What Cognition Learned Building Cloud Agents for Enterprise Engineering Orgs
Building cloud agent infrastructure requires solving three interconnected challenges that containerized approaches cannot address: shared-kernel security threats, inability to persist agent state across the async gaps of real engineering work, and the massive orchestration and governance investment needed to operate at enterprise scale.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Engineer delegates task
An engineer defines and delegates a software engineering task precisely enough that the agent can execute without constant correction.
Tools used
DevinmicroVMs
Outcome
Itaú, the largest private bank in Latin America, deployed cloud agents across nearly 17,000 engineers and after eleven months completed migrations 5 to 6x faster, auto-remediated 70% of static-analysis security vulnerabilities, and increased test coverage by 2x.
What failed first
A leading cloud data platform company attempted to build in-house cloud agent infrastructure but abandoned the project because the combined scope of orchestration, governance, and integrations overwhelmed their infrastructure team.
Results
Volume5 to 6x faster
Running sinceeleven months in (relative to publication)