Agentic SDLC at Uber — Uday Kiran Medisetty & Adam Huda, Uber
Uber has implemented a comprehensive 'Software Factory' powered by agentic AI to revolutionize its SDLC. Key infrastructure investments include a centralized Model Gateway for security and latency control, an MCP Gateway for token optimization, and a Context Graph that unifies knowledge across disparate systems. These building blocks enable autonomous agents (like Minion) to accelerate development from idea generation (via Cortana) through drafting PRs, validating changes in inner loops (e.g., comparing simulator screenshots against Figma specs), and managing maintenance tasks.
Key takeaways
-
Agentic Adoption Metrics
Over the last year, agentic AI led to more than 70% of Uber's Pull Requests (PRs) originating from local or cloud agents, resulting in double the lines of code per engineer year-over-year.
-
Model Gateway Performance
2:06
The Model Gateway handles all internal model calls through a single endpoint, ensuring PII redaction for over 20 types and running five specialized safety models under a strict 100 millisecond guardrail budget. It processes over 100 million requests daily across 800+ projects.
-
Token Optimization
5:51
The MCP Gateway, combined with projecting MCPS into CLI patterns and using Omni MCP, cut fleetwide token usage by more than 40%.