While it can feel frustrating, mandating that teams use AI tools daily is a "necessary evil." This aggressive approach forces rapid adoption and internal learning, allowing a company to disrupt itself before competitors do. The speed of AI's impact makes this an uncomfortable but critical survival strategy.

To get teams experimenting with AI, leaders should provide an open budget for tokens initially. Being 'profligate' at the start is crucial, as imposing constraints too early leads to unimpressive results, stifles creativity, and hinders true adoption. Efficiency can be optimized later.

A trend called "tokenmaxxing" is emerging in Silicon Valley, where companies like Meta use leaderboards to track employee AI token usage. This reflects a corporate bet that higher token consumption correlates with increased productivity, turning AI usage into a new, albeit gameable, performance metric for engineers.

Gamifying AI token consumption via internal leaderboards, as seen at Meta, creates perverse incentives. Employees may burn tokens to climb the ranks rather than to solve real business problems. This "tokenmaxxing" promotes conspicuous consumption of compute, a vanity metric that masks true productivity and ROI.

True AI-native companies apply AI beyond their external products. They create dedicated internal teams to help employees leverage new AI tools, like LLMs, to boost their own productivity. This is a deliberate, culturally ingrained motion to ensure the entire organization moves with technological shifts.

To accelerate company-wide skill development, Shopify's CEO mandated that learning and utilizing AI become a formal component of employee performance evaluations. This top-down directive ensured rapid, broad adoption and transformed the company's culture to be 'AI forward,' giving them a competitive edge.

Recognizing that providing tools is insufficient, LinkedIn is making "AI agency and fluency" a core part of its performance evaluation and calibration process. This formalizes the expectation that employees must actively use AI tools to succeed, moving adoption from voluntary to a career necessity.

To accelerate its internal AI transformation, Meta is now grading employees on their use of company-provided AI tools as part of their performance reviews. This tactic moves AI from an optional productivity enhancer to a mandatory part of the job, creating powerful incentives for adoption and cultural change across the organization.

The most successful companies are those that fundamentally re-architect their culture and workflows around AI. This goes beyond implementing tools; it involves a top-down mandate to prepare the entire organization for future, more powerful AI, as exemplified by AppLovin's aggressive adoption strategy.