Episode Details

In this newsletter, technology leader Indy Sawhney introduces the concept of workflow gravity, a phenomenon where institutional knowledge and team habits become deeply embedded within specific AI platforms. Unlike the data-centric migrations of the cloud era, this new form of vendor lock-in is driven by the cognitive muscle memory and custom integrations developed by employees. The text highlights how major tech companies use different entry points—from no-code tools to developer APIs—to capture enterprise workflows and create high switching costs. To combat this, Sawhney encourages leaders to maintain architectural discipline by clearly separating their proprietary logic from the platform's core functions. By prioritizing composability and optionality, organizations can prevent accidental dependencies and retain strategic leverage as they scale their AI adoption. This edition serves as a practical guide for executives to recognize and manage the unintended long-term costs of distributed AI decision-making.