Quests, token leaderboards, and a skills marketplace: the elite AI adoption playbook | John Kim

2026-05-06 · Source: How I AI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Robotics & Autonomous Systems · Depth: Intermediate, extended

Summary

Sunbird CEO John Kim details an internal AI adoption strategy centered on an "Automator Platform" and "quests" that empower non-engineering teams, such as marketing, to build AI-powered tools without traditional engineering support. This approach fosters a "marketplace of AI needs and AI builders" within the company, enabling rapid development of custom solutions like a marketing-built swag store with Stripe integration. The company also measures AI engagement through a token consumption leaderboard, categorizing employees from "AI newbie" to "AI god" based on daily token usage (over 100 million tokens for an AI god). This system aims to smooth AI adoption, identify internal champions, and integrate AI as a core part of the workforce, moving towards an "AI-first" company culture.

Key takeaway

For Directors of AI/ML or VPs of Engineering aiming to drive company-wide AI adoption, focus on decentralizing AI development. Build an internal platform that enables non-technical teams to create AI-powered solutions, providing secure templates and clear guidelines. Measure AI token consumption to identify and support internal champions, fostering a culture where AI is integrated into daily workflows rather than confined to a centralized engineering roadmap. This approach cultivates rapid, relevant innovation and boosts team engagement.

Key insights

Empowering non-technical teams with AI-building platforms accelerates internal innovation and fosters an AI-first company culture.

Principles

• Cultivate curiosity and agency in hiring.
• Leadership must actively model AI adoption.
• Innovation thrives on individual energy and stories.

Method

Implement an internal "Automator Platform" for AI quests, allowing any employee to request or build AI automations. Provide templated, secure production environments and measure token consumption to track adoption and identify champions.

In practice

• Build a templated, secure production path for internal AI tools.
• Measure AI token usage to track adoption and identify power users.
• Create an internal marketplace for AI needs and builders.

Topics

• AI Adoption Strategy
• Internal AI Platforms
• AI Token Consumption
• AI Skills Marketplace
• Employee Empowerment

Best for: CTO, Executive, Entrepreneur, Director of AI/ML, VP of Engineering/Data, AI Engineer

Related on AIssential

• Quests, token leaderboards, and a skills marketplace: The elite AI adoption playbook | John Kim (Sendbird) — Sendbird's internal AI platform and gamified adoption strategy empower non-technical teams to build and deploy AI-powered solutions.
• How Coinbase scaled AI to 1,000+ engineers | Chintan Turakhia — Driving AI adoption in large engineering organizations requires hands-on leadership, automating toil, and data-driven user analysis.
• From Overwhelmed to Empowered: A CEO’s Guide to AI — Effective AI adoption for leaders focuses on practical application and human-centric strategies, not deep technical understanding.
• How AI is changing Software Engineering: A Conversation with Gergely Orosz, @pragmaticengineer — Measuring AI token output can lead to counterproductive "token maxing" behavior among engineers.
• How to Build an AI Native Team with Mike Cannon-Brookes — Enterprise AI leadership hinges on thoughtful, aggressive adoption, prioritizing context, and integrating AI into existing workflows while exploring new paradigms.
• How the Best Companies Use AI — Leading companies treat AI as a growth engine, building institutional systems that empower all employees, not just individual users.

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Editorial summary, takeaway, and curation by AIssential. Original article published by How I AI.