00:05:00] came out and I'm like, Oh my gosh, how do we incorporate this into? How did you go from high level vision to actually figuring out what's possible?
And maybe you could talk a little bit about what some of those early explorations look like.
Sean Thomson: , I mean, one thing, um, to really get that early signal, and to get quickly from vision to something more practical, especially, this is a startup environment, we're moving fast.
Um, vision is... It's days, not months, um, of, of works, usually. Um, so we, we kind of transitioned from this, this high level vision of communication assistance for all to these practical ideas, um, around, uh, like what could we possibly do today and then, like, what's maybe a stretch, you know, but we still want to learn about it and, and we partnered with research to do so.
So we came up with concepts around. Uh, there was AI coaching, so like, you know, what if we listen to a recording and we tell you after, like, what could be better, um, what's great, [00:06:00] um, and then we did auto chapters, auto titles, auto summaries, which you've seen, um, we've talked about filler word removal, uh, silence removal with customers, and further out we've talked to customers about being able to just edit video via text, so, you know, if you, if you say, if you say something and you want to say it differently, what if you could just type, so.
We package those all as like really high fidelity concepts to put in front of customers super early.
Helen: Yeah. And as Sean mentioned, we had various rounds of UXR validation. So I think even just the earliest steps were before the holidays back at end of 2022. My research manager, Margie, actually partnered with Sean to take some of the earliest concepts like auto titles, chapters, um, you know, like communication assistance, as he mentioned.
And really, just to, to gut check with users, do these resonate? Do they not? Like, are we headed in a totally wrong direction? Um, but we did get a lot [00:07:00] of positive signal. I think, in particular, users thought that having that automated context could be such a powerful add to their workflows, in terms of efficiency gains, which I think relates to what we were saying earlier.
Sean Thomson: Another really important thing early was, I think, I think some folks have been really interested that Loom's AI play was actually like very research and design centric.
Um, versus it being a very technical play. Um, that said, um, collaboration with Eng was just like so critical. Um, just like learning, like learning what, what was feasible, what could be our first experiment, what needed more time. Like for example, doing a lot of the editing of the video via text. It turns out it needs a lot of time.
Um, it's really hard to, to get right. Um, but we were really confident with things like auto titles and summaries. And we, and we had. I'm not confident that there would be a high impact. It actually turned out to be, as little as we thought it was, in terms of our first [00:08:00] step, it actually turned out to be like our biggest metric mover.
Um, and I think the reason for that is like what Helen touched on from a research perspective. There's just so many folks out there sharing stuff, but then they're not contextualizing. They're not telling people like, hey, I need you to watch this for this reason. This is why it's relevant to you. And that really hurts their ability to get viewers, so.
Um, that, that project really just helped them immediately start to get more viewers.
Ridd: One of the things that I'm curious about is like, if we go back to some of those interviews. My gut is that a lot of it probably was pretty exciting for the people that you're talking to because it's like all of these shiny new AI features and things are happening that previously literally were not possible to do, at least at scale.
So how did you narrow down this list of all of the shiny experiments that? Show some level of promise to ultimately, like finalize this road map and maybe even know where to draw the line for that [00:09:00] initial closed beta release.
Determining the right scope
Sean Good: Because we're a startup, like we're looking at other startups in the industry, and we're seeing a lot of people come out with their own product suites, their own A.
I add ons or integrations. And so I do think that we felt like a little bit of pressure, both like internally from are we pushing ourselves enough to releasing the right features for customers? Um, as well as like from investors to make sure that like, we really hit this, um, technological wave where we needed to.
I'm mixing metaphors. Um, yeah. And so we needed to come to a compromise of what felt like the right level of investment to make inside of these features, uh, to provide enough value to customers where they would feel like it would be worth paying for. Um, one of the packaging decisions here was to pursue like an add on model.
I think it was the right decision in a lot of ways because not everyone's going to be comfortable with. Automatic AI in our product and with the way that we were trying to improve creators hygiene on their own videos, like a lot of the power and the features was the [00:10:00] automatic nature. And so having multiple UXR rounds, getting some early validation on what customers would find most valuable in their own, like workflow and tool stack.
Uh, we were able to align on a group of features, the features that we shipped to GA, um, as our sort of like first wave of. introducing AI to loom. Um, I will say, like, that was definitely not, uh, an obvious thing. Like we had to arrive at what felt like the right amount of package, which ended up being six features that we shipped out.
Um, at the time that we'd made that decision, I think that we had built two and a half. And so there was quite a lot of work in front of us and it was sort of a big challenge and a big commitment. Um, and one of the projects we had planned to release for GA, um, was previously slated for being released after we, uh, launched LumiEye.
And so, there was also a lot of collaboration, just keeping the scopes really tight. And, um, I think from design [00:11:00] and research especially, we stuck pretty close to a definition of like, minimum lovable product. Like, how do we get this thing that feels complete, that feels like it is... valuable and that people really like using it in loom, um, without just shipping out a product that we felt wasn't at a high enough quality bar.
Determining the right scope
Sean Good: Because we're a startup, like we're looking at other startups in the industry, and we're seeing a lot of people come out with their own product suites, their own A.
I add ons or integrations. And so I do think that we felt like a little bit of pressure, both like internally from are we pushing ourselves enough to releasing the right features for customers? Um, as well as like from investors to make sure that like, we really hit this, um, technological wave where we needed to.
I'm mixing metaphors. Um, yeah. And so we needed to come to a compromise of what felt like the right level of investment to make inside of these features, uh, to provide enough value to customers where they would feel like it would be worth paying for. Um, one of the packaging decisions here was to pursue like an add on model.
I think it was the right decision in a lot of ways because not everyone's going to be comfortable with. Automatic AI in our product and with the way that we were trying to improve creators hygiene on their own videos, like a lot of the power and the features was the [00:10:00] automatic nature. And so having multiple UXR rounds, getting some early validation on what customers would find most valuable in their own, like workflow and tool stack.
Uh, we were able to align on a group of features, the features that we shipped to GA, um, as our sort of like first wave of. introducing AI to loom. Um, I will say, like, that was definitely not, uh, an obvious thing. Like we had to arrive at what felt like the right amount of package, which ended up being six features that we shipped out.
Um, at the time that we'd made that decision, I think that we had built two and a half. And so there was quite a lot of work in front of us and it was sort of a big challenge and a big commitment. Um, and one of the projects we had planned to release for GA, um, was previously slated for being released after we, uh, launched LumiEye.
And so, there was also a lot of collaboration, just keeping the scopes really tight. And, um, I think from design [00:11:00] and research especially, we stuck pretty close to a definition of like, minimum lovable product. Like, how do we get this thing that feels complete, that feels like it is... valuable and that people really like using it in loom, um, without just shipping out a product that we felt wasn't at a high enough quality bar.
Getting alignment internally
Ridd: And I think it's a good point because one of the things I was curious about was how much you were looking at other tools. Cause I can think of a couple of tools where it did feel like they kind of just slapped something on there and it didn't really integrate cohesively with the product. You mentioned the decision of Having it be a separate add on, I'd like to return to that.
Cause I think there's a whole conversation we can have there. I'm also curious, like, man, one of the most difficult parts of stewarding a project of this size and this level of potential impact is just making sure that people are aligned and not even the people in this room, but like other key stakeholders, CEO, things like that in those early days.
Can you talk about some of the key? [00:12:00] Checkpoints where you had to make sure that there was alignment in order to ensure that everyone was on the same page and moving in the right direction.
Sean Thomson: Um, I, I think, uh, our VP of Design, Christina, really kind of took charge with regards to Um, I think we, we really wanted this to be for the loom design team, a, uh, just an effort that really took advantage of the many skill sets we have.
Um, and, and kind of work towards this common goal, which was a new muscle for us, I would say. Um, we actually, Rajiv, one of the designers who isn't here, um, was really excited and proposed this idea of, um, like a summer release. Um, and, and company got really excited about that idea and actually started. Um, like for example, Rajiv and I had worked on a redesign of our recorder that took longer than expected, but we actually decided instead of shipping it separately to bundle it in to really make this an exciting launch.
Um, so a lot of things happened last minute, but there was a lot of coordination too from our, uh, our VP of design and this group.
Sean Good: yeah, the, [00:13:00] the other thing that I would say there is that in the midst of the project, it is really challenging to be working with like six or seven other designers who are all touching different facets of the work, um, from thinking about like. Hey, what's beyond the GA launch like Sean and Rajeev were doing a lot of work just thinking about these things that are going to take more investment and time, like, what are we actually building toward?
And I think that helped clear a path, not only just for like our North stars, but also to understand, based on the decisions that we have to make today, the trade offs given technical constraints or product limitations or finance, um, you know, what are we marching toward? And so, uh, of the parts about this project that I love the most is like just how integrated like brand was throughout the whole process.
And even though we were making decisions based on like core product experience, we were also able to loop in like, uh, our design and research, Crystal and Tiff from the billing team. Um, there was so much [00:14:00] alignment happening early on that it made keeping frequent and regular syncs on the calendar and in our Slack channels like a habit.
And. I think, like, we learned a lot of lessons about communicating to, like, a pretty large team. I think we were at around, like, 40 people working on this, um, at one point in the project. Um, but I would say that, like, it was a better, it was a better project as a result of that early alignment. And it allowed us to move a lot faster, because even though we felt a little behind, um, to the AI wave, we were able to, like, ship something really high quality and complete, um, in a non trivial amount of time.
Sarah: My favorite part of this project in general was just how just to see all the different teams like hop on Weekly syncs and stand ups. I think there was a point We have like four or five different AI specific meetings on the calendar and it sounded overwhelming at first But we quickly realized when it was needed and it was important and then from a brand perspective like having to [00:15:00] create an identity for one AI which is like a It's still confusing to me, like personally, um, but creating an identity for this as it was moving, like the ship was still being built.
We're still putting the pieces together and trying to brand it. It was challenging, but it was also fun because we were all in there together just throwing in all the pieces and trying to figure it out and trying to create something that felt unique to Loom as a brand, but also aligned very closely with like our principles, you know.
Um. And I think we did a pretty good job of getting there. And I just, I look forward to how we're going to continue to push it with more features coming out, um, throughout the year.
Sean Thomson: I think it was one of those scenarios where we were seeing designs for the landing page and like how to represent removing filler words and we were like, Oh, like, could our motion designer do like a micro interaction like that in the product or, you know, things like that.
So it was, it was a great, um, it was just great that we established that [00:16:00] relationship early because there were just like a lot of dividends that that happened.
Getting alignment internally
Ridd: And I think it's a good point because one of the things I was curious about was how much you were looking at other tools. Cause I can think of a couple of tools where it did feel like they kind of just slapped something on there and it didn't really integrate cohesively with the product. You mentioned the decision of Having it be a separate add on, I'd like to return to that.
Cause I think there's a whole conversation we can have there. I'm also curious, like, man, one of the most difficult parts of stewarding a project of this size and this level of potential impact is just making sure that people are aligned and not even the people in this room, but like other key stakeholders, CEO, things like that in those early days.
Can you talk about some of the key? [00:12:00] Checkpoints where you had to make sure that there was alignment in order to ensure that everyone was on the same page and moving in the right direction.
Sean Thomson: Um, I, I think, uh, our VP of Design, Christina, really kind of took charge with regards to Um, I think we, we really wanted this to be for the loom design team, a, uh, just an effort that really took advantage of the many skill sets we have.
Um, and, and kind of work towards this common goal, which was a new muscle for us, I would say. Um, we actually, Rajiv, one of the designers who isn't here, um, was really excited and proposed this idea of, um, like a summer release. Um, and, and company got really excited about that idea and actually started. Um, like for example, Rajiv and I had worked on a redesign of our recorder that took longer than expected, but we actually decided instead of shipping it separately to bundle it in to really make this an exciting launch.
Um, so a lot of things happened last minute, but there was a lot of coordination too from our, uh, our VP of design and this group.
Sean Good: yeah, the, [00:13:00] the other thing that I would say there is that in the midst of the project, it is really challenging to be working with like six or seven other designers who are all touching different facets of the work, um, from thinking about like. Hey, what's beyond the GA launch like Sean and Rajeev were doing a lot of work just thinking about these things that are going to take more investment and time, like, what are we actually building toward?
And I think that helped clear a path, not only just for like our North stars, but also to understand, based on the decisions that we have to make today, the trade offs given technical constraints or product limitations or finance, um, you know, what are we marching toward? And so, uh, of the parts about this project that I love the most is like just how integrated like brand was throughout the whole process.
And even though we were making decisions based on like core product experience, we were also able to loop in like, uh, our design and research, Crystal and Tiff from the billing team. Um, there was so much [00:14:00] alignment happening early on that it made keeping frequent and regular syncs on the calendar and in our Slack channels like a habit.
And. I think, like, we learned a lot of lessons about communicating to, like, a pretty large team. I think we were at around, like, 40 people working on this, um, at one point in the project. Um, but I would say that, like, it was a better, it was a better project as a result of that early alignment. And it allowed us to move a lot faster, because even though we felt a little behind, um, to the AI wave, we were able to, like, ship something really high quality and complete, um, in a non trivial amount of time.
Sarah: My favorite part of this project in general was just how just to see all the different teams like hop on Weekly syncs and stand ups. I think there was a point We have like four or five different AI specific meetings on the calendar and it sounded overwhelming at first But we quickly realized when it was needed and it was important and then from a brand perspective like having to [00:15:00] create an identity for one AI which is like a It's still confusing to me, like personally, um, but creating an identity for this as it was moving, like the ship was still being built.
We're still putting the pieces together and trying to brand it. It was challenging, but it was also fun because we were all in there together just throwing in all the pieces and trying to figure it out and trying to create something that felt unique to Loom as a brand, but also aligned very closely with like our principles, you know.
Um. And I think we did a pretty good job of getting there. And I just, I look forward to how we're going to continue to push it with more features coming out, um, throughout the year.
Sean Thomson: I think it was one of those scenarios where we were seeing designs for the landing page and like how to represent removing filler words and we were like, Oh, like, could our motion designer do like a micro interaction like that in the product or, you know, things like that.
So it was, it was a great, um, it was just great that we established that [00:16:00] relationship early because there were just like a lot of dividends that that happened.
How Loom pivoted mid-project
Ridd: I like to think of design, especially on these kind of 0 to 1 projects as. Almost just like moving at the front of the ship with a little flashlight, or maybe you're in a cave and you're just kind of exploring, like trying to identify, like, what even are the doors that we should be considering as a team?
I've never worked on a project with 40 people with flashlights. And so everyone's kind of like discovering and finding these different paths and different opportunities on their own to an extent and kind of reporting back. I would imagine that leads to. A lot of like little micro pivots or, um, seeing something else that somebody is working on and trying to incorporate it into like your own little slice of the feature set.
So maybe can you talk a little bit about times where maybe strategies changed or evolved or maybe as you were iterating, you ended up going down a direction that you didn't initially think you would.
Sean Thomson: I think one thing we noticed was before we really formed [00:17:00] into this, um, like highly functioning, like multi team entity, um, like early, um, we were, we were doing a lot of AI features in isolation, I would say.
And, um, I think. Because we started to, um, to form as a team, we started to realize, like, what that experience would feel like if we didn't start to, um, like, work together a lot more closely. So, for example, um, a lot of the features you see represented as Loom AI in one area were kind of appearing in multiple places.
Like, oh, we updated the title, so we're going to tell you about that. Or we changed the chapter, we're going to tell you about that. And I think, I think a few of us started to realize, like, okay, this is starting to feel like... You know, we're working separately, which we are, um, so how can we make this feel like, you know, this cohesive experience that gives people confidence, because that's the whole point of it, um, by appearing in one spot, and I think we all got really excited about that, and, um, [00:18:00] Shanji and others, like, really took it to the finish line and, and took that, that idea, I think, of, like, how can we help people understand everything that's happening, um, in one place.
So that was a big pivot.
Sean Good: Yeah, that's so true. Um, Sean, when you talk about that, it reminds me that the, the way that we were thinking about the AI suite of features was just like a list of features and it took some convincing to get a, uh, like a design solution presented and resourced where. We could, we could give these features to users in a way that was like holistic, um, sort of centralized on the page as well.
And we were working a lot in silos. Um, I think that we had heard a lot of different like user insights, uh, through Helen's research, especially. Um, one particular one that I think led to a lot of those, you know, we should present Loom AI as a home conversations was the idea that. For many creators, [00:19:00] especially newer creators, our own editing tools were actually not very discoverable.
There were a lot of people, like a significant amount of people that didn't even realize Loom had any editing tools. And we were about to start automatically editing their video. And so, it was a really good opportunity to look at sort of our foundation of the page, and simplify some of the things that we knew that people didn't really use a lot of.
And instead, like, use that space to really present, um, Illume. ai and our launch in a way to someone that would be, um, cohesive and part of one story. And you knew that you could feel a little bit more control, in control with this new technology if you had everything, like, visible to you immediately as soon as you stopped recording.
Um. So I would say that like right around that moment is when the team started working a lot more closely because now we had a like internally we had a goal of presenting this cohesively [00:20:00] and That allowed teams to work together a lot more closely to figure out For this feature. I'm building like how it be represented.
What's it gonna look like in the end to end? When's the first time someone will see it? How do I access more control or deeper levels like for tasks you have to go through a review step? Um And I'm happy about that structure too, because it's paving a path toward like more advanced editing features. Um, like Sean was sort of peaking a little bit earlier.
Sean Thomson: I think when you get designers and researchers with very different, um, experience, expertise, et cetera, um, together, um, the product gets a lot better. So for example, we, I feel like we had more flashlights because we had that early vision to like, think about like.
Like, oh, this doesn't feel like the early vision. Like, one of the pitches was, like, how can we be a camera crew for everyone? Um, and it's like, oh, this doesn't feel like that. Um, or, you know, I think Sean, you had a really, um, you know, tight grasp on, like, how the share page was designed. Um, the, the page that everyone sees with the [00:21:00] video on it.
So, how can we, like, build into that in an elegant way that people understand? And, um, and, like, what do our customers care about? Like, Helen, you know, always advocating for that.
Sean Good: It's a great point. I actually have like a huge shout out to Kevin for, uh, yeah, Kevin Yan. He's a product designer here. Um, he was the designer on a feature that we didn't think would ship to GA, auto tasks. And he got really creative and did a lot of like iterations on how we would leverage the existing front end architecture of the page, specifically our comments architecture.
to build tasks into the product that felt like a consolidated view of your activity on the page. Um, but also, like, managed to get that in pre launch. And so, it was a really scrappy way of building that allowed us to get value out sooner to users and took a lot of resourcefulness. Okay. Um,
Sean Thomson: Yeah, plus one. We weren't sure that was going to ship, and I think they just doubled down on quality and, like, shipping, like, are these tasks useful to you? Like, on a weekly basis, and we were [00:22:00] like, oh man, I feel bad for Kevin and team, but that's, that's what you have to do with this kind of work, I think. I think everyone's experienced that.
It's, it's new frontier.
Ridd: It's really interesting to hear some of the changes that came out of. Thinking about it maybe as separate features and like one holistic release and even the extent to which it impacted like the primary architecture on that main share editing page,
like those are big changes. If you're editing like the core layouts on the screen, what does it look like for you to get that in front of the rest of the team and how are you stewarding that process?
Sean Good: , one thing. In general, the loom design and research team loves is like feedback from customers. And so, uh, because we are building a product that we all use daily, like there is a relentless feedback loop. And this comes from multiple places. Uh, this comes from like dog fooding aggressively our product.
And so we have a lot of feedback channels in the company. Um, we use Slack. So, uh, a lot of feedback [00:23:00] channels in Slack to be able to report things that different people are seeing. Throwing new experiences out to the company and getting feedback from power users like almost instantaneously at times With this particular release one new thing that we did was releasing Certain features to like a beta group and so we knew that this was a bit of a nascent technology And we were inviting users who were excited about that into sort of like the back room To be able to test and get early feedback from users I think that this was really Because with a standard feature that you're building, you can, you can typically glean a lot from the sort of data or like qualitative user interviews, um, that you're, that you're running, uh, and after you ship, of course, you have like a lot of metrics to, to look at and to analyze, but because we are using AI to generate outputs from user content.
We needed like real world people using this thing in [00:24:00] their work lives to be able to tell us whether or not we were making that quality bar at an acceptable level. And so like a really good example of this is our third AI feature that we built, auto chapters. In the midst of this project, we were shipping out updates to our AI beta group, getting feedback from people on the quality level, and it helped us identify, um, basically like a processing issue with the way that our transcription pipeline works with our OpenAI API, um, where the second half of the video is basically like one big chapter in a lot of cases.
Being able to test early with real customers in their work, um, very early before we launched this out to everybody gave us indications where we should spend a little bit more time on like prompt quality here and make sure that we actually have something suitable that comfortable shipping out to every single customer.
Ridd: You mentioned the beta group and I was one of the [00:25:00] early people, I guess, to get access to this because I remember it kind of just came out of left field and I saw this thing and it was so cool and the first thing I noticed was there was some kind of unique interactions. Some of the animations I hadn't seen before.
It was a little bit more gradient heavy even than like the typical UI that you all would ship. Can you talk to me a little bit about how the visual language for this feature set? Emerged and how you thought about fitting that within the larger loom brand.
Sarah: I'll definitely say we, We went through a couple of iterations. We explored a few different directions, some a bit bolder than others, I would say. But at the core, I think we all knew that we wanted to land on a visual style that felt that we were true to loom and like I said to our principles, um, and the goal of looming eyes essentially like to make the recording process a bit easier and allow users to be a bit more productive and efficient.
So we really wanted to communicate the ease of it all with like the softer pastel colors, [00:26:00] the floating dimensional bubbles, which are also a nod to the camera bubble that is very specific to loom. Um, but through all of the explorations, I would definitely say like. There was a lot of like looking at what other companies are doing and knowing that we didn't exactly fit in that mold of the dark, vibrant purple, like that's already our brand color.
And so it was like, how do we create an identity for this add on end product that feels a bit different to create enough contrast, but also close enough to feel like a part of the Loon brand.
Ridd: It's interesting to think about like being in your shoes, because like I said, like every tool was racing to ship something in this space. How'd you think about where to kind of break from the path and, and maybe go a different direction than some of the other tools.
Sarah: It's so funny that you asked that because I think we spent like a third or maybe even half of the time while working on the visual identity was spent on the [00:27:00] mark exploration, like We're not gonna do the Sparkle because everyone else is doing it.
So we need to try something totally different. And I think like if I look through my files today, I probably have like 75 different mark options. Some that were just like, you know, just trying to explore different things because we knew that we wanted to set ourselves apart. And in one of those feedback, um, in those reviews with our CEO actually, he reached back out and was like, I don't understand why we're trying to...
Be so different here, and it took me a second to get it, but then it hit me and I was like, wait, like this sparkle is actually what everyone is so familiar with, and I don't think that this is our opportunity to try to veer off or try to be different. AI in itself is already so new, and a lot of people are still trying to understand it, and if this is the only moment we have to like, Create that familiarity.
Let's stick to that. But then we can bring in our brand and that spice through the other elements like the gradients and the bubbles. And there's just so many other opportunities to go [00:28:00] wild. But I think having that mark remain true to what users are already so used to seeing was very, very crucial.
Sean Thomson: Yeah, I think it's also like one of those classic design challenges where it's like, how do you bring people in by showing them something familiar and then challenge them? Like, like, hey, like, yes, this is AI, but what does that mean in the context of Bloom, right? And I think that's, that's where we, we could shine.
How Loom pivoted mid-project
Ridd: I like to think of design, especially on these kind of 0 to 1 projects as. Almost just like moving at the front of the ship with a little flashlight, or maybe you're in a cave and you're just kind of exploring, like trying to identify, like, what even are the doors that we should be considering as a team?
I've never worked on a project with 40 people with flashlights. And so everyone's kind of like discovering and finding these different paths and different opportunities on their own to an extent and kind of reporting back. I would imagine that leads to. A lot of like little micro pivots or, um, seeing something else that somebody is working on and trying to incorporate it into like your own little slice of the feature set.
So maybe can you talk a little bit about times where maybe strategies changed or evolved or maybe as you were iterating, you ended up going down a direction that you didn't initially think you would.
Sean Thomson: I think one thing we noticed was before we really formed [00:17:00] into this, um, like highly functioning, like multi team entity, um, like early, um, we were, we were doing a lot of AI features in isolation, I would say.
And, um, I think. Because we started to, um, to form as a team, we started to realize, like, what that experience would feel like if we didn't start to, um, like, work together a lot more closely. So, for example, um, a lot of the features you see represented as Loom AI in one area were kind of appearing in multiple places.
Like, oh, we updated the title, so we're going to tell you about that. Or we changed the chapter, we're going to tell you about that. And I think, I think a few of us started to realize, like, okay, this is starting to feel like... You know, we're working separately, which we are, um, so how can we make this feel like, you know, this cohesive experience that gives people confidence, because that's the whole point of it, um, by appearing in one spot, and I think we all got really excited about that, and, um, [00:18:00] Shanji and others, like, really took it to the finish line and, and took that, that idea, I think, of, like, how can we help people understand everything that's happening, um, in one place.
So that was a big pivot.
Sean Good: Yeah, that's so true. Um, Sean, when you talk about that, it reminds me that the, the way that we were thinking about the AI suite of features was just like a list of features and it took some convincing to get a, uh, like a design solution presented and resourced where. We could, we could give these features to users in a way that was like holistic, um, sort of centralized on the page as well.
And we were working a lot in silos. Um, I think that we had heard a lot of different like user insights, uh, through Helen's research, especially. Um, one particular one that I think led to a lot of those, you know, we should present Loom AI as a home conversations was the idea that. For many creators, [00:19:00] especially newer creators, our own editing tools were actually not very discoverable.
There were a lot of people, like a significant amount of people that didn't even realize Loom had any editing tools. And we were about to start automatically editing their video. And so, it was a really good opportunity to look at sort of our foundation of the page, and simplify some of the things that we knew that people didn't really use a lot of.
And instead, like, use that space to really present, um, Illume. ai and our launch in a way to someone that would be, um, cohesive and part of one story. And you knew that you could feel a little bit more control, in control with this new technology if you had everything, like, visible to you immediately as soon as you stopped recording.
Um. So I would say that like right around that moment is when the team started working a lot more closely because now we had a like internally we had a goal of presenting this cohesively [00:20:00] and That allowed teams to work together a lot more closely to figure out For this feature. I'm building like how it be represented.
What's it gonna look like in the end to end? When's the first time someone will see it? How do I access more control or deeper levels like for tasks you have to go through a review step? Um And I'm happy about that structure too, because it's paving a path toward like more advanced editing features. Um, like Sean was sort of peaking a little bit earlier.
Sean Thomson: I think when you get designers and researchers with very different, um, experience, expertise, et cetera, um, together, um, the product gets a lot better. So for example, we, I feel like we had more flashlights because we had that early vision to like, think about like.
Like, oh, this doesn't feel like the early vision. Like, one of the pitches was, like, how can we be a camera crew for everyone? Um, and it's like, oh, this doesn't feel like that. Um, or, you know, I think Sean, you had a really, um, you know, tight grasp on, like, how the share page was designed. Um, the, the page that everyone sees with the [00:21:00] video on it.
So, how can we, like, build into that in an elegant way that people understand? And, um, and, like, what do our customers care about? Like, Helen, you know, always advocating for that.
Sean Good: It's a great point. I actually have like a huge shout out to Kevin for, uh, yeah, Kevin Yan. He's a product designer here. Um, he was the designer on a feature that we didn't think would ship to GA, auto tasks. And he got really creative and did a lot of like iterations on how we would leverage the existing front end architecture of the page, specifically our comments architecture.
to build tasks into the product that felt like a consolidated view of your activity on the page. Um, but also, like, managed to get that in pre launch. And so, it was a really scrappy way of building that allowed us to get value out sooner to users and took a lot of resourcefulness. Okay. Um,
Sean Thomson: Yeah, plus one. We weren't sure that was going to ship, and I think they just doubled down on quality and, like, shipping, like, are these tasks useful to you? Like, on a weekly basis, and we were [00:22:00] like, oh man, I feel bad for Kevin and team, but that's, that's what you have to do with this kind of work, I think. I think everyone's experienced that.
It's, it's new frontier.
Ridd: It's really interesting to hear some of the changes that came out of. Thinking about it maybe as separate features and like one holistic release and even the extent to which it impacted like the primary architecture on that main share editing page,
like those are big changes. If you're editing like the core layouts on the screen, what does it look like for you to get that in front of the rest of the team and how are you stewarding that process?
Sean Good: , one thing. In general, the loom design and research team loves is like feedback from customers. And so, uh, because we are building a product that we all use daily, like there is a relentless feedback loop. And this comes from multiple places. Uh, this comes from like dog fooding aggressively our product.
And so we have a lot of feedback channels in the company. Um, we use Slack. So, uh, a lot of feedback [00:23:00] channels in Slack to be able to report things that different people are seeing. Throwing new experiences out to the company and getting feedback from power users like almost instantaneously at times With this particular release one new thing that we did was releasing Certain features to like a beta group and so we knew that this was a bit of a nascent technology And we were inviting users who were excited about that into sort of like the back room To be able to test and get early feedback from users I think that this was really Because with a standard feature that you're building, you can, you can typically glean a lot from the sort of data or like qualitative user interviews, um, that you're, that you're running, uh, and after you ship, of course, you have like a lot of metrics to, to look at and to analyze, but because we are using AI to generate outputs from user content.
We needed like real world people using this thing in [00:24:00] their work lives to be able to tell us whether or not we were making that quality bar at an acceptable level. And so like a really good example of this is our third AI feature that we built, auto chapters. In the midst of this project, we were shipping out updates to our AI beta group, getting feedback from people on the quality level, and it helped us identify, um, basically like a processing issue with the way that our transcription pipeline works with our OpenAI API, um, where the second half of the video is basically like one big chapter in a lot of cases.
Being able to test early with real customers in their work, um, very early before we launched this out to everybody gave us indications where we should spend a little bit more time on like prompt quality here and make sure that we actually have something suitable that comfortable shipping out to every single customer.
Ridd: You mentioned the beta group and I was one of the [00:25:00] early people, I guess, to get access to this because I remember it kind of just came out of left field and I saw this thing and it was so cool and the first thing I noticed was there was some kind of unique interactions. Some of the animations I hadn't seen before.
It was a little bit more gradient heavy even than like the typical UI that you all would ship. Can you talk to me a little bit about how the visual language for this feature set? Emerged and how you thought about fitting that within the larger loom brand.
Sarah: I'll definitely say we, We went through a couple of iterations. We explored a few different directions, some a bit bolder than others, I would say. But at the core, I think we all knew that we wanted to land on a visual style that felt that we were true to loom and like I said to our principles, um, and the goal of looming eyes essentially like to make the recording process a bit easier and allow users to be a bit more productive and efficient.
So we really wanted to communicate the ease of it all with like the softer pastel colors, [00:26:00] the floating dimensional bubbles, which are also a nod to the camera bubble that is very specific to loom. Um, but through all of the explorations, I would definitely say like. There was a lot of like looking at what other companies are doing and knowing that we didn't exactly fit in that mold of the dark, vibrant purple, like that's already our brand color.
And so it was like, how do we create an identity for this add on end product that feels a bit different to create enough contrast, but also close enough to feel like a part of the Loon brand.
Ridd: It's interesting to think about like being in your shoes, because like I said, like every tool was racing to ship something in this space. How'd you think about where to kind of break from the path and, and maybe go a different direction than some of the other tools.
Sarah: It's so funny that you asked that because I think we spent like a third or maybe even half of the time while working on the visual identity was spent on the [00:27:00] mark exploration, like We're not gonna do the Sparkle because everyone else is doing it.
So we need to try something totally different. And I think like if I look through my files today, I probably have like 75 different mark options. Some that were just like, you know, just trying to explore different things because we knew that we wanted to set ourselves apart. And in one of those feedback, um, in those reviews with our CEO actually, he reached back out and was like, I don't understand why we're trying to...
Be so different here, and it took me a second to get it, but then it hit me and I was like, wait, like this sparkle is actually what everyone is so familiar with, and I don't think that this is our opportunity to try to veer off or try to be different. AI in itself is already so new, and a lot of people are still trying to understand it, and if this is the only moment we have to like, Create that familiarity.
Let's stick to that. But then we can bring in our brand and that spice through the other elements like the gradients and the bubbles. And there's just so many other opportunities to go [00:28:00] wild. But I think having that mark remain true to what users are already so used to seeing was very, very crucial.
Sean Thomson: Yeah, I think it's also like one of those classic design challenges where it's like, how do you bring people in by showing them something familiar and then challenge them? Like, like, hey, like, yes, this is AI, but what does that mean in the context of Bloom, right? And I think that's, that's where we, we could shine.
Designing the upgrade flow
Ridd: How concretely were you defining what success looks like for this project?
Sean Good: I thought we had a pretty concrete measurement of success, which was, uh, money. And so, like our, our core metric was. Because of our add on pricing structure, we wanted to create like X amount of dollars in net new ARR. And it's, it's sometimes a little challenging to use, you know, what's, what's sometimes an output metric revenue as your goal.
Um, knowing also that like the features that we would launch would substantially change the way that people [00:29:00] would engage on our, uh, on our product. But I do think that given... Given the pricing and packaging discussions, given the fact that this was a lot of new functionality that just wasn't possible even six months ago in our product, um, focusing on like how much value people would find out of the feature set that we launched, questioning people about that very early on in Helen's research, and then also taking that all the way through as a measurement to understand, Hey, are people, um, are people getting enough value out of this where they can pay?
Ridd: What about during that closed beta where you actually weren't charging people though? Maybe you could talk a little bit about some of the key things you learned during the closed beta and how that impacted the design.
Helen: During the beta. We weren't charging for anything. And so I think what was really critical was looking at engagement with the features. Um, so first and foremost, like our users using these features, are they editing the automated output? I think both engagement and [00:30:00] accuracy.
Of the output was really top of mind because as we know, you know, AI is not always perfect It's still a new technology And so that was very very top of mind and I think we are really grateful That our beta members were so open and so excited about these features to give us valuable feedback So we could continue to improve the quality of these features so that it would increase the likelihood to engage and also, um metrics loom is very very metrics driven.
So not only money, but One metric that we care a lot about is what we call video first views. And so our hypotheses were that if we add context to these, um, If we add automated context to Loom videos, then the viewers receiving the videos would be like, oh, I know what this video is about, I know that it applies to me, and might be more willing to watch them.
So, you know, video first views and also subsequent engagement with those videos, like whether that's commenting, emoji reactions, and stuff like that. All of those we were [00:31:00] keeping pulses on, like a hawk.
Ridd: let's talk about that upgrade flow now, because kind of everything that you have done and like, it's a pretty big appetite project. You've invested a lot into it. None of it really matters if people aren't going to hit that pay button because it is an add on.
So I'd love to learn more about. The process and how you approached that upgrade flow and some of the different things that you tried, maybe some of the explorations that didn't work, like, how'd you get from, okay, we need to make money with this to what the flow looks like today.
Sean Good: One thing that's maybe helpful to note as a consideration for designing the upgrade flows. We have different tiers and then of course we had a business trial as well. And now we were adding a second, different type of trial, um, to free and business plans. And so, a lot of the upgrade journeys and purchase experiences were really customized based on your account tier.
And [00:32:00] many of the moments, especially, um, the like visually expressive moments were really considered like end to end. What's it look like when someone purchases? Signs up for Loom, goes through an onboarding experience, and then gets hit with Loom AI features for the first time. Or what does it look like if you've been using Loom for like years, and you record like 30 videos a month, and now AI features start appearing on your video?
Um, those two are pretty extreme examples of like, someone who might go through an upgrade flow, and need to see different things at different times. Um, and there's also going to be the case with AI, because of the way our... Package is structured that someone doesn't want to pay for it. And so what's a good way to give them a little bit of it in a usage based trial and then sort of turn down the volume if we know that somebody doesn't want to upgrade either because they don't trust the technology yet or because it's not relevant to them or they just don't need to at this time.
And so, uh, I would say that like one thing that really benefited all of these [00:33:00] different flows was that myself working on the core product experience of that. Centralized interface where you can see all of your AI features was done and signed in parallel with how crystal was working through all of these different upgrade flows.
And so it did mean that there was a lot of collaboration and some very rapid iteration, but it also meant that one could inform the other and we weren't locking ourselves into a design that wouldn't work for like an enterprise request flow where someone can't even decide to upgrade. They need to admin.
Um. And so I would just say like huge shout out to the team there because there was a lot of research that informed that, um, all the way down to how someone selects the add on in a payment flow, um, to, you know, the very first time that we present these features to a user, like for our, um, we call it an F talks, but a first time modal that someone sees on launch.
Ridd: I think one of the most difficult parts of a project like this [00:34:00] is just keeping track of all of those different states that you mentioned and things that like maybe feel like edge cases, but to that user, like that's their default experience. Can you talk a little bit about how you manage that internally at Loom, just to make sure that you're not overlooking any specific type of user or some kind of a state that maybe is not primary, but still really important.
Sean Good: You bring up a great point. Like there's just so much to consider. We're adding like this additional layer across like many parts of our product and like leadership wanted to be sure that we were considering like the full end to end flow, which was the right instinct.
Like we were changing many pieces of our product. We need visibility. And so Crystal and I worked on, I guess it's sort of like a. like a wire flow diagram. It allowed us to put all of the different screens across all of the different account flows and trial based flows where you were onboarding all the way through to a full fledged paying customer with blue may I on every [00:35:00] video.
Um, and we set it up in a way that it made it a lot more tractable for all the stakeholders to get in, see Where does somebody come from on this particular screen? Where do they go to? What happens if they opt in or out of this particular control? And I felt like it made our feedback, like, way more effective because people had a full view of that journey.
And so they were able to understand, Oh, you know, a new user might see this, while a power user might see this, and then evaluate based on that user context. So... I think that while the creation of like a huge diagram map is not appropriate for every project for this one, just due to the amount of states that we had to cover was, was really helpful in just making the system visible.
Sean Thomson: The, the other thing I'll add is, um, just, just a huge thing that helped us, um, ship this in a, in a coherent manner that considered all of the, the various, um, edge cases, or like you're saying, [00:36:00] like primary use cases for some people was just, um, Sean mentioned this earlier, but we truly do dog food loom a lot.
It's one of the most fascinating things, honestly, of any company I've joined, is how much loom uses loom. Uh, we, we use it so much that we don't actually use email at all. Um,
we've
Ridd: That's a superpower for a design team. That's
Sean Thomson: yeah, yeah, we're just like, cool, we're not gonna use this, we're gonna use this instead. It has its pitfalls, but I think what's cool about it.
Is, we're just always very tuned into like, is it working for me? Like, we're acting like users a lot. Um, so you'll see our feedback channels just slammed with, with feedback. Like, hey, this isn't working for me in this particular context. Um, whereas I've worked other places. Um, where it's like people don't even use Twitter and they work there.
Which is fine, it's a big company. But, um, everybody uses Loom. I think that helped a lot. Um, another thing, and Sean touched on this, um, our product and edge counterparts. had a very sophisticated QA [00:37:00] process, like every edge case, every consideration that I could never think of, um, considered.
There's like a fun story with our QA. Um, so as you can imagine, there was a lot of time constraint here. We, we had set a big launch date of August 29th and we were doing everything possible to make that happen. And the QA like Sean was talking about was extensive because we had to trial all of these different flows and.
Consider which parts of the experience were built and which weren't, and some of the experiences that you would see wouldn't even happen until you recorded videos four or five times. And so, um, a lot of like product and engineering work was just getting to a spot where our staging and our admin tools could allow more people to come into that system and stress test everything.
And a fun moment, um, happened toward the end of the project where we as a full design team and also a full leadership team with like our C suite. came together, got everybody into [00:38:00] staging, which was a little bit of a journey, and used FigJam to be able to get everybody's, like, feedback, from very minute, like, copy changes to, hey, like, this thing just looks broken.
Um, and we did some, like, fun team awards through that as well. Um, the Caveman Award, I think, is my favorite one. It's how, how did you even break that? Like, what, what even happened? What did you do? But a really cool moment for the design team was taking all that feedback and having only like two days to be able to turn around solutions that would have to be built and then triaged and pushed to prod.
And instead of like Crystal Ma and I going into a cave and designing 20 different solutions, we used our live critique time the next day to bring together the whole team and jam on solutions for these 20 different high priority problems to solve. And we were able to solve them in like two hours. And I mean, Sean, you were there as well.
And it was a super collaborative effort bringing [00:39:00] in everyone that had a little or a lot of context and sort of working together to like get these things over the line and unblock our engineering partners.
Designing the upgrade flow
Ridd: How concretely were you defining what success looks like for this project?
Sean Good: I thought we had a pretty concrete measurement of success, which was, uh, money. And so, like our, our core metric was. Because of our add on pricing structure, we wanted to create like X amount of dollars in net new ARR. And it's, it's sometimes a little challenging to use, you know, what's, what's sometimes an output metric revenue as your goal.
Um, knowing also that like the features that we would launch would substantially change the way that people [00:29:00] would engage on our, uh, on our product. But I do think that given... Given the pricing and packaging discussions, given the fact that this was a lot of new functionality that just wasn't possible even six months ago in our product, um, focusing on like how much value people would find out of the feature set that we launched, questioning people about that very early on in Helen's research, and then also taking that all the way through as a measurement to understand, Hey, are people, um, are people getting enough value out of this where they can pay?
Ridd: What about during that closed beta where you actually weren't charging people though? Maybe you could talk a little bit about some of the key things you learned during the closed beta and how that impacted the design.
Helen: During the beta. We weren't charging for anything. And so I think what was really critical was looking at engagement with the features. Um, so first and foremost, like our users using these features, are they editing the automated output? I think both engagement and [00:30:00] accuracy.
Of the output was really top of mind because as we know, you know, AI is not always perfect It's still a new technology And so that was very very top of mind and I think we are really grateful That our beta members were so open and so excited about these features to give us valuable feedback So we could continue to improve the quality of these features so that it would increase the likelihood to engage and also, um metrics loom is very very metrics driven.
So not only money, but One metric that we care a lot about is what we call video first views. And so our hypotheses were that if we add context to these, um, If we add automated context to Loom videos, then the viewers receiving the videos would be like, oh, I know what this video is about, I know that it applies to me, and might be more willing to watch them.
So, you know, video first views and also subsequent engagement with those videos, like whether that's commenting, emoji reactions, and stuff like that. All of those we were [00:31:00] keeping pulses on, like a hawk.
Ridd: let's talk about that upgrade flow now, because kind of everything that you have done and like, it's a pretty big appetite project. You've invested a lot into it. None of it really matters if people aren't going to hit that pay button because it is an add on.
So I'd love to learn more about. The process and how you approached that upgrade flow and some of the different things that you tried, maybe some of the explorations that didn't work, like, how'd you get from, okay, we need to make money with this to what the flow looks like today.
Sean Good: One thing that's maybe helpful to note as a consideration for designing the upgrade flows. We have different tiers and then of course we had a business trial as well. And now we were adding a second, different type of trial, um, to free and business plans. And so, a lot of the upgrade journeys and purchase experiences were really customized based on your account tier.
And [00:32:00] many of the moments, especially, um, the like visually expressive moments were really considered like end to end. What's it look like when someone purchases? Signs up for Loom, goes through an onboarding experience, and then gets hit with Loom AI features for the first time. Or what does it look like if you've been using Loom for like years, and you record like 30 videos a month, and now AI features start appearing on your video?
Um, those two are pretty extreme examples of like, someone who might go through an upgrade flow, and need to see different things at different times. Um, and there's also going to be the case with AI, because of the way our... Package is structured that someone doesn't want to pay for it. And so what's a good way to give them a little bit of it in a usage based trial and then sort of turn down the volume if we know that somebody doesn't want to upgrade either because they don't trust the technology yet or because it's not relevant to them or they just don't need to at this time.
And so, uh, I would say that like one thing that really benefited all of these [00:33:00] different flows was that myself working on the core product experience of that. Centralized interface where you can see all of your AI features was done and signed in parallel with how crystal was working through all of these different upgrade flows.
And so it did mean that there was a lot of collaboration and some very rapid iteration, but it also meant that one could inform the other and we weren't locking ourselves into a design that wouldn't work for like an enterprise request flow where someone can't even decide to upgrade. They need to admin.
Um. And so I would just say like huge shout out to the team there because there was a lot of research that informed that, um, all the way down to how someone selects the add on in a payment flow, um, to, you know, the very first time that we present these features to a user, like for our, um, we call it an F talks, but a first time modal that someone sees on launch.
Ridd: I think one of the most difficult parts of a project like this [00:34:00] is just keeping track of all of those different states that you mentioned and things that like maybe feel like edge cases, but to that user, like that's their default experience. Can you talk a little bit about how you manage that internally at Loom, just to make sure that you're not overlooking any specific type of user or some kind of a state that maybe is not primary, but still really important.
Sean Good: You bring up a great point. Like there's just so much to consider. We're adding like this additional layer across like many parts of our product and like leadership wanted to be sure that we were considering like the full end to end flow, which was the right instinct.
Like we were changing many pieces of our product. We need visibility. And so Crystal and I worked on, I guess it's sort of like a. like a wire flow diagram. It allowed us to put all of the different screens across all of the different account flows and trial based flows where you were onboarding all the way through to a full fledged paying customer with blue may I on every [00:35:00] video.
Um, and we set it up in a way that it made it a lot more tractable for all the stakeholders to get in, see Where does somebody come from on this particular screen? Where do they go to? What happens if they opt in or out of this particular control? And I felt like it made our feedback, like, way more effective because people had a full view of that journey.
And so they were able to understand, Oh, you know, a new user might see this, while a power user might see this, and then evaluate based on that user context. So... I think that while the creation of like a huge diagram map is not appropriate for every project for this one, just due to the amount of states that we had to cover was, was really helpful in just making the system visible.
Sean Thomson: The, the other thing I'll add is, um, just, just a huge thing that helped us, um, ship this in a, in a coherent manner that considered all of the, the various, um, edge cases, or like you're saying, [00:36:00] like primary use cases for some people was just, um, Sean mentioned this earlier, but we truly do dog food loom a lot.
It's one of the most fascinating things, honestly, of any company I've joined, is how much loom uses loom. Uh, we, we use it so much that we don't actually use email at all. Um,
we've
Ridd: That's a superpower for a design team. That's
Sean Thomson: yeah, yeah, we're just like, cool, we're not gonna use this, we're gonna use this instead. It has its pitfalls, but I think what's cool about it.
Is, we're just always very tuned into like, is it working for me? Like, we're acting like users a lot. Um, so you'll see our feedback channels just slammed with, with feedback. Like, hey, this isn't working for me in this particular context. Um, whereas I've worked other places. Um, where it's like people don't even use Twitter and they work there.
Which is fine, it's a big company. But, um, everybody uses Loom. I think that helped a lot. Um, another thing, and Sean touched on this, um, our product and edge counterparts. had a very sophisticated QA [00:37:00] process, like every edge case, every consideration that I could never think of, um, considered.
There's like a fun story with our QA. Um, so as you can imagine, there was a lot of time constraint here. We, we had set a big launch date of August 29th and we were doing everything possible to make that happen. And the QA like Sean was talking about was extensive because we had to trial all of these different flows and.
Consider which parts of the experience were built and which weren't, and some of the experiences that you would see wouldn't even happen until you recorded videos four or five times. And so, um, a lot of like product and engineering work was just getting to a spot where our staging and our admin tools could allow more people to come into that system and stress test everything.
And a fun moment, um, happened toward the end of the project where we as a full design team and also a full leadership team with like our C suite. came together, got everybody into [00:38:00] staging, which was a little bit of a journey, and used FigJam to be able to get everybody's, like, feedback, from very minute, like, copy changes to, hey, like, this thing just looks broken.
Um, and we did some, like, fun team awards through that as well. Um, the Caveman Award, I think, is my favorite one. It's how, how did you even break that? Like, what, what even happened? What did you do? But a really cool moment for the design team was taking all that feedback and having only like two days to be able to turn around solutions that would have to be built and then triaged and pushed to prod.
And instead of like Crystal Ma and I going into a cave and designing 20 different solutions, we used our live critique time the next day to bring together the whole team and jam on solutions for these 20 different high priority problems to solve. And we were able to solve them in like two hours. And I mean, Sean, you were there as well.
And it was a super collaborative effort bringing [00:39:00] in everyone that had a little or a lot of context and sort of working together to like get these things over the line and unblock our engineering partners.
Looking ahead and analyzing the competition
Ridd: What about looking forward? I mean, this is like a, a big moment in the product team's history to an extent. Like, you know, 40 people all working towards a collective release. I've looked at your website. There are a lot of coming soon features. What does this next season look like for Design at Loom?
Sean Thomson: I think what's really exciting is we're still bullish on this idea of like, what does a camera crew for everyone who uses loom look like, and I think to the company, this is very much a starting point, um, with a lot more to do. Um, and, and it's just, if you look at the range of competitors, both direct competitors and just people in the industry providing, uh, tools that help someone look, sound better, et cetera, um, there's a lot going on.
So I think, I, I think the future is, is us trying to get [00:40:00] our heads around some of this like emerging technology and, and see where it is most appropriate given all the extensive research we've done. Um, so I think you'll see editing for sure, um, being a big focus for the company. Um, an area, a growth area for us, um, like how can we really help someone who experiences Stage Fright feel like they are supported, not just because we're titling their looms and removing filler words, that is awesome, but how can we, like, really go far with that, um, so that's, that's a big, big, big area for us, I would say.
Helen: And to add a little bit to why we're focusing on editing. Um, one insight that has emerged at loom is that our users are spending a lot of time re recording their looms. You know, even if you intend to record a five minute loom, some people have a higher, um, Threshold for perfection. And so they might find themselves spending 20 minutes, 30 minutes just to record that five minute loom.
And, um, what we've learned through some of our power user [00:41:00] behaviors is that they've adopted these alternate ways of recording more efficiently. A lot of them lean on post record editing of their videos. So you might slip up, but it's totally fine. You can, you have the confidence knowing that you can go into his editing suite and sort of snip out that mistake and continue onwards.
And, um, I think many of our users are new to video. period. Not to mention video editing. And so a lot of what Sean Thompson and Rajiv have worked on recently is how can we make that editing experience be truly next generation, efficient, seamless, like much more intuitive to our users? And yeah, really, really excited for that to be rolled out and really to have an opportunity to maybe shift some of the mindset Mindsets and behaviors of how our users even think about recording a loom from start to finish.
Ridd: I think that's such an interesting point is it's almost like not as. [00:42:00] Problem oriented as other companies that I've worked at. Like, it's not like a user is going to come to you and be like, here are the three problems that I'm experiencing every time I record a loom. It's like you have to be savvy to identify the trends, but also to understand all of this technological advancement that's happening because all of these new things are possible.
And so having a, having a pulse on that, but then also you're in a really interesting. Industry too, where the people or the companies that are adjacent to you, everyone's kind of trying to vertically orient a little bit and eat more and more of the stack. How do you even think about that as a designer?
Like, do you feel this need to have more of a grasp of what's actually happening in the industry than previous roles or not so much?
Sean Thomson: I personally do, I mean, I think having previous experience was at Twitter, I think Twitter struggled to have direct competitors, if that makes sense, um, Whereas Loom, [00:43:00] there are many, many products that resemble Loom, um, that have less, less users or maybe more. Um, there's, there's things adjacent that aren't, you know, directly, like, competing, but certainly in the video space that we're constantly learning from.
I, I think, answer yes, like learning, like looking at competitors a lot more, looking, looking at, um, technology a lot more, um, because it's such an active space. Um, especially, I mean, I think for Loom, period, that's the case. And then, when you layer in, like, Oh, we're trying to make investments in this emerging area of, like, video based AI, Um, yeah, we'd be foolish not to be very, um, watchful.
Um, of, like, what's going on in the industry. How can we learn from them? How can we partner with them? Um, et cetera.
Sean Good: Yeah, I think that's one of the creative and challenging things about, like, the format that Loom excels at. Because at the end of the day, like, AI or [00:44:00] not, the user behaviors on our platform are, like, pretty same at the core. Um, and many of their use cases and needs, like, remain the same regardless of whether or not they're augmenting with AI or other technologies that may exist in the future.
But there's a lot of tension at figuring out, um, where, where Loom can go next. And like, that's part of the fun part of being a designer here because the culture is like very design driven. We have the autonomy to invent new concepts and show them to users very quickly. And everyone in the company has a lot of empathy for users because we all quite relentlessly.
Looking ahead and analyzing the competition
Ridd: What about looking forward? I mean, this is like a, a big moment in the product team's history to an extent. Like, you know, 40 people all working towards a collective release. I've looked at your website. There are a lot of coming soon features. What does this next season look like for Design at Loom?
Sean Thomson: I think what's really exciting is we're still bullish on this idea of like, what does a camera crew for everyone who uses loom look like, and I think to the company, this is very much a starting point, um, with a lot more to do. Um, and, and it's just, if you look at the range of competitors, both direct competitors and just people in the industry providing, uh, tools that help someone look, sound better, et cetera, um, there's a lot going on.
So I think, I, I think the future is, is us trying to get [00:40:00] our heads around some of this like emerging technology and, and see where it is most appropriate given all the extensive research we've done. Um, so I think you'll see editing for sure, um, being a big focus for the company. Um, an area, a growth area for us, um, like how can we really help someone who experiences Stage Fright feel like they are supported, not just because we're titling their looms and removing filler words, that is awesome, but how can we, like, really go far with that, um, so that's, that's a big, big, big area for us, I would say.
Helen: And to add a little bit to why we're focusing on editing. Um, one insight that has emerged at loom is that our users are spending a lot of time re recording their looms. You know, even if you intend to record a five minute loom, some people have a higher, um, Threshold for perfection. And so they might find themselves spending 20 minutes, 30 minutes just to record that five minute loom.
And, um, what we've learned through some of our power user [00:41:00] behaviors is that they've adopted these alternate ways of recording more efficiently. A lot of them lean on post record editing of their videos. So you might slip up, but it's totally fine. You can, you have the confidence knowing that you can go into his editing suite and sort of snip out that mistake and continue onwards.
And, um, I think many of our users are new to video. period. Not to mention video editing. And so a lot of what Sean Thompson and Rajiv have worked on recently is how can we make that editing experience be truly next generation, efficient, seamless, like much more intuitive to our users? And yeah, really, really excited for that to be rolled out and really to have an opportunity to maybe shift some of the mindset Mindsets and behaviors of how our users even think about recording a loom from start to finish.
Ridd: I think that's such an interesting point is it's almost like not as. [00:42:00] Problem oriented as other companies that I've worked at. Like, it's not like a user is going to come to you and be like, here are the three problems that I'm experiencing every time I record a loom. It's like you have to be savvy to identify the trends, but also to understand all of this technological advancement that's happening because all of these new things are possible.
And so having a, having a pulse on that, but then also you're in a really interesting. Industry too, where the people or the companies that are adjacent to you, everyone's kind of trying to vertically orient a little bit and eat more and more of the stack. How do you even think about that as a designer?
Like, do you feel this need to have more of a grasp of what's actually happening in the industry than previous roles or not so much?
Sean Thomson: I personally do, I mean, I think having previous experience was at Twitter, I think Twitter struggled to have direct competitors, if that makes sense, um, Whereas Loom, [00:43:00] there are many, many products that resemble Loom, um, that have less, less users or maybe more. Um, there's, there's things adjacent that aren't, you know, directly, like, competing, but certainly in the video space that we're constantly learning from.
I, I think, answer yes, like learning, like looking at competitors a lot more, looking, looking at, um, technology a lot more, um, because it's such an active space. Um, especially, I mean, I think for Loom, period, that's the case. And then, when you layer in, like, Oh, we're trying to make investments in this emerging area of, like, video based AI, Um, yeah, we'd be foolish not to be very, um, watchful.
Um, of, like, what's going on in the industry. How can we learn from them? How can we partner with them? Um, et cetera.
Sean Good: Yeah, I think that's one of the creative and challenging things about, like, the format that Loom excels at. Because at the end of the day, like, AI or [00:44:00] not, the user behaviors on our platform are, like, pretty same at the core. Um, and many of their use cases and needs, like, remain the same regardless of whether or not they're augmenting with AI or other technologies that may exist in the future.
But there's a lot of tension at figuring out, um, where, where Loom can go next. And like, that's part of the fun part of being a designer here because the culture is like very design driven. We have the autonomy to invent new concepts and show them to users very quickly. And everyone in the company has a lot of empathy for users because we all quite relentlessly.
Favorite parts of the design culture at Loom
Ridd: we've covered like a lot of ground and I'm really appreciative of just the lens that you've given us to really get a sense for what design at Loom is like. And I'd like to end by giving an opportunity to share a bit more about the culture and what makes Design at Loom special.
But I'm going to do so by creating a little hypothetical and maybe you won't like it [00:45:00] originally, but it'll be fun. I promise. Let's say, and I want to hear from each of you. Let's say that tomorrow you are leaving Loom and you're going to work at a different startup. What is an element of how design works at Loom that you would want to make sure to bring with you to that new company?
Sean Good: I've never been on a more collaborative team. People show work early and often. We're always jamming and inviting other people to do the same. And so that's something that's had a major impact on the way I work.
And Loom, of course, empowers that, because it allows you to share very quick and very often. Um, but I'll take that with me throughout the rest of my career.
Ridd: Can you double click on that a little bit?
What do you think makes so that, that kind of culture exists at Loom?
Sean Good: Yeah, I think that's a fair question. Um, at Loom, it's using Loom. You aren't just judged by... What artifact you send out to a Slack channel or post on a platform. [00:46:00] Um, and it is a challenging problem for designers because we, we put a thought of thought and effort into things. And so to get critical feedback can sometimes hurt a little bit at first, but with loom, like you're presenting yourself in a more human format, you can talk about the things that are sort of unresolved or the things that you're really confident in, or more easily direct, um, feedback at a particular area that you need.
And so. Specifically, I'll take Loom with me, as long as it exists as a product, anywhere I go. And I will, um, I will force everybody else around me to use it too. Because it's a great way of working distributed.
Helen: I think because we all care so much about the Design and Research Partnership, we are proactive about including A person on, you know that we see is left out on a calendar inviter list. Like I've definitely, you know, Sean Goodwin and Sean Thompson have both done that in situations where they're like, Hey, actually, you know, research should have a voice in this conversation.
And I feel like every single person on the loom design team has that same [00:47:00] sense of care and sense of ownership, which I really think helps a lot to make that collaboration much.
Sean Thomson: Another thing is, It's so nice to work at a company that is just hungry for design. Instead of, like, convincing people that they should be. Um, it's, it's definitely the vantage point I think we operate from where, um, We have a seat at the table, and it's like, it's on us to, like, use it wisely.
Um, and I think that's a really fun spot to be in. That's hard to find.
Sarah: I say this all the time to like even former co workers like the people here are top tier like everyone cares so much about loom as a product but also just about each other like everyone here said but also yeah like the crits on Thursdays and studio time on Friday and being able to share async like work for feedback.
Like there's just so many opportunities to share and I might not always share but I'm always so excited to like see what everyone else is doing and like leave feedback where I [00:48:00] find that I can or sometimes just observe and learn from the other designers. So the collaboration, 10 out of 10. The people, amazing.
Boom as a product, just great. There's just a lot to take from here.
Ridd: Well, I think that's like the perfect place to end it. You all are amazing, big fans of everything that you're doing at Loom. Thank you again for kind of just pulling back the curtain and letting other people see what it's like and what you're working on and. If you haven't checked it out already, I'm sure anyone listening to this is using Loom.
I would be shocked if you weren't, but go to Loom AI, like, play with it. It's pretty amazing. Honestly, the captions are, like, spectacular. And, yeah. Thanks again, everyone. It was wonderful to talk to you.
Sean Thomson: uh, thank you so much. Yeah, this was fun instead of scary, which that's awesome.
Favorite parts of the design culture at Loom
Ridd: we've covered like a lot of ground and I'm really appreciative of just the lens that you've given us to really get a sense for what design at Loom is like. And I'd like to end by giving an opportunity to share a bit more about the culture and what makes Design at Loom special.
But I'm going to do so by creating a little hypothetical and maybe you won't like it [00:45:00] originally, but it'll be fun. I promise. Let's say, and I want to hear from each of you. Let's say that tomorrow you are leaving Loom and you're going to work at a different startup. What is an element of how design works at Loom that you would want to make sure to bring with you to that new company?
Sean Good: I've never been on a more collaborative team. People show work early and often. We're always jamming and inviting other people to do the same. And so that's something that's had a major impact on the way I work.
And Loom, of course, empowers that, because it allows you to share very quick and very often. Um, but I'll take that with me throughout the rest of my career.
Ridd: Can you double click on that a little bit?
What do you think makes so that, that kind of culture exists at Loom?
Sean Good: Yeah, I think that's a fair question. Um, at Loom, it's using Loom. You aren't just judged by... What artifact you send out to a Slack channel or post on a platform. [00:46:00] Um, and it is a challenging problem for designers because we, we put a thought of thought and effort into things. And so to get critical feedback can sometimes hurt a little bit at first, but with loom, like you're presenting yourself in a more human format, you can talk about the things that are sort of unresolved or the things that you're really confident in, or more easily direct, um, feedback at a particular area that you need.
And so. Specifically, I'll take Loom with me, as long as it exists as a product, anywhere I go. And I will, um, I will force everybody else around me to use it too. Because it's a great way of working distributed.
Helen: I think because we all care so much about the Design and Research Partnership, we are proactive about including A person on, you know that we see is left out on a calendar inviter list. Like I've definitely, you know, Sean Goodwin and Sean Thompson have both done that in situations where they're like, Hey, actually, you know, research should have a voice in this conversation.
And I feel like every single person on the loom design team has that same [00:47:00] sense of care and sense of ownership, which I really think helps a lot to make that collaboration much.
Sean Thomson: Another thing is, It's so nice to work at a company that is just hungry for design. Instead of, like, convincing people that they should be. Um, it's, it's definitely the vantage point I think we operate from where, um, We have a seat at the table, and it's like, it's on us to, like, use it wisely.
Um, and I think that's a really fun spot to be in. That's hard to find.
Sarah: I say this all the time to like even former co workers like the people here are top tier like everyone cares so much about loom as a product but also just about each other like everyone here said but also yeah like the crits on Thursdays and studio time on Friday and being able to share async like work for feedback.
Like there's just so many opportunities to share and I might not always share but I'm always so excited to like see what everyone else is doing and like leave feedback where I [00:48:00] find that I can or sometimes just observe and learn from the other designers. So the collaboration, 10 out of 10. The people, amazing.
Boom as a product, just great. There's just a lot to take from here.
Ridd: Well, I think that's like the perfect place to end it. You all are amazing, big fans of everything that you're doing at Loom. Thank you again for kind of just pulling back the curtain and letting other people see what it's like and what you're working on and. If you haven't checked it out already, I'm sure anyone listening to this is using Loom.
I would be shocked if you weren't, but go to Loom AI, like, play with it. It's pretty amazing. Honestly, the captions are, like, spectacular. And, yeah. Thanks again, everyone. It was wonderful to talk to you.
Sean Thomson: uh, thank you so much. Yeah, this was fun instead of scary, which that's awesome.
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