Devin Oncall Sends an AI Agent to Production Alerts

Cognition has launched Devin Oncall, a product that turns production alerts into tasks for its coding agent. When an observability platform reports an incident, Devin opens an investigation, examines the available telemetry and code, then returns a diagnosis or creates a pull request.

The product extends Devin from planned development work into incident response. Cognition wants its agent to complete the initial investigation before an engineer joins, reducing the time spent searching logs, tracing deployments, and identifying the relevant service or repository.

Alerts Become Agent Sessions

Devin Oncall sits between monitoring systems and engineering workflows. Cognition lists integrations with Datadog, Dynatrace, Sentry, and other observability platforms. Those systems continue to detect incidents and generate alerts; Oncall consumes the payloads and begins the investigation.

1. The observability platform sends Devin an alert and its associated context.
2. Devin opens a session with access to its shell, editor, browser, connected repositories, and permitted infrastructure.
3. The agent inspects logs, code, recent deployments, and relevant documentation to test possible causes.
4. Devin posts its findings or prepares a code change as a pull request.
5. Engineers review the evidence, approve changes, or take over when the incident requires broader judgment.

The published workflow preserves existing review, CI, merge, and deployment controls when Devin proposes a patch. That boundary matters during an outage because a pull request is reversible and reviewable, while an automated production change carries a larger operational risk.

The Same Devin, Triggered by Production

Oncall uses the existing Devin platform as a new trigger. An alert can open the same kind of coding session that Devin uses for planned work, allowing the agent to move from diagnosis to implementation while retaining the investigation context.

Cognition’s Model Context Protocol tools expose sessions, playbooks, knowledge, schedules, integrations, and repository documentation. MCP provides a standard interface through which systems can supply tools and context to an AI agent. Oncall builds on that toolset, so runbooks, service documentation, and repository knowledge can guide the incident session.

The agent’s reach depends on the permissions attached to those integrations. Repository access allows code inspection and pull requests, while access to logs, cloud consoles, deployment history, or secrets creates additional security requirements. Teams will need to apply least-privilege credentials and preserve audit records for every action.

Early Data Shows a Triage-Heavy Workload

Cognition says Devin Oncall already processes thousands of alerts per day for large customers. Its customer profile for document AI company Reducto says the agent serves as the first responder and has reduced the frequency with which engineers receive pages.

Cognition also uses the workflow internally, routing Datadog alerts into Slack for Devin to investigate. In a recent presentation, one of its engineers said fewer than 2% of alerts resulted in code changes. The company has not published the sample size, measurement period, or severity mix behind that figure.

The under-2% rate indicates that pull requests represent a small part of the workload. Many investigations may end with a false alarm, an operational explanation, a configuration issue, or an escalation that requires human action. Useful evaluation therefore requires more than counting generated patches.

Incident Response Is Filling With Agents

Cognition is expanding Devin across more stages of software delivery, including code review, automated triage, code scanning, scheduled work, and production support. The company says Devin now writes 89% of its internal pull requests. It has also reported more than $2 billion in funding at a $48 billion valuation, enterprise usage growth above tenfold since the start of the year, and $492 million in run-rate revenue.

AWS has previewed a competing DevOps Agent that correlates metrics, logs, and recent deployments to identify likely causes and recommend mitigations. Datadog, Dynatrace, and New Relic also offer AI-assisted root-cause analysis. Cognition’s differentiator is the connection to a general coding agent that can inspect a repository, edit code, run tests, and submit the resulting patch.

Checks Before Granting Pager Access

Production incidents expose an agent to incomplete evidence, rapidly changing systems, and pressure to act. A useful deployment plan should define the agent’s scope before alerts begin opening autonomous sessions.

Cognition’s announcement does not list public pricing, a complete integration matrix, or a service-level commitment. Deployment architecture, data retention, permission boundaries, and the availability of individual integrations will require confirmation during evaluation.

The Pager Becomes a Work Queue

Devin Oncall makes production alerts another entry point into an agent-driven engineering workflow. Its practical value will depend on the quality of each diagnosis, the evidence attached to escalations, and the safety of the permissions granted to the agent.

Observability platforms supply the signals, while Devin adds investigation and code execution above them. If the product consistently filters routine alerts and prepares credible fixes, on-call engineers can begin incidents with a tested hypothesis and a documented trail instead of an unexplained page.