🔗 The system around the code

Many organizations experience an enthusiasm deflation when it comes to implementing the latest AI solutions. Zarar Siddiqi highlights that while dazzling demos captivate many, the harder truth involves the systems surrounding code rather than the code itself. Years of experience remind us that the path to deployment is often clouded by structural and organizational issues. A key example cited is an incident in which a developer's mistake was mischaracterized as an AI problem when in fact, the issue stemmed from poor engineering practices. This article emphasizes the importance of understanding these systems and structures to avoid repeating past mistakes. Siddiqi addresses how the transition to AI requires a focus on building robust systems that can manage increased complexity rather than merely implementing AI tools without consideration for their context and impact.