by Rohit Agrawal, Shuyu Cao, Darming Zhao, Zack Siegel and Aaron Davidson
• At Databricks, we govern AI spend at scale by routing every coding agent through Unity AI Gateway, giving our teams one place to enforce budgets, visibility, and policies across every model and tool.
• We balance innovation with cost control, using separate daily and monthly budgets that stop runaway AI spend while keeping our engineers productive with self-service budget increases instead of approval bottlenecks.
• This proven governance model combines centralized spend controls, unified observability, and data-driven policy enforcement to scale AI adoption without slowing our developers down.
At Databricks, the way we build software is changing quickly as we aggressively adopt AI for engineering. Thousands of our engineers use coding agents every day, mixing between Claude Code, Codex, Cursor, and others, often several at once. That adoption is great, but it creates a new problem: coding agent spend is now one of the fastest growing line items in R&D, and a single runaway automation loop can burn through a month of budget in an afternoon.
