Skip to main content

​
AI DevOps

AI DevOps in Cloudgeni is the agent-session workflow exposed in the app at Agent Sessions. It is the shared execution surface behind:
  • Direct agent chats
  • Some remediation handoffs
  • Cloud resource import handoffs
  • Session resume and fork workflows

​
What It Is Good For

Use an agent session when you want Cloudgeni to work with repository context rather than only show scan output. Typical use cases:
  • Draft new IaC for a requested change
  • Refactor or explain existing IaC
  • Continue from a finding or remediation thread
  • Import existing cloud resources into a repository structure

​
How A Session Works

  1. Open Agent Sessions
  2. Pick the repository or repositories you want the agent to work in
  3. Optionally attach cloud and documentation context
  4. Submit the prompt
  5. Watch the streamed conversation and tool output
  6. Resume or fork the session if you want a second pass
The backend service is run-oriented. A single session can have multiple runs over time, which is why resume and fork are first-class behaviors in the codebase rather than add-ons.

​
Terminal Workflow

Use the CLI when you want to work with the same agent sessions from a terminal. 
cloudgeni org use
cloudgeni agent
cloudgeni agent opens the active session for the selected organization. To send a single prompt and stream the result: 
cloudgeni agent "Investigate the latest drift and propose the smallest safe change"
For automation or another coding agent: 
cloudgeni agent run "Draft the Terraform change" \
  --repo <repo>:<branch> \
  --cloud-integration <integration> \
  --watch

​
What The Agent Can Use As Context

The current app supports a guided launch model with context selectors for:
  • Repositories
  • Cloud integrations
  • Documentation integrations
That makes the session composer more useful than a plain prompt box. Use it.

​
How Changes Land

Agent sessions are still Git workflows. The useful output is usually:
  • File changes in the selected repository
  • A branch or pull request
  • A follow-up review cycle
The product is not designed around the agent writing directly to production infrastructure.

​
When Not To Start Here

If you only want an initial security signal, Static Analysis or Cloud Compliance is usually a better first step. Start with AI DevOps when you already know you want generated or edited repository changes.

Cloud Resource Import

Start from discovered resources and hand off into an agent session.

Pull Request Reviews

Use agents on incoming pull requests rather than only in interactive sessions.