This article addresses the persistent gap between organizational investment in learning and development (L&D) and actual workforce skill acquisition. The author argues that traditional training-focused approaches fail because they prioritize content delivery over genuine learning, and that a fundamental cultural shift is required. The central argument draws on David Perkins' Theory One from Harvard University, which posits that people learn what they have both the opportunity and motivation to learn. The author contends that linking skill attainment to performance management creates the extrinsic motivation necessary to drive a 'pull learning economy,' wherein employees actively demand high-impact learning opportunities rather than passively receiving pushed training content. Key evidence is largely prescriptive rather than empirical, comprising practitioner recommendations across five areas: improving training quality, implementing capability academies, supporting informal learning, integrating generative AI tools, and adopting learning technology. The article concludes that transforming to a continuous learning culture is a multi-year, organization-wide endeavor requiring both short-term tactical action and long-term systemic change. Key insights: David Perkins' Theory One — that people learn what they have reasonable opportunity and motivation to learn — is presented as the foundational principle for designing a continuous learning culture. Most organizations operate a 'push' learning economy where training is delivered with low employee uptake; linking skill gaps to performance management outcomes is proposed as a mechanism to shift to a 'pull' economy driven by employee demand. Informal learning is identified as the dominant mode of workplace skill development, yet it remains underinvested and insufficiently visible within most L&D infrastructures. Practical takeaways: Connecting skills gap data to performance management processes can create extrinsic motivation that encourages employees to prioritize learning amid competing demands. Diversifying learning content formats — blending formal courses with articles, peer-created modules, mentoring, and generative AI tools — addresses different learning preferences and contexts.