A fair question at this point: how is an agent different from a cron job or a CI script that just runs code? The answer is the intelligence layer, four things an agent does that a script does not.

Context retrieval. Before acting, Devin reads the codebase, consults DeepWiki, queries connected integrations (Jira, Datadog, Confluence), and pulls relevant Knowledge notes. It builds understanding of the system before it changes anything, the way a human engineer reads docs and code before starting.

Decision-making. It chooses an implementation approach, decides which files to touch, and picks a testing strategy. When something breaks, it reads the error, diagnoses the issue, and tries a different path.

Verification. It runs your build and test suite, monitors CI after pushing, and iterates until checks pass or escalates when it cannot resolve an issue on its own.

Communication. It opens PRs with context-rich descriptions, responds to review comments, and posts status updates in your existing channels (GitHub, Slack, Teams).

A cron job runs the same commands every time. An intelligent agent reads context, makes decisions, adapts to failure, and reports back: the same workflow a human engineer follows, at machine speed.

Once agents are part of your capacity rather than a tool you reach for, the shape of a sprint changes.

	Before (humans only)	After (humans + agents)
Planning	Accounts for 100% human-hours	Separates human-judgment work from well-defined implementable work
Maintenance	Competes with features for the same capacity	Runs on a schedule without eating sprint capacity
Campaigns	Migrations and upgrades drag on for months	Parallelize across agents, finish in weeks
Reactive work	Incidents and CI failures interrupt deep work	Handled by event-driven agents, reviewed asynchronously

The key insight: adding agent capacity does not replace engineers, it changes what they spend their time on. Work that was perpetually deferred (maintenance, coverage, upgrades, compliance) finally gets done, and engineers concentrate on the architecture, design, and judgment calls only humans can make.

Key takeaways

The intelligence layer (context retrieval, decision-making, verification, communication) is what separates an agent from a script.
Before agents, maintenance competes with features; after, it runs on a schedule while campaigns parallelize and reactive work is handled async.
More agent capacity does not shrink the team's role, it elevates focus to the problems only humans can solve.

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