CTO Circle brings 350 engineering leaders together to share lessons on building AI-native organizations

The CTO Circle event reflects a broader challenge facing engineering leadership: there is no established playbook for building AI-native organizations, and competitive pressures have kept these conversations largely private within individual companies. Snowflake's decision to convene this peer forum addresses a real gap—engineering leaders need to compare what works in production and challenge assumptions about team structure, investment priorities, and risk management as AI becomes embedded throughout the software development lifecycle.

The three themes that emerged from the discussion—AI in production, velocity-and-risk balance, and team design—represent a maturation of AI adoption beyond early coding assistants. Snowflake's own transformation demonstrates that treating developer productivity as a customer problem, then institutionalizing successful workflows into organizational knowledge, creates measurable competitive advantage. This approach differs fundamentally from simply deploying another AI tool; instead, it emphasizes depth of usage, mastery, and optimization as the stages through which organizations must progress. Similarly, Jeremy Burton's argument that context (semantics, ontologies, APIs, business relationships) matters as much as data quality, and Aditya Gaur's example of Netflix's investment in data architecture before AI agents, underscore that production success depends on foundational infrastructure decisions, not AI models alone. The tension between velocity and governance—highlighted by Chris Kozlowski's emphasis on matched speed and control in regulated environments—signals that the organizations moving fastest are those investing deliberately in both innovation and reliability.