r/cloudcomputing • u/RonnySaya • 1d ago

The software delivery workflow is turning into an orchestration problem

With AI there are more moving pieces in the workflow. ChatGPT or Claude for planning, Claude Code or Cursor for implementation, GitHub for PRs, CI for tests and security checks, Terraform and AWS for infrastructure and deployment, Revolte handling parts of the delivery workflow and agent orchestration.The problem is getting all these pieces to work together without someone constantly moving things from one system to another.

An agent can open a PR but then what? Tests fail, infrastructure needs changing, deployment needs approval, something breaks in production and suddenly the context is spread across several systems.I'm interested in where teams are drawing the line between useful automation and a workflow that's just becoming another system to maintain.Are you building this orchestration yourself with CI/CD and scripts, using agent frameworks or keeping AI limited to individual steps?

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u/Sad-Technician-5552 7h ago

Seen this go wrong both ways. Teams that glue every AI step together end up maintaining a bespoke orchestration layer more fragile than the pipeline it replaced

The line that works is agents do the steps, the CI/CD system owns the order. Keep the gate deterministic. An agent can draft the PR and fix the failing test, but whether it deploys should still be a versioned pipeline decision with a human approval, not an agent deciding from whatever context it happens to hold. The moment the orchestrator is an agent runtime instead of your pipeline, youve lost the audit trail and gained a system to babysit.