How I AI

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

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Key takeaways

  • Turn AI adoption into a cultural movement by empowering curious employees and celebrating their projects.
  • Build internal platforms like automator quest systems and skills marketplaces to lower barriers for AI experimentation and internal tool building.
  • Measure AI engagement with dashboards and token leaderboards to provide visibility and motivate continuous learning.
  • Leverage leadership and visible usage to signal the importance of AI and inspire broader adoption across all levels.
  • Encourage a curiosity-driven, fun, and fail-forward environment to foster internal innovation and knowledge sharing.
  • Use AI for personalized learning, knowledge management, and internal projects to unlock creative potential and deepen engagement.
  • Create clear expectations around AI use and foster a supportive environment to reduce fear and build confidence.

Summary

Transforming Company Culture with AI: Leadership, Adoption, and Fun

This section explores how John Kim emphasizes the importance of making AI part of the company's culture and operations. He discusses turning AI adoption into a company-wide movement by encouraging curiosity, energy, and agency among employees. John highlights the value of leadership involvement, visible usage, and measurement—like token leaderboards and dashboards—to foster transparency and motivate teams. He also advocates for fun projects, such as building swag stores or smart campaigns, to inspire internal innovation and engagement, viewing these efforts as vital to creating an AI-first organization.

Internal Tools as a Catalyst for AI Adoption: The Automators Platform & Skills Marketplace

This section delves into the platforms and systems John Kim’s team has built to lower barriers for AI experimentation within the company. The Automators platform allows anyone to propose and collaborate on AI quests—autonomous automation projects that anyone can initiate. AI agents can assist in building these projects, significantly accelerating development. Additionally, a skills marketplace enables internal teams to share and access AI skills and plugins across functions, fostering a culture of co-evolution and internal expertise sharing. These initiatives support rapid, creative, and compliant internal tool development.

Tracking and Measuring AI Usage: Token Leaderboards and Adoption Metrics

This part discusses how Sendbird tracks token consumption and usage patterns to measure AI engagement without introducing a punitive atmosphere. They use dashboards that display token usage, with tiers from 'beginner' to 'AI God,' helping teams and individuals understand their level of AI maturity. Leadership participation is encouraged to set examples and signal the importance of AI, which in turn promotes broader adoption. The system’s goal is to smooth token usage curves, ensuring continuous AI activity even during staff vacations, and to build a clear vision of what it means to be an AI-native organization.

Democratizing AI and Building a Learning Culture: Personal Use Cases & Education

In this section, John Kim shares his personal AI projects for learning and knowledge management, such as creating a personal neuroscience curriculum and a gardening-style knowledge base. He advocates for using AI to deepen engagement with topics, rather than replacing critical thinking. The conversation emphasizes that cultivating a curiosity-driven culture—by emphasizing high agency, curiosity, and continuous learning—is crucial. He also highlights the importance of onboarding and continuously educating teams through templates, guides, and internal workshops to turn internal tools into learning accelerators.

Practical Advice for Organizations and Individuals: Cultivating AI Culture & Personal Projects

This final section provides actionable insights for leaders seeking to embed AI into their organizations. John Kim advises identifying curious champions within teams, demonstrating leadership’s own participation, and setting clear expectations on AI usage. He underscores the importance of measurement and transparency while maintaining a positive, failure-tolerant environment. On a personal level, he shares his enthusiasm for building knowledge bases and leveraging AI for self-directed learning, highlighting that the era of playful experimentation and internal innovation is now accessible and rewarding.

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Show notes

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

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Brought to you by:

WorkOS—Make your app enterprise-ready today

ThoughtSpot—Build AI-powered analytics into your product

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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

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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

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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

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 jordan@penname.co.

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