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When Cloud Agents Make Sense

This guide helps you decide whether cloud agents are the right abstraction for your problem.
Use cloud agents when the work is recurring, spans multiple systems, and needs team-owned outcomes. If you want the canonical definition and taxonomy first, read: Cloud Agents Taxonomy.
Use cloud agents when:
  • The same class of issue returns weekly (or daily)
  • The work is mostly handling (triage, patching, cleanup), not discovery
  • Inputs come from tools like GitHub, error monitoring, security scanners, analytics
  • You need a reviewable outcome (PR, report, ticket update)
  • You want to reduce interruptions, not just respond faster

Great fits

  • security remediation
  • recurring error triage
  • dependency hygiene
  • analytics-driven fixes

Common triggers

  • task dispatch
  • schedules
  • event webhooks

When Cloud Agents Are a Bad Idea

Avoid cloud agents when:
  • The problem is novel and poorly understood
  • The blast radius is unclear
  • Ownership is ambiguous (“someone should handle this”)
  • You can’t define review criteria
  • The work is better solved by eliminating the root cause directly
Cloud agents amplify whatever system you already have. If ownership is unclear, automation will make it worse.

Cloud Agents vs Alternatives

Comparison Matrix

FeatureScripts / CI JobsLocal Agents (TUI)Cloud Agents (Headless)
LogicDeterministic (If/Then)AI / ProbabilisticAI / Probabilistic
ContextInputs onlyFull Repo + User ChatRepo + Integrations (Snyk/GitHub/etc.)
InteractionNone (Logs only)Interactive (Conversations)Autonomous (Fire & Forget)
Tool AccessUnlimitedAll (Ask permission supported)Safe (No “Ask” tools)
Best ForTesting, Building, LintingDebugging, Refactoring, ExplorationTriage, Remediation, Reporting

The Decision Checklist

Use cloud agents if you can say “yes” to most of these:
  • We’ve seen this problem at least twice
  • Inputs come from shared systems (alerts, issues, analytics)
  • We can define what “good output” looks like
  • A PR/report is an acceptable artifact
  • Someone owns reviewing the result
  • We can start in a manual or assisted mode
If you’re unsure, start with a one-off task and treat it like an experiment.

Where to Go Next