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.
Instead of a generalist AI, LinkedIn built a suite of specialized internal agents for tasks like trust reviews, growth analysis, and user research. These agents are trained on LinkedIn's unique historical data and playbooks, providing critiques and insights impossible for external tools.
LinkedIn is piloting a "Full Stack Builder" model where individuals handle the entire product lifecycle. The model's goal is to automate most tasks, allowing builders to focus on uniquely human traits: vision, empathy, communication, creativity, and especially judgment.
LinkedIn's CPO reveals their unique data shows the skills needed for current jobs will change by 70% in just a few years. This rapid obsolescence is the primary driver for rethinking product development, as companies must adapt faster than ever to stay competitive.
A critical learning at LinkedIn was that pointing an AI at an entire company drive for context results in poor performance and hallucinations. The team had to manually curate "golden examples" and specific knowledge bases to train agents effectively, as the AI couldn't discern quality on its own.
Despite the hype, LinkedIn found that third-party AI tools for coding and design don't work out-of-the-box on their complex, legacy stack. Success requires deep customization, re-architecting internal platforms for AI reasoning, and working in "alpha mode" with vendors to adapt their tools.
In a radical shift, LinkedIn is ending its traditional Associate Product Manager (APM) program. It's being replaced by an Associate Product Builder (APB) program where new hires are trained from day one in coding, design, and product management, reflecting the move toward a consolidated, AI-powered builder role.
While many believe AI will primarily help average performers become great, LinkedIn's experience shows the opposite. Their top talent were the first and most effective adopters of new AI tools, using them to become even more productive. This suggests AI may amplify existing talent disparities.