Uber Engineering

Every tool an AI agent can use expands its capabilities and its attack surface. Even an authorized action can take an agent somewhere the user never intended.

Uber engineers are building protections across the agent lifecycle to keep actions aligned with user intent and session context. Making those controls effective in production means balancing security with latency, autonomy, and legitimate tasks.

See what we learned about designing and deploying agent security:

More than 200,000 CPU cores power Uber’s data lake ingestion. At that scale, every efficiency gain counts.

Making better use of that compute means examining how Spark executes queries, moves data, and writes to growing tables. Accelerating one stage can leave other bottlenecks untouched.

Uber engineers are improving production workloads with native vectorized execution and evaluating new ways to accelerate write-heavy pipelines.

Explore the engineering choices behind those efforts, where the benchmarks showed gains, and what remains to be optimized.

Technical talks, fresh perspectives, and a community ready to connect. Our mini GHC day at Uber had plenty to celebrate!

After the cancellation of GHC, the Uber community rallied to talk engineering and have some fun. We were especially excited to welcome @EricaLockheimer from HumanizeHer to share her experience and perspective.

Thanks to everyone who took the stage and joined the conversations!