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Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird)

42m 19s

Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird)

In this episode, John Kim, founder and CEO of Sandbird, demonstrates how his company is becoming an "AI-first" organization by treating AI adoption as a product. The core is an internal platform where employees can raise "quests"—requests for AI automations or tools. AI can now read quest specifications, create PRs, and start coding, alongside human engineers. This enables rapid innovation, as shown by the marketing team building a swag store (with a Konami code Easter egg) in a day without engineering support. The platform gamifies adoption: users earn experience points for completing quests, leading to rewards like gift cards or stage time to present builds. A skills marketplace lets teams share plugins (e.g., for recruiting or design) to avoid duplication. Key infrastructure includes pre-vetted app templates, security compliance, and knowledge guides (e.g., for GitHub), allowing non-technical staff to build safely. The company measures AI usage via a token consumption leaderboard and uses weekly stand-ups to showcase successes (e.g., recruiting automations). John emphasizes that innovation starts with curious, agency-driven employees, and that AI enables "failing forward" faster, making fun and creativity cheap to prioritize.

Transcription

7948 Words, 42935 Characters

English
Unleashing this power AI and giving it to the power of marketer salespeople, you get all these cool ideas that get rolled out rapidly to the market. It's taking someone's super creativity and giving them powers to deliver it to your customers. This is an internal platform where anyone in the company can raise their hand and create what we call the quest. When there's a quest AI can actually re-through the specification, create PRTs and start actually coding. Basically a marketplace of AI needs and AI builders inside your company where anybody can just pop in and say, "Oh, I think I know how to do that." So tell me a little bit about this dashboard. So what you're seeing here is the overall usage of our token and the company level. We measure AI causes somebody who spend more than 100 million tokens a day. What I love about this moment is I think it is just such a moment to learn things you could never learn before because the best teacher with the most in-depth knowledge and an endless willingness to go to research is right there at your fingertips. This is a beautiful time to fail forward and still get up and run faster than the other because innovation doesn't start from a pure theoretical structures. They start with people who have that energy and the story behind them. So find them. They're always in your organization and they really build energy around that. Welcome back to How I AI. I'm Clarevo, product leader and AI obsessive here on a mission to help you build better with these new tools. Today I have John Kim, founder and CEO of Sandbird and he's going to show us his AI token consumption leader board where everyone in the company is ranked from AI newbie to AI God. He's also going to show us how AI quests can be the key to company-wide adoption. Let's get to it. 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Join them and hundreds of other industry leaders at workOS.com. Start building today. John, I love what you're going to show us today because I tell people right now, they want to transform their company. They need to think of their team as a product. And what you're going to show us, little spoiler alert, for everybody excited to get into this episode is how you've turned AI adoption, not just into a program in your company, but a product. So tell me, what's your ambition for your team around the use of AI? We want to become the AF first company, and what we mean by that is not just to adopt AI as a tool, but how do we make AI as part of our workforce? So we're really trying to empower people and give them right set of information and tools. So the data himself can really harness the power of AI. And some of the things we are hopefully about to show you today will inspire people to do something similar. Yeah, and let's go to the outcomes because I think a lot of people that I talk to are trying to articulate the why behind adopting AI that goes beyond I would like you to do more with less. And that's a lot of what employees are hearing right now is just I want you to go faster. You can go faster. We should be able to do more and more and more. But I think what your team is building is showing a different benefit of of adopting AI and everybody becoming builder. So you want to jump in and show us some of the stuff that you all are building with AI, and then we'll back into how you got the team there. Welcome to a delight as shop is we're really excited about this. This is a swag store that really captures the culture and the energy of where our company is headed. The source called Big S. Energy is an agent as a service. And this entire store was built by our marketing team without engineering support. So you can actually buy really cool swag that are very timely. Actually I really did ask my team to make this my ass is bigger than your ass for the term is a stick. I think this is one of the most popular swaps we have right now. You can actually go and buy this. So our marketing team integrated stuff, strike integration. So yeah, we do charge a little bit of money. But I think it's going to be really cool. Another favorite context window I carry a lot. So imagine like unleashing this power of AI to your marketing team for this amazing creative energy. And instead of asking like your design team or you know, engineering to put this side together, they put this side together in matter of a day or two. And then it's now up and running. We also have a super secret easter egg. Look for those of gamers for the listening. If you do Konami code, up, down, down, left, right, left, right, B.A. And here's a little secret. So we are throwing a conference in May 7th called Delice Fart in San Francisco. It's got to be a really amazing conference bringing the CX leaders AI builder from all over the world. Be a people to inform and drop it. We'll be showing showcasing our future roadmap. So hopefully it will be a great chance to really learn about the cutting edge of AI. But also thinking through the lens of where's the future of customer experience going to look like. So this is what our marketing team has built together. I just need to stop and reflect. So we just had a really recent episode with Jason, Levin, the CEO of Memelord. And he said, let your marketers cook. That was his whole thesis, which is when marketers can be builders, they can build things that delight your customers and acquire them. And I just go back to like the before times. If marketing had this idea, it would be like, well, can we prioritize it? Is it worth investing engineering resources in? It's just for this event, the event's going to pass quickly. Just do something out of the box and you know, R CMS. And then you get this sort of like middleing experience for your customers, very mediocre, very like MVP experience for your customers. And now I think just looking at this, this store and the Easter egg and the way you get into the event, it's taking someone's super creativity and giving them powers to to deliver it to your customers. And this again is like the example of it's not about going faster. It's about having a bigger ambition and doing more honestly fun things. And I think this is underrated too, which is it's so hard to build like it's so hard to prioritize fun in your product. But when fun can be cheap, you should be more fun. So that's my thesis on why you should let marketers become come builders. And I'm sure they love it too, just from like a team engagement, you know, creativity perspective. Yeah, I love that because that's exactly what happened. Because imagine sitting in a room full of engineers and product leaders and say, hey, you know what? We have this cool idea. We want to add this to your product release cycle in roadmap. It's going to take you two sprints. I use gunner very hard. It's going to be very hard to get that on the table. But just like again, unleashing this power AI and getting it to the power of marketers salespeople, like you get all these cool ideas that get rolled out rapidly to the market. So very, very excited. Well, I would say that not every marketer though a year ago or two years ago was coding, although many more are now. So how did you get the team here? Like how did you manage the transition from classic marketing? Everything has to go to engineering to actually enabling teaching people how to use this product or how to use AI and then how to get what they wanted done in production. So to really help facilitate that transformation, we built out a platform called the Automator's Automator's platform. Now this website is particularly has been designed to just show you the demo today, but actually you can actually create a question on your own. So let's say you're a finance department. Hey, I want to automate my account receivable and count payable workflow. You can kind of do that. And then some other engineers can come in and help or if they're AI enabled, they can build it themselves. So just to give a couple of example, if you go to a completed list of quests, these are all the things that have been built or being pending. And then so let's say I use the quest then and there's usually a quest giver. So this person usually somebody raising their hands and hey, can you some can somebody help me build a customer account look up using kind of different workflows and other people like let me actually give you a hand. So two people actually teamed up to build out this workflow. And then the result is they usually submit either code repository or some kind of a skill, right. This video, you can see how to actually use those skills and for instance, internal workflow. So we kind of blurred it out, but you kind of get the idea, right? So you have this all these skills being built. Now on top of that, what we're just rolling out, this is like part of the press, I guess, or fresh out of the oven is when you create this kind of quest, you can actually now ask AI to build it too. So when there's a quest, AI can actually read through the specification, create PRTs and start actually coding. So this is the next level is alongside human engineers and team members. Now we have AI agents who are also helping us build automation workflows. To do that really is to help people also learn themselves to how to build these tools. So we have this internal guidelines that continue to get updated on a pretty much on a daily basis, teaching people how to set up Github, create new applications, and also internally we have created this app template where all the authentication and all the environments have already been set up. So what marketer or the CSM customer success manager has to do is they just extract the template and just build it on top of it and they don't have to think about the rest of the infrastructure is fully compliant, all the securities already pre-built in. So all they have to come up is with an cool idea they want to bring through the world. I just I want to pause really quickly and just reiterate for folks that are not watching because you you breeze through it, but it's so powerful, which is you built and and this is totally separate. I'm presuming from like all your other product road nappy stuff. You built a very fun. I love the idea of a quest, the ability for your team to request an AI automation or tool from someone else in the team. So you take a subject matter expertise like a recruiter or a salesperson, they know what they want. They just don't know how to get there and you're like engineer, will you go on this quest with me and they make the request and some things that we missed I wondered if you would wouldn't mind pulling pulling up just showing folks is you've also made it really centric to the value you're getting out of this automation. And so I saw in the corner of the quest like what's the risk of it? That's probably some assessment of the data it touches or what it what it does. The weeks saved and then who's the the team or person that's benefiting it. And then I love this idea like people can build like jump in and help with these things without having to go through a whole like prioritization exercise, all this kind of stuff. And so imagining you're kind of like building this like shadow AI roadmap that works really efficiently basically a marketplace of AI needs and AI builders inside your company where anybody can just pop in and say, Oh, I think I know how to do that and build it. It was that kind of the intention is to get it out of like the big prioritization mess get it out of I don't know how to do this myself and kind of make everybody feel responsible for it. Exactly. Because if you think through the traditional logic of software development life cycle, you think through the lens of sprints and you try to fill up the sprint with different practice and blocks. But sometimes you know people have these little tiny micro vacations I called them like where they have some free time. They want to like build other stuff that are not not tied to the most important core repository your main product that's very very stressful. Are there's fun little site projects that can help out. But also this has immediate customer pain. The user you can talk to within the company. So there's the feedback loop. And the moment you deliver the value, people are like you get the instantaneous dopamine if you will. So there's a lot of fun to this. And what's happening. The thing is people who are completing some of these classes actually earn experience points. If you earn enough experience point, you can change to a gift card. You can have a T with any executive you choose. You can present what you build to the rest of the company. So we do weekly standup on Wednesday. So we have people coming up from stage and sharing what they built within entire company. This week was recruiting team automation. Previously, I think it was marketing team. So there's a different team showing. And it's almost never actually the engineer team. It's other teams that are like really excited to show what they built. I love that so much. And then you know, the other thing that you did, which is very practical, which I've also advised almost every company to sit down and do is you have a bunch of people that have vibed coded something with cloud codes sitting on their computer. And they one just either don't know how to get that to production or they're getting it to production for the entire internet. They're just, you know, pushing it up to Netlify or Versel and saying, I built this thing and I love the idea that you both built knowledge guides for how to learn core skills like Git that will make people a little bit more fluid in building things. But also please everybody stop and listen, make a templated happy path to secure production for the things that people want to build behind off with the right kind of data access. Just make it so because your team is going to do somebody's doing it anyway. And it's a very low investment to get a lot of velocity on things being built, but also a lot of kind of like right size security. I would say it's not a hard thing to do. So I love that you built that. Who is responsible for like maintaining that, keeping it up to date? Yeah. So one of the team that we created is AI Engineer for internal operations. It's a very mouthful. But really the team is responsible for helping and accelerating the RAI transformation to becoming AI first company. So this role directly reports to me and our chief of staff. So it has an ability to work cross-functionally. But obviously there's a lot of support from our CTO and Engineer team as well as our InfoSec. So they part our very closely. So we have this task force where we meet on a weekly basis to talk about unblocking some of these challenges, whether it be appliances, how do we law things, what are the software that we can actually vet everything in advance. So when our team's like, hey, like I'm in sales, I'm going to build this tool. Then here's a full text like AI's that you do need to have to worry about databases. It's just all there coming through idea. And everything has always been already been vetted. So there's a working group. But it didn't start the media that way. And actually started with a couple of people building out their own personal tools and showcasing. But again, it came from the non-engineering team which really gave us the optimism that we can actually do it is. And that's actually built more infrastructure. So these people can run at 100 miles per hour. I love that. And so speaking of infrastructure, it's not only these one-off automations and work flows or guides for building apps. You've also built, which I think is very smart, a company-wide skills marketplace. So tell me a little bit more about how that works. Yeah. So share anyone can create a plugin. Plug in is a collection of skills or we can create and download individual skills as well. So let's say you're in sales team or even if you're not in sales team, you want to learn more. You have to look at the sales skills repository. Plug in. So we internally use something called the medic framework. So if you want to learn more about medic framework, you can actually download or use a medic, a med pick advisor. And it teaches you how the skills actually build. But you can actually plug it into your own software or into your own workflow to get this skill to the view device. So we have that for almost all the functions, recruiting, design, some of those things are redacted for compliance purposes. But this is where we kind of actually build our market. Because what we realized to your point earlier, there are people who are building the same app across different functions or sometimes the same skill. And so we're trying to create this place where we can co-evol rather than people operating inside those. Yeah. And have you found that people have kind of understood this concept of skills and it's been a nice way to get people to encode their expertise or how did you train people on what a skill was? Did this happen organically? Oh, yes or no. I think there's a both top down and bottom up top down meaning, you know, myself, but CTO, some of our executive leaders really tried to get people to adopt it. There was some a lot of tough one of ones like, hey, we noticed that you haven't been spending any tokens. Like, can he help you? What's going on? What's stopping you from doing that? But certainly some people who are more curious, so we'll maybe talk about the archetypes of the people we're actually hiring for is the sense of curiosity and agency. Those who are curious who click a few more buttons and read a few more blog posts are like, hey, I've been hearing about this work called skills. And then they now see these word pop up in Slack channels. And then some people uploading markdown files. I'm like, hey, I saw this design markdown. Can I use that? What does the outcome look like? And this one person goes to the state on Wednesday and showcased what they built a beautiful inside. And we know this person's not a designer, but has a beautiful inside. They're like, how to pull that off. They're usually some skills involved. So I think there's that organic, kind of shared learning aspect as well. So we're looking at this from a meta perspective, which is your how I built use AI built a product to incept the rest of my organization to adopt and use AI. I'm curious just off the top of your head, what are some real wins that you've had from this? We saw the swag store. That's a fun win. What are a couple like kind of top of mind skills wins or automation wins that you think the team is really proud of? Yeah. I'll do you one better. So actually one team level example and one specific campaign that we're doing. So our bar getting team again, has built this entire marketing sass almost on their own. This completely set of tools, whether it be inter-remarketing plan calendar, there's the count based marketing tools, various tools, right? We have a competitor review. I wish I can click on this. It has a lot of sensitive information, real-time metrics. We call it purple cow. How do we stand out? As you see from the ass store that we built, the thing is pretty revolutionary. I know I'm going to buy a few. So this entire portal is built and managed and used daily by a marketing team. And just to give you one example of a very recent one, they're actually live right now. It's this concept of a buzz for it. It's like there are a lot of sass companies that actually do it is. What it does is you can create a campaign and track what's happening and how many people post have shared? Who's winning in the company that attracted most amount of engagement. One example is we are right now doing a billboard in San Francisco in one a while. We have real photos, we have AI-generated billboards, so you can actually pick one of them and choose a language or whatever a pre-configured copy and you can post directly on LinkedIn. This entire tool was built by a marketing team and then you can also change length and details and energy level and this is being used daily as you've seen from the metrics we're tracking. So I think this is like one example of really good use. We also have Spark attendee logos which is a conference we're again throwing and coming soon. How are AI, John's episode? We're going to run a social media campaign. Great, this is going to be the top performing episode. This episode is brought to you by ThoughtSpot. Proper leaders know the struggle. 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I think there's plenty of software problems to solve that really deeply engage teams with an under-synuous space can create delightful solutions and things that matter. I think people will like to buy those solutions off the shelf. I think a lot of teams are going to be like yours, which is when they could reach for searching for some sort of external solution, they're first going to say, well what do we want and can we build it internally? What I like about what you're doing, which I also tell people is it's not about functionally replicating an external vendor. It's not like functionally replicating a social posting vendor. It's about building the LinkedIn posting tool that works the best for your team, for your culture and how you know people work. I think this customization of micro software solutions inside companies is so undervalued. I'm so glad to hear that you have an AI-focused internal tools team. I tell everybody this is revenge of the internal tools team. I don't know. You've probably been around long enough that you know that prior to this moment, no one wanted to be on internal tools because it was always starred for resources. You always working on just functionally getting the thing to work. Now I feel like everybody should want to be on this internal tooling team because you have this green field to have so much fun. Well, actually love building internal tools. That's my jam. Yeah. So just a magical moment for me because now, you remember when you build internal tools that designs are not quite there because you're always under resource tools are sluggish and slow. Now the design looks beautiful. It's fast and rapid. It's responsive. It's a dream scenario for people like me which just want to increase the productivity and collaboration between people. It's like a magical world for me. Yeah. I love what you're showing us right now, which is the other thing I tell people is the people that are actually doing this are measuring and they are measuring it without shame. I talked to so many executives that are like, I couldn't possibly measure token usage and tell people to use their tokens because there will be a revolt and I say, look, every person that I know that is actually pulling this off has a dashboard john exactly what you're showing us right here. And they just look at it and they they set targets and they say we're going to get there. So tell me a little bit about this dashboard. Yeah. So just like you said, we had that in short on debate a little bit. It's like, well, well, engineers can't always optimize this. Famous tokens. And we actually had to experience it in early 2000. If you remember, when we some some business organization decide to measure engineers productivity by measuring the line of code. Well, obviously engineer wrote bunch of blank lines that lots of comments. It just took up space. That's not what we're trying to do. Our goal is to understand are people actually just learning how to use AI, but also this is not part of the performance review, but definitely part of a conversation to help people bring along the journey. So what we're seeing here is the overall usage of our token at the company level. So we're kind of like currently, if you look at the stats, we're a cloud code shop. But if you look at some of the top spenders are actually codecs. So you can kind of guess and we redacted the name, but some people on the working on the legacy code of our massive chat infrastructure where we have 300 million plus month active users. People are managing complex code based with cloud codecs, whereas some people are into the job of rapidly building product roadmap and rapidly turning on new features. They're more than need to cloud code. And this was a very organic, which is kind of fascinating. One of the things that we internally talk about is how do we make sure this token consumption is smooth? Because when there's a dip means people are on the weekend or they're going on vacation or whatever that's happening, AI is not working. So when this curve smooths out means we have AI partners, they're working around the clock. So how do we harness the power of that? So we track individual usage team level. This is what the manager can see about their own team members. And there's of course a leaderboard where you may have labels. I think there's a mislabel. So we measure AI causes somebody who's spent more than 100 million tokens a day. So we have different five tiers, which is actually described here. So every manager knows on their team which tier they're on. So they can start from the beginner, intermediate, you have experts, you have architects, catalysts and AI gods. And knowing where your team is on the journey, then you can tailor what kind of enablement you want to do for them. So you can actually say, Hey, it's okay to be a beginner. It's rather great to be accepted at your beginner. So they can give you the right tools to bring you quickly to the intermediate rather than throwing you with a bunch of catalysts where you're like, I don't know where to start. So how do we actually bring them along the journey? As an organization, I think we're kind of somewhere here. Stage two and stage three we're still kind of using AI, a lot of automation, but not fully automated. So we're trying to get to the stage three and also by team level, if I'm a salesperson, what does it mean to be level three or level four? So by team members, managers can use this as a framework to talk about by by by the team members, how do we bring you to the next level? And where are we as a collective company in the overall journey? John, and I'm just I could not hype you up more. This is my favorite topic to talk about and I have to ask you one, are you an AI god? Where are you? 30 day average, no, I'm still a catalyst. I think my peak is about 200 million tokens a day. And you can yes, you can burn more tokens, but that's not the point to be productive. I think I'm in the hundred to 200 million range. Okay. But on average, I spend about 30 to 50 million tokens a day. Okay, and then executives out there, if you cannot answer that question for yourself, I want you to in 30 days be able to answer answer for yourself. I mean, the second thing that I want to just call out here is you have to make this not scary, but also make in an expectation, right? So it's it's not you don't have to be AI god out the gate. But once you hit level one, let's hit level two and level three. And then these lenses are so important. You need to look at an individual level. You need to look at it in organization level and you need to look at a functional level and being really clear about what being AI native or AI first looks like because people just don't know what the vision is. A lot of time. So, you know, one thing I definitely recommend to folks is take the time to lay out these expectations. And then because we all have access to, you know, Cloud Code and Codex, make it a beautiful app inside inside your company. Now, John, I have to ask you a second question, which is are you on the Codex side or on the Cloud Code side? Yeah, I'm still living more Cloud Code. Sorry, I love Sam Alpin. You know, we went through I see. But yeah, I definitely am living more Cloud Code for now. I think I'm about 80% Cloud Code and 20% Codex. I'm I'm I don't know, maybe I'd be an AI god in your cup. I'm like all all Codex all day, mostly because I'm just working in the back end of stuff. So, so I'm going to be a Codex hype right now, although I think for a lot of, I think for a lot of non-super technical backend tax, Cloud Code is so good. And it's actually really good at non-coding tasks as well. I feel like people really underappreciated. Yeah, I think Cloud Code has a slightly better front end taste. Of course. Living more rapid. That's why I'm living more biased. But is this actually changed over time too? You used to be about 75, 80% Cloud Code. But very quickly within a month, now it's like two-third is Cloud Code. So the codex is gaining. market share quite rapidly. Okay, so I love this organizationally. You showed us what's the benefit of going AI first. It enables your team to do really delightful things to cost your person for customers. The way you do that is you set those expectations and then you actually build a platform to enable that. That sits next to your normal roadmap, not in your normal roadmap. You build a team that's focused on it. I love that it reports directly to you cross-functional and that team is really built to get stuff out of the way of folks who want to use AI and then you are measuring it. And I love this idea. I want to make sure people did not miss it. Smoothing the curve, not because you don't want people to take vacation, but when people are taking vacation, you want AI to be filling in the gaps and working autonomously, which is not something that we've heard on this podcast before. Before we get to lightning rounds, any personal use cases that you find really useful. I mean, just promote one little open-source project I released not too long ago and actually nobody uses it because I haven't really promoted this. But it's what I call the gardener. What the gardener does, and I'm sure a lot of people use like obsidian or some kind of markdown file as a knowledge base. I've been a long-term user of obsidian and log stack, all this kind of weak-y based knowledge base. What a basic does is like imagine a garden showing up at your house. And then you look through your notes, figure out which notes to enrich. If there's a people name that's not registered and then you create some research on the person about the company, also fixed typos, grammatical errors, create beautiful headings and clusters and cross-linking. So it basically does that for you. So if there's a seating stage, they nurture it, and then when the document is mature enough, then it's going to the tending mode. So it has very different aspects of gardening functioning that really comes through your notes. I'm able to show my personal notes because it has a lot of information in it. But basically I built it for myself, and this was beautifully well. So I have recommended it. Maybe one more thing I do want to share, just a second, is what I used to actually learn. So AI to create my own personal learning center. So this example is neuroscience. I always love neuroscience and brains. This was created back in February. So basically I asked this is a prompt. So you're like a PhD neuroscience researcher. Here's what you're trying to create, and you run Cloud Code of Codex. And give it 10 minutes, 20 minutes. It comes back with this beautiful structure of everything you want to learn about neuroscience. So where you start, let's say you go to this craft view, it shows this marvelous, space of neuroscience. Then you can learn about your scientists, neurological disorders. You can learn everything there to learn about different types of neurological disorders. You can learn about your modulators, and dopamine, serotonin, all these things are very popular among podcasts like Andrew Huberman. So you can learn everything there to learn about neuroscience. So I have this for neuroscience. I have this for potomacanics. I have this for fusion. And it also does research for all the startups out there. So basically there are like this cluster of knowledge base I used to just geek out. I was smiling. I was smiling because I'm like, we could have done an entire episode on just personal, a personal knowledge basis. And I love what I love about this moment is I think it is just such a moment to learn things you could never learn before because the best teacher with the most in depth knowledge and an endless willingness to go to research is right there at your fingertips. And to me, I worry and I think about is AI going to lead to cognitive decline where none of us are going to think about anything. And I'm just dangerously skip permissions. Yes, yes, yes, make no mistakes. And instead what I'm finding is I'm having a richer engagement with topics that I have been interested in, but either haven't found the time to intersect with or the current form factor is not consumable for my particular brain. And so the fact that you can like massage and change and organize and explore data and knowledge in a just completely novel customized way, I think is so underappreciated by folks as an opportunity to use AI to learn. I'm really excited about this for my kids. I was watching that and I was like, oh, my kid is super interested in cybersecurity. He's like nine very Silicon Valley kids sort of thing. And he's like in the terminal and he's like, mom, do you know this is your mac address? I was like, I do know that's my mac address, but you know, like it's just very, it's very cute. There is no like cyber security for nine year olds book out there that is robust. But I could build this for him in a way that's really accessible and can grow with his maturity over time. I think that's so exciting. Yeah, there's not a single website in the world that dedicates to a personal learning. One is only contains the content about that feel like there's no website, but you can create your own within 10, 20 minutes by sitting in your laptop and completely offline so you can read it on your airplane if you want. And this is fantastic. You can continue to update it too. And to your point, if you want to make any changes, you can ask a few more questions. You can redo the structure, give you guys a high level of this content. So I love it as a learning tool. And to your points earlier, people maybe talking about people's archetypes. So we actually read that our entire job description for many of these AFers roles. So we actually lower the bar in terms of like tenure or experience of all we actually optimize now for high curiosity, high agency and high energy people who are curious who are going to go deep and willing to just figure things out and learn on their own. Because like, as I say, world is your oyster. You can do things. You can build things. You can learn things. There's nothing stopping you. The cost is practically $200 a month if you go to the mass fine. But you can pay 20 bucks too. So you know, I love this. We all have to do around too. I think you just have so many things you could show us with the company level at the personal level. Let's get you out of here. We're running up against time. Couple lightning round questions. I said, truly, this week with like five CEOs that are just looking at me with these desperate eyes that say, Claire, how do I get my company to do this? What would you tell them? They're always people in your organization who are already curious, who already have agency, find them, make them the champions, keep them the spotlight, let them share their fun things. And usually people will be anxious like, oh well, I don't know if I'm doing things right and I'm going to get embarrassed from my colleagues. Just really give them the confidence. And also you have to fail forward. This is like beautiful time to fail forward and still get up and run faster than the others. So use more examples of that and people bring up their confidence. So you have to really build energy around those people because innovation doesn't start from a pure theoretical structures. It starts with people who have that energy and the story behind them. So find them. And then two is of course, leadership have to be really bought in. The top token consumers in our entire organizations are our CTOs and our co-founders chief architect. These are leaders who are spending the most amount of tokens. Business leaders are also spending quite a bit of tokens. So it's similar to the team that this actually works. This is actually important. And when they show up with different capabilities, people are like, wait, my leader, I thought it was like, easy, why is it coming up with more work? This is amazing. You get inspired. Well, maybe not so amazing. But people get inspired, right? So it's similar to the team. This is how it's done. This is going to be a new world. And I think it just energizes a lot of people. OK, I have a second question. Doesn't have anything to do with AI. I suspect based on what you've showed me, you have played video games in your life. Oh, yes. Great. Great instinct. Yes. This is the moment for all of us who played Starcraft to really show our skills. So tell me what game do you think made you most prepared for this moment in AI? Hello, games. But I was telling my wife, when Cloud Code, Opus 4.5 came out, I literally could not go to sleep. I was spending 16 hours, 20 hours a day, just five coding. As tell, I was like, I feel like I'm just teenager again. I feel more addicted to Cloud Code than playing games. But I used to be, I used to play a lot first-person shooters, Quake and Realtortment. I was career's number one professional gamer back in the days in World's number three player, which means I was a terrible son and a terrible boyfriend back then. So I admit, mom cried quite a bit. I feel like, you know, I did not know that about you. I should have done my research. I could just tell. You saw the levels. You saw the tsunami code. I would like this person. Yes, please. Well, there was some games. Great. Very still. Smart games, the idea. But there was some like, yes, I love you. Yeah. I feel the same way as I tell people, I feel like this, I have not felt like this about technology since I was a teenager, cobbling together computers to play games on. Like that's the same feeling I had when I was setting up my open claw, which truly I have to like kick the back mini every morning to wake it up. You know, it's unstable, but beloved. Is it just like reinvigorates this builder energy in me, which is why I ended up with the jobs that I ended up with and getting close to that feels so gratifying because I did go through this phase where I was like, my job is to be in meetings. And I don't want my job to be being in meetings. I want my job to be building and doing all these things. So I love that. Okay. When AI is not listening, when you are trying to consume the tokens and it is just not doing what you want, what's your prompting strategy? Do you yell? I know there's a fear of tactic, I know it warms well in the short term. Just like play this after a second. Right now, I know like we know like AI doesn't really have like a long term memory, but I firmly believe starting your science and you, people are working on it like episodeing memory is a magic memory. So once AI starts to remember, they're not like, be resentful. So I want to like start building a relationship with them. So that when this guy that takes over, I'm like, well, John was pretty nice to us, you know, like, we'll let him live a few years longer, maybe. I'm trying to be consistently nice. You were the first person that has admitted they are explicitly nice, you know, just just to avoid the AI. To say that, thank you. I'm polite as well. I think it reflects my own humanity to be polite to the AI and also just like I don't expect good performance from a teammate that I yell at and then I'm rude at. I do not expect a good performance from AI long term. One that I yell at. Well, John, this has been incredible. One of my favorite episodes ever. I don't say that often. This is, this is awesome. So many people are going to learn from this on how to transform their own organizations, things to build and then just how to bring a curious energy to AI. So where can we find you and how can we be helpful? Yeah, you can find me on x.com. I don't use a lot, but at dash Kim, you can find me on Instagram. We're going to follow our company story. And we have a wonderful conference is going to happen. San Francisco may seven. So, yeah, keep your eyes out on LinkedIn. Great. John, thanks for joining how AI. Thanks so much. Thank you very much. Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube, or even better, leave us a comment with your thoughts. You can also find this podcast on Apple podcasts, Spotify, or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at how I AI pod.com. See you next time.

Podcast Summary

Key Points:

  1. Sandbird’s internal platform, the Automator’s platform, uses "quests" where employees request AI automations, and AI can now also generate code from specifications.
  2. AI adoption is gamified
  3. A marketing team built a swag store (e.g., "Big S. Energy" with a Konami code Easter egg) in a day without engineering support, showcasing how AI empowers non-technical teams to create customer-facing products.
  4. The company provides pre-vetted app templates, security compliance, and knowledge guides (e.g., GitHub setup) to enable safe, rapid building by any employee.
  5. A skills marketplace allows teams to share and reuse plugins (e.g., "med pick advisor"), preventing duplicate work and fostering cross-functional collaboration.

Summary:

In this episode, John Kim, founder and CEO of Sandbird, demonstrates how his company is becoming an "AI-first" organization by treating AI adoption as a product. The core is an internal platform where employees can raise "quests"—requests for AI automations or tools. AI can now read quest specifications, create PRs, and start coding, alongside human engineers.

This enables rapid innovation, as shown by the marketing team building a swag store (with a Konami code Easter egg) in a day without engineering support. The platform gamifies adoption: users earn experience points for completing quests, leading to rewards like gift cards or stage time to present builds. , for recruiting or design) to avoid duplication.

, for GitHub), allowing non-technical staff to build safely. , recruiting automations). John emphasizes that innovation starts with curious, agency-driven employees, and that AI enables "failing forward" faster, making fun and creativity cheap to prioritize.

FAQs

It's an internal platform where anyone in the company can create a 'quest' to request an AI automation or tool, and others can help build it. AI can also read specifications and start coding the quest.

Employees raise their hands with an idea for a tool, and others can volunteer to build it. Completed quests earn experience points, which can be redeemed for rewards like gift cards or executive meetings.

They built a swag store called 'Big S. Energy' with a Stripe integration and a secret Easter egg, all without engineering support, in just a day or two.

They use a token consumption leaderboard that ranks employees from AI newbie to AI God, and they measure AI causes as those who spend more than 100 million tokens a day.

Skills are reusable AI tools or workflows that can be downloaded and used across different functions. They help encode expertise and prevent people from building the same thing twice.

Through a mix of top-down support from executives and bottom-up curiosity, with weekly standups where teams showcase their AI builds and one-on-one check-ins for those not using tokens.

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