AI Developer and DevOps Agents for Code and Ops
Engineering teams lose hours to the work around the code: reviewing pull requests, chasing failed pipelines, writing changelogs and keeping docs current. The Developer & DevOps range takes on that work with agents for code review, QA, incident triage, testing and documentation. Many come in editions that connect natively to GitHub, GitLab, Bitbucket, Jira or Slack.
Products in this category
What work do these agents take off your plate?
Think of the tasks that pile up between releases. The AI Code Review Agent comments inline on pull requests about bugs, security issues and standards. AI Test Generation writes unit and integration tests for existing code. The AI Dependency Update Agent proposes and tests upgrades as pull requests your team can review before anything is merged.
- Inline code review on pull requests
- Structured test plans with defect evidence
- Pipeline failure diagnosis with proposed fixes
- Grouped alerts and drafted incident updates
- Docs, API references and changelogs from your work
Should you pick a core product or a tool edition?
The core products describe the job, and the editions describe where the job happens. If your code lives in GitHub, the AI Code Review Agent for GitHub reads and updates repositories, pull requests, issues and checks there. Teams on GitLab or Bitbucket have matching editions of both the code review agent and the AI DevOps Agent.
Incident work follows the same pattern. AI Incident Triage for Jira works with issues and comments, the Slack edition works in approved channels, and the GitHub edition reads recent commits, pull requests and deployments. Choose the edition that matches where your team already talks about incidents.
What about on-call support and documentation?
On-call engineers often need context more than code. The AI On-Call Assistant brings runbooks, context and next steps together, and AI Log Analysis summarizes logs and surfaces error patterns. For docs, the AI Documentation Agent maintains technical docs from code and specs, AI API Documentation builds references from API definitions, and the AI Changelog Generator writes release notes from merged work.
Questions buyers ask
Does the code review agent change code on its own?
The AI Code Review Agent reviews pull requests and leaves inline comments. Fixes from the AI DevOps Agent arrive as proposals, and the AI Dependency Update Agent opens pull requests for your team to review. Your engineers stay in charge of what gets merged, and each product's Scope Card spells out what it reads and updates.
Is there a GitLab edition of the QA agent?
Yes. The AI QA Agent for GitLab runs structured test plans against your application and reports defects with evidence, and it reads and updates GitLab projects, merge requests and pipelines. There is a GitHub edition too. If your team uses neither platform, take a look at the core AI QA Agent, which does the same job.
Where do these engineering agents run?
Inside your own accounts and tools. The agents connect to your repositories, pipelines and chat workspaces, and the setup stays with your team after handover. That keeps source code and logs in systems you already secure and audit, rather than moving them somewhere new that your security team has never reviewed.
Choosing between Developer & DevOps products?
Tick Compare on up to four products to see scope, price and delivery side by side. If you would rather talk it through, an expert can help you pick the one that fits how you work.