New playbook: when your own AI model pays. Read
Uber (mobility and delivery) reported this on 27 Aug 2026 in company self-report (source). It belongs to the agents, traceability and evals layer.
A "software factory" of managed agents that handle code review, self-healing CI failures, end-to-end PRs with visual validation, on-call triage and bug debugging, grounded by a 24M-node context graph and with spend alerts and manager sign-off for tier upgrades.
More than 70% of pull requests attributed to agents; 30K+ agent skill executions a day; cost per session down 52% from its June 2026 peak.
The number covers uber engineering and internal agent users.
“…handling a variety of code maintenance tasks with human reviews/escalations,” Uber said.
Agent work flows through human reviews and escalations; budget alerts at 50/80/100% of expected spend; manager approval for higher-cost tiers.
Each agent has one narrow task, a named owner and an action log.
12,500
banker hours saved in the first month of operation, July 2026
Five specialist agents on Amazon Bedrock AgentCore that classify and read payslips and bank statements, run serviceability calculations and verify them against lending policy, then hand the banker a result to review for mortgage and credit-card applications (source).
$10M
EBITDA uplift from two agent systems, Partners Group says
Two agentic systems built on a cleaned proprietary policy-level dataset: one runs new-client policy processing, the other automates human-intensive policy checking; delivered by a seven-person team with Version 1 (source).
2–3 minutes
per ocean or air freight quote, down from one to three days
Hundreds of in-house AI agents embedded across the shipment lifecycle (quoting, orders, appointments, missed-pickup checks) and now ocean and air quoting, ocean booking and customs brokerage, built and run under a lean waste-removal discipline by 450+ in-house engineers and data scientists (source).