In a leaked internal memo, Opendoor's CEO established a new standard for becoming an 'AI native' company. Employee job expectations and performance reviews will now explicitly measure how frequently they 'default to AI' tools over traditional software like Google Docs for their work.
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Formal AI competency frameworks are still emerging. In their place, innovative companies are assessing employee AI skills with concrete, activity-based targets like "build three custom GPTs for your role" or completing specific certifications, directly linking these achievements to performance reviews.
Competing in the AI era requires a fundamental cultural shift towards experimentation and scientific rigor. According to Intercom's CEO, older companies can't just decide to build an AI feature; they need a complete operational reset to match the speed and learning cycles of AI-native disruptors.
To achieve hyper-growth ($40M+ ARR in year one), your product isn't enough. Every internal function—finance, legal, contracting, customer onboarding—must also be AI-native to process deals and deliver value at a velocity that matches sales success.
Dr. Fei-Fei Li states she won't hire any software engineer who doesn't embrace AI collaborative tools. This isn't about the tools' perfection, but what their adoption signals: a candidate's open-mindedness, ability to grow with new toolkits, and potential to "superpower" their own work.
According to Goodhart's Law, when a measure becomes a target, it ceases to be a good measure. If you incentivize employees on AI-driven metrics like 'emails sent,' they will optimize for the number, not quality, corrupting the data and giving false signals of productivity.
Moving beyond casual experimentation with AI requires a cultural mandate for frequent, deep integration. Employees should engage with generative AI tools multiple times every hour to ideate, create, or validate work, treating it as an ever-present collaborator rather than an occasional tool.
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.
To accelerate AI adoption and overcome fear of displacement, OneMind's CEO has a policy to financially reward and find new roles for employees who successfully eliminate their own positions using AI. This turns a threat into an incentive for innovation.
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.
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.
