Quests, Token Leaderboards, and a Skills Marketplace: The Elite AI Adoption Playbook | John Kim

Why It Matters

Democratizing AI development turns every employee into a rapid innovator, accelerating product cycles while maintaining enterprise security and fostering a culture of continuous improvement.

Key Takeaways

• AI quests turn employee ideas into deployable tools quickly.
• Token leaderboard gamifies AI usage, driving internal adoption.
• Marketers become builders, delivering customer‑focused experiences without engineers.
• Automator platform lets any team create quests for AI‑generated code.
• Experience points reward contributions, fostering a culture of rapid innovation.

Summary

John Kim, CEO of Sunbird, outlines an "AI adoption playbook" that turns internal ideas into production‑ready tools through AI‑driven quests, a token consumption leaderboard, and a skills marketplace. The approach treats AI as a product, empowering marketers, salespeople, and other non‑engineers to request and co‑create automation without waiting for traditional engineering cycles.

Key insights include a company‑wide token leaderboard that ranks users from "AI newbie" to "AI god," incentivizing usage through gamification. Sunbird’s internal "Automator" platform lets any employee raise a "quest"—a specification that AI can read, generate PRDs for, and even code. The system integrates pre‑built security, authentication, and deployment templates (via Work OS) so creators focus solely on the business logic.

Notable examples illustrate the concept: a marketing‑built swag store launched in days, complete with Stripe integration and a hidden Konami‑code Easter egg; weekly stand‑ups where teams showcase quest outcomes; and an experience‑point system that rewards contributors with gift cards or executive coffee. Kim emphasizes that AI should be a workforce capability, not just a speed‑up tool.

The broader implication is a cultural shift toward democratized AI development, reducing bottlenecks, accelerating time‑to‑market, and fostering continuous learning. By embedding security and compliance into the platform, enterprises can scale AI adoption without compromising governance, positioning themselves as truly "AI‑first" organizations.

Original Description

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:

1. How Sendbird’s marketing team built a fully functional swag store with Stripe integration in a day (with no engineering support)

2. How the Automators platform works—an internal marketplace where anyone can request AI tools and engineers (or AI agents) can build them

3. How to create secure, compliant templates so non-technical teams can ship to production safely

4. How 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 total

5. Why visible leadership usage is the most powerful adoption signal

6. Why Sendbird rewrote job descriptions to prioritize curiosity, agency, and energy over years of experience

7. How John uses AI for his own learning

Brought to you by:

WorkOS—Make your app enterprise-ready today: https://workos.com?utm_source=lennys_howiai&utm_medium=podcast&utm_campaign=q22025

ThoughtSpot—Build AI-powered analytics into your product: https://go.thoughtspot.com/howIAI

In this episode, we cover:

(00:00) Introduction to John Kim

(02:45) The Delight.ai swag store built by marketing in two days

(05:51) The before times: when fun had to earn its place on the roadmap

(07:55) Demo: The Automators platform and quest system

(13:47) The AI Engineer for Internal Operations role

(16:06) Demo: The company-wide skills marketplace

(17:19) Treating AI adoption as a product

(18:43) Real wins: team-level and campaign examples

(21:51) Why SaaS isn’t dead—it’s being rebuilt internally

(23:46) Demo: The token tracking dashboard

(26:32) Measuring without fear: setting expectations, not punishments

(28:54) Quick recap

(30:51) Personal AI use cases: endless knowledge at your fingertips

(36:15) Lightning round and final thoughts

Tools referenced:

• Claude Code: https://claude.ai/code

• Codex (OpenAI): https://openai.com/codex

• Obsidian: https://obsidian.md

• GitHub: https://github.com

• Stripe: https://stripe.com

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/

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

Delight.ai Spark Conference (May 7, SF): https://delight.ai/spark

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

_Production and marketing by https://penname.co/._

_For inquiries about sponsoring the podcast, email [e-mail]._