Pod Insights How I AI Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird) About this episode John Kim is the co-founder and CEO of Delight.ai, a customer experience platform that’s transforming how companies deploy AI. But what makes John’s story fascinating isn’t just his product; it’s how he’s turned his entire company into an AI-native organization. His marketing team built a fully functional e-commerce swag store with Stripe integration in days. His sales team built their own CRM tools. His recruiting team automated their entire workflow. And it’s all tracked, measured, and celebrated through an internal platform called Automators.
What you’ll learn:
How Sendbird’s marketing team built a fully functional swag store with Stripe integration in a day (with no engineering support)How the Automators platform works—an internal marketplace where anyone can request AI tools and engineers (or AI agents) can build themHow to create secure, compliant templates so non-technical teams can ship to production safelyHow Sendbird built a token usage dashboard with five tiers (beginner through AI God) and why tracking the smoothness of the curve matters more than the totalWhy visible leadership usage is the most powerful adoption signalWhy Sendbird rewrote job descriptions to prioritize curiosity, agency, and energy over years of experienceHow John uses AI for his own learning—
Brought to you by:
WorkOS https://workos.com/?utm_source=lennys_howiai&utm_medium=podcast&utm_campaign=q22025—Make your app enterprise-ready today
ThoughtSpot http://go.thoughtspot.com/howIAI—Build AI-powered analytics into your product
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In this episode, we cover:
(00:00 https://www.youtube.com/watch?v=uH39OZ-KnkY) Introduction to John Kim
(02:45 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=165s) The Delight.ai swag store built by marketing in two days
(05:51 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=351s) The before times: when fun had to earn its place on the roadmap
(07:55 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=475s) Demo: The Automators platform and quest system
(13:47 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=827s) The AI Engineer for Internal Operations role
(16:06 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=966s) Demo: The company-wide skills marketplace
(17:19 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1039s) Treating AI adoption as a product
(18:43 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1123s) Real wins: team-level and campaign examples
(21:51 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1311s) Why SaaS isn’t dead—it’s being rebuilt internally
(23:46 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1426s) Demo: The token tracking dashboard
(26:32 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1592s) Measuring without fear: setting expectations, not punishments
(28:54 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1734s) Quick recap
(30:51 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=1851s) Personal AI use cases: endless knowledge at your fingertips
(36:15 https://www.youtube.com/watch?v=uH39OZ-KnkY&t=2175s) Lightning round and final thoughts
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Tools referenced:
• Claude Code: https://claude.ai/code
• Codex (OpenAI): https://openai.com/codex
• Obsidian: https://obsidian.md https://obsidian.md/
• GitHub: https://github.com https://github.com/
• Stripe: https://stripe.com https://stripe.com/
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Other references:
• Jason Levin (CEO of Memelord) on How I AI: https://www.lennysnewsletter.com/p/from-a-690-newsletter-to-3m-api-how
• Konami Code: https://en.wikipedia.org/wiki/Konami_Code
• Andrew Huberman’s podcast: https://hubermanlab.com/
• Y Combinator: https://www.ycombinator.com/
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Where to find John Kim:
X: https://x.com/doshkim
Instagram: https://instagram.com/dosh
LinkedIn: https://www.linkedin.com/in/doshkim/
Company: https://delight.ai https://delight.ai/
Delight.ai Spark Conference (May 7, SF): https://delight.ai/spark
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Where to find Claire Vo:
ChatPRD: https://www.chatprd.ai/
Website: https://clairevo.com/
LinkedIn: https://www.linkedin.com/in/clairevo/
X: https://x.com/clairevo
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected] .
Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
0:00 Speaker 00 Unleashing this power of AI and giving it to the power of marketers, salespeople, you get all these cool ideas that get rolled out rapidly to the market.
0:07 Claire Vo? It's taking someone's super creativity and giving them powers to deliver it to your customers.
0:12 Speaker 00 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 read through the specification, create PRDs and start actually coding.
0:24 Claire Vo? 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.
0:33 Speaker 00 So what we're seeing here is the overall usage of our token at the company level. We measure AI gods as somebody who spend more than 100 million tokens a day.
0:40 Claire Vo? 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 do research is right there at your fingertips.
0:52 Speaker 00 This is like a beautiful time to fail forward and still get up and run faster than the other. Because innovation doesn't start from a pure theory of structures. It starts 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.
1:11 Claire Vo? Welcome back to How I AI. I'm Clairvo, 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 Sendbird, and he's going to show us his AI token consumption leaderboard, 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. This episode is brought to you by WorkOS. AI has already changed how we work. Tools are helping teams write better code, analyze customer data, and even handle support tickets automatically. But there's a catch. These tools only work well when they have deep access to company systems. Your co-pilot needs to see your entire code base.
1:57 Claire Vo? Your chatbot needs to search across internal docs. And for enterprise buyers, that raises serious security concerns. That's why these apps face intense IT scrutiny from day one. To pass, they need secure authentication, access controls, audit logs, the whole suite of enterprise features. Building all that from scratch, it's a massive lift. That's where WorkOS comes in. WorkOS gives you drop-in APIs for enterprise features so your app can become enterprise-ready and scale up market faster. Think of it like Stripe for enterprise features. OpenAI, Perplexity, and Cursor are already using WorkOS to move faster and meet enterprise demands.
2:39 Claire Vo? 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, a 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 their use of AI?
3:13 Speaker 00 We want to become the AI-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 a right set of information and tools so that they themselves 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.
3:34 Claire Vo? 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, more, more. But I think what your team is building is showing a different benefit of adopting AI and everybody becoming builders. So you want to jump in and show us some of the stuff that you all are building with AI? And then maybe we'll back into how you got the team there?
4:09 Speaker 00 Welcome to a delight as shop. It's, we're really excited about this. This is a swag store that really captures the culture and the energy of where our company's headed. The store is 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 sass, fully deterministic. I think this is one of the most popular swags we have right now. You can actually go and buy this. So our marketing team integrated Stripe integration. So yeah, we do charge a little bit of money, but I think it's gonna be really cool. Another favorite context window I carry a lot.
4:54 Speaker 00 So imagine unleashing this power of AI to your marketing team for this amazing creative energy. And instead of asking your design team or engineer to put this site together, they put this site together in a matter of a day or two, and then it's now up and running. We also have a super secret Easter egg for those of gamers for 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 Delight Spark in San Francisco. It's gotta be a really amazing conference, bringing the CX leaders, AI builders from all over the world, people joined from Anthropic.
5:39 Speaker 00 We'll be 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 is the future of customer experience going to look like? So this is what our marketing team has built together.
5:53 Claire Vo? I just have to stop and reflect. So we just had a really recent episode with Jason Levin, the CEO of Meme Lord. 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 gonna pass quickly. Just do something out of the box in. You know, our CMS and then you get this sort of like middling experience for your customers.
6:37 Claire Vo? 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, um, my thesis on why you should let marketers become, come builders.
7:21 Claire Vo? And, and I'm sure they love it too, just from like a team engagement, you know, creativity perspective.
7:27 Speaker 00 Yeah, I love that because that's exactly what happened. Because imagine sitting in a, 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 and roadmap. It's going to take you two sprints. I, it's kind of very hard. It's going to be very hard to get that on the table. But just like, again, unleashing this power of 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.
7:55 Claire Vo? 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?
8:18 Speaker 00 So to really help facilitate that transformation, we built out a platform called the Automators, Automators Platform. This is an internal platform where anyone in the company can raise their hand and create what we call the quest. Now this website is particularly has been designed to just show you the demo today. But actually you can actually create a quest on your own. 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 examples, if you go to a completed list of quests, these are all the things that have been built or being pending.
9:03 Speaker 00 And then so let's say you go to a quest. Then 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 lookup 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 first it's an internal workflow, so we kind of blurt 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 hot off the press, I guess, or fresh out of the oven, is when you create this kind of quest,
9:48 Speaker 00 you can actually now ask AI to build it too. So when there's a quest, AI can actually read through the specification, create PRDs 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 continue to get updated pretty much on a daily basis, teaching people how to set up GitHubs, 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.
10:31 Speaker 00 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. It's fully compliant, all the security is already pre-built in. So all they have to come up is with a cool idea they want to bring to the world.
10:51 Claire Vo? 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 roadmap-y 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 wouldn't mind pulling, pulling up, just showing folks is
11:32 Claire Vo? 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 I'm imagining you're kind of like building this like shadow AI roadmap that works really efficiently.
12:10 Claire Vo? Basically a marketplace of AI needs and AI builders inside your company where anybody can just pop in and say, oh, I, 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.
12:29 Speaker 00 Exactly. Because if you think through the, the traditional logic of software development lifecycle, you thinking, think through the lens of sprints. And you try to fill up the sprint with different prioritizing blocks. But sometimes, you know, people have these little, you know, tiny micro, you know, vacations, I call them, like where they have some free time. They want to like build other stuff that are like not tied to the most important core repository, your main product that's very, very stressful. Are there's fun little side projects that I can help out? But also this has immediate customer pain, the user you can talk to within the company. So there's that feedback loop. And the moment you deliver that, the value, people are like, you get the instantaneous dopamine hit, if you will. So there's a lot of fun to this.
13:13 Speaker 00 And what's happened behind the scenes is people who are completing some of these quests, they actually earn experience points. If you earn enough experience point, you can change to a gift card. You can have a tea with any executive you choose. You can present what you built to the rest of the company. So we do weekly stand up on Wednesday. So we have people coming up to the stage and sharing what they built with the entire company. This week was recruiting team automation. Previous week, I think, was marketing team. So there's a different team showing. And it's almost never actually the engineering team. It's other teams that are like really excited to show what they built.
13:46 Claire Vo? 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 vibe coded something with Claude code 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 Vercel 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 fluent in building things. But also, please, everybody, stop and listen.
14:27 Claire Vo? 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 it. 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 sized security, I would say. And 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?
14:56 Speaker 00 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 our AI transformation to becoming AI first company. So this role directly reports to me and our chief of staff. So it has a 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 partner 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 Clients, how do we log 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 want to build this tool. Then here's a full text like the I think you have to worry about databases.
15:41 Speaker 00 It's just all there. Come with your idea and everything has always been already been vetted. So there's a working group, but it didn't start immediately that way. It actually started with a couple of people, you know, kind of building out their own personal tools and showcasing. But again, it came from the non-engineering team, which really gave us the optimism like we can actually do this. And let's actually build more infrastructure so these people can run at 100 miles per hour.
16:06 Claire Vo? I love that. And so, speaking of infrastructure, it's not only these one-off automations and workflows 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.
16:19 Speaker 00 Yeah, so here, anyone can create a plugin. Plugin is a collection of skills or you 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, a plugin. 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 MedPick, an advisor. 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 give you advice. So we have that for almost all the functions with recruiting, design, some of those things are redacted for compliance purposes.
17:02 Speaker 00 But this is where we kind of actually build our marketplace. 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-evolve rather than people operating in silos.
17:20 Claire Vo? 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?
17:33 Speaker 00 Well, yes and no. I think there's both top-down and bottom-up. Top-down meaning myself, a CEO, some of our executive leaders really try to get people to adopt it. There was a lot of tough one-on-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 a 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 word 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?
18:18 Speaker 00 And this one person goes to the stage on Wednesday and showcased what they built, a beautiful-looking slide. And we know this person is not a designer, but has a beautiful slide. They're like, how'd you pull that off? There are usually some skills involved. So I think there's that organic, pure learning aspect as well.
18:33 Claire Vo? So we're looking at this from a meta perspective, which is you're how I built, used 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's really proud of?
18:56 Speaker 00 Yeah. How do you win better? So actually, one team-level example and one specific campaign that we're doing. So our marketing team, again, has built this entire marketing SaaS almost on their own. This completely set of tools, whether it be interview marketing plan, calendar, there's account-based marketing tools, various tools, right? We have competitor review. I wish I can click on this. 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've built, we think it's pretty revolutionary. I know I'm gonna buy a few. So this entire portal is built and managed and used daily by our marketing team.
19:41 Speaker 00 And just to give you one example of a very recent one, they're actually live right now. Is this concept of a buzzboard. It's like there are a lot of SaaS companies that actually do this. What it does is you can create a campaign and track. You know what's happening, how many people posts have shared, who's winning in the company. That attracted most amount of engagement. And one example is we are right now doing a billboard in San Francisco going one mile. So we have real photos, we have AI generated billboards. So you can actually pick one of them. And choose like a language or whatever, a pre configured copy and you can post directly on LinkedIn. And this entire tool was built by marketing team.
20:24 Speaker 00 And then you can also change the 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.
20:40 Claire Vo? Coming soon.
20:40 Speaker 00 How I AI, John's episode. We're gonna run a social media campaign on that too.
20:45 Claire Vo? Great, this is gonna be the top performing episode. This episode is brought to you by ThoughtSpot. Product leaders know the struggle. Your users want data insights, but they don't want to leave your app to find them. ThoughtSpot Embedded solves this by putting analytics directly into your product. Your users can search in plain English and explore data instantly, right where they work. No separate tools and zero context switching. What sets ThoughtSpot apart is that it's not just another bolt on dashboard. It's a search driven, AI powered experience that feels native to your app. Developers can embed it with just a few lines of code and then fully customize the look and feel. The result?
21:27 Claire Vo? More engaged users, faster decisions and a product that delivers more value every time someone logs in. If analytics is becoming core to your product strategy, visit go dot thoughtspot dot com slash how I AI. For more information and try the free trial at go dot thoughtspot dot com slash how I AI slash trial. What I want to reflect on on this is like, there's this big debate about whether SaaS is dead or not. And you know, I I tell people, look, I don't think SaaS is going to zero. I think there's plenty of software problems to solve that really deeply engage teams with an understanding of space. Can create delightful solutions and things that matter. And I think people will like to buy those solutions off the shelf.
22:13 Claire Vo? And 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? And 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. And I think this customization of like micro software solutions inside companies is so undervalued.
22:58 Claire Vo? I am so glad to hear that you have an AI-focused internal tools team. I tell everybody this is like 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 like always starred for resources. You're always working on like just functionally getting the thing to work. And 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.
23:28 Speaker 00 Well, side note, actually love building internal tools. That's my jam.
23:33 Claire Vo? Yeah.
23:34 Speaker 00 So this is like a magical moment for me because now, because you remember like when you build internal tools, the designs are not quite there because you're always under resourced. Tools are sluggish and slow. Now the design looks beautiful, is fast and rapid, is responsive. It's like it's a dream scenario for people like me, who just want to increase the productivity and collaboration between people. This is like a magical world for me. Yep.
23:57 Claire Vo? 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.
24:28 Speaker 00 Yeah. So just like you said, we had that internal debate a little bit. It's like, well, engineers can always optimize to spend more tokens. And we actually had the experience in early 2000s, if you remember, when we, some some business organizations decided to measure engineers' productivity by measuring the line of code. Well, obviously, engineer wrote a bunch of blank lines and 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 Codex.
25:13 Speaker 00 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 multi-active users. People are managing complex code bases with Codex, where some of people are working the job of rapidly building product roadmap and rapidly turning on new features. They're more leaning 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 is 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?
25:58 Speaker 00 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 gods as somebody who spend 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.
26:42 Speaker 00 It's rather to great to be accepted 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,
27:19 Speaker 00 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?
27:28 Claire Vo? John, 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?
27:42 Speaker 00 Thirty 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 100 to 200 million range.
27:54 Claire Vo? Okay.
27:54 Speaker 00 But on average, I spend about 30 to 50 million tokens a day.
27:57 Claire Vo? 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 making 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 it individual level. You need to look at it at an organization level and you need to look at it 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 times.
28:39 Claire Vo? 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, Claude 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 Claude Code side?
28:58 Speaker 00 Yeah, I'm still a little bit more Claude Code. Sorry, I love Sam Altman, you know, we went through YC. But yeah, I definitely am a little bit more Claude Code for now. I think I'm about 80% Claude Code and 20% Codex.
29:13 Claire Vo? I'm, I'm, I don't know, maybe I'd be an AI god in your company. I'm like all, all Codex all day, mostly because I'm just working on the backend of stuff. So, so I'm gonna be a Codex hype right now, although I think for a lot of, I think for a lot of non-super technical backend tasks, Claude Code is so good. And it's actually really good at non-coding tasks as well. I feel like people really underappreciate it.
29:42 Speaker 00 Yeah, I think Claude Code has a slightly better frontend taste.
29:45 Claire Vo? Yeah, of course.
29:46 Speaker 00 A little bit more rapid. That's why I'm a little bit more biased.
29:48 Claire Vo? Yep.
29:49 Speaker 00 But this has actually changed over time too. It used to be about 75, 80% Claude Code, but very quickly, within a month, now it's like two third is Claude Code. So the Codex is gaining market share quite rapidly.
30:01 Claire Vo? Okay.
30:02 Speaker 00 So it's hot to watch.
30:03 Claire Vo? I love this. Organizationally, you know, you showed us what's the benefit of going AI first. It enables your team to do really delightful things to customers and 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're measuring it. And I love this idea. I want to make sure people did not miss it. Of 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 in the gaps and working autonomously,
30:48 Claire Vo? 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?
30:57 Speaker 00 Let me 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 like markdown file as a knowledge base. I've been a long-term user of Obsidian, LogSec, all this kind of wiki-based knowledge base. What it basically does is like, imagine a gardener showing up at your house. Every day, you look, go through your notes, figure out which notes to enrich. If there's a people name that's not registered, and then you create, do some research on the person, about the company. Also fix typos, grammatical errors, create beautiful headings and clusters and cross-linking. So it basically does that for you.
31:40 Speaker 00 So if there's a seeding stage, they nurture it. And then when the document is mature enough, then it's going to the tending mode. So it has a very various different aspects of gardening functioning that really combs through your notes. Now I'll be able to show my personal notes because it has a lot of information in it. But basically, I built it for myself and this works beautifully well. So I recommend 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.
32:26 Speaker 00 So you're like a PhD neuroscience researcher. Here's what you're trying to create and you run Clacko or Codex. And give it, you know, 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 graph view. It shows this marvelous space of neuroscience, right? Then you can learn about key neuroscientists, neurological disorders. You can learn everything there is to learn about different types of neurological disorders. You can learn about your modulators, I know dopamine, serotonin, all these things are very popular. My podcasts like Andrew Huberman. So you can learn everything there is to learn about neuroscience. So I have this for neuroscience, I have this for quantum mechanics.
33:10 Speaker 00 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 use to just geek out.
33:20 Claire Vo? 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 do research is right there at your fingertips. And you know, 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, you know, 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
34:03 Claire Vo? 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 kid 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.
34:47 Claire Vo? But you know, like, it's just very, it's very cute. There is no like cybersecurity 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.
35:04 Speaker 00 Yeah, there's not a single website in the world that dedicates to a personal learning.
35:09 Claire Vo? Yeah.
35:10 Speaker 00 And it's only contains the content about that field. Like, there's no websites, but you can create your own within 10, 20 minutes by sitting on your laptop and completely offline, so you can read it on your airplane if you want.
35:22 Claire Vo? Yeah.
35:22 Speaker 00 And this is fantastic and 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 how to follow 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 redid our entire job description for many of these A F first roles. So we actually lowered the bar in terms of like tenure or experience level. We actually optimize now for high curiosity, high agency and high energy. People who are curious, who are willing to go deep and willing to just figure things out and learn on their own. Cause like, as they say, world is your oyster. You can do things, you can build things, you can learn things. There's nothing stopping you.
36:06 Speaker 00 The cost is practically $200 a month if you go to the max plan. But yeah, you can pay 20 bucks too. So, you know.
36:15 Claire Vo? I love this. We will have to do a round two. I think you just had so many things you chose, both at 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 sit 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?
36:38 Speaker 00 There are always people in your organization who are already curious, who already have agency. Find them, make them the champions, give them the spotlight, let them share their fun things. Initially, people will be anxious like, oh, well, I don't know if I'm doing things right. 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. Right? So use more examples of that and people bring out 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, they're always in your organization and they really build energy around that.
37:21 Speaker 00 And then two is, of course, leadership has to be really bought in. The top token consumers in our entire organizations are our CTOs and our co-founder, chief architect. These are leaders who are spending the most amount of tokens. Our business leaders are also spending quite a bit of tokens. So it's similar to the, 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 lazy, 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.
38:01 Claire Vo? Okay, I have a second question. Doesn't have anything to do with AI. I suspect, based on what you showed me,
38:10 Claire Vo? you have played video games in your life.
38:12 Speaker 00 Oh, yes, great, great instinct, yes.
38:16 Claire Vo? 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?
38:27 Speaker 00 I love games, but I was telling my wife when Claude Code, uh, Opus 4.5 came out, I literally could not go to sleep. I was spending 16 hours, 20 hours a day, just five coding. I was telling my wife, I feel like I'm just teenager again. I feel more addicted to Claude Code than playing games. But I used to be, I used to play a lot of first-person shooters, Quake, Unreal Tournament. I was Korea's number one professional gamer back in the days and world's number three player, which means I was a terrible son and a terrible boyfriend back then. So, yeah, I made mom cry quite a bit.
39:00 Claire Vo? I feel like, you know, I, I, I did not know that about you. I should have done my, did my research. I could just tell. You saw the levels, you saw the Konami code. I was like, this person has played some games.
39:12 Speaker 00 Very serious marketing team's idea, but there was something like, yes, I love you.
39:15 Claire Vo? Yeah. I mean, I, I feel the same way. As I, 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, that's the same feeling I had when I was setting up my OpenClaw, which truly I have to like, kick the Mac Mini every morning to wake it up. You know, it's, 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, and doing all these things. So I love that. Okay, last question.
40:01 Claire Vo? 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?
40:09 Speaker 00 I know like there's a fear tactic. I know it works well in the short term. Just like play this out for a second. Right now, I know like, we know like AI doesn't really have like a long-term memory, but I firmly believe studying neuroscience and you people are working on it, like episodic memories, semantic memory. So once AI start to remember, they're gonna like be resentful. So I wanna like start building a relationship with them. And so that when the Skynet 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 try to be consistently nice.
40:41 Claire Vo? You were the first person that has admitted they are explicitly nice, you know, just, just to avoid the AI overrewards.
40:48 Speaker 00 Thank you.
40:50 Claire Vo? I'm polite, I mean, I'm polite as well. I think it, 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 that I'm rude at, I do not expect 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?
41:26 Speaker 00 Yeah, you can find me on X.com. I don't use a lot, but at @DoshKim. You can find me on Instagram if you want to follow our company story, @Dosh, D-O-S-H, short handle. But yeah, come check out our website, Delight that AI. And we have a wonderful conference that's going to happen in San Francisco, May 7. So yeah, keep your eyes out on LinkedIn.
41:45 Claire Vo? Great. John, thanks for joining How AI.
41:48 Speaker 00 Thank you so much. Thank you for having me.
41:51 Claire Vo? 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 howiaipod.com. See you next time.
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