devlo

devlo's core move is turning an issue into a finished pull request. You assign it a ticket, and it comments with an implementation plan, writes the code, and opens a PR with tests included. The value here is the starting point: instead of staring at an empty editor, a developer reviews and adjusts real work. It fits small, well-scoped bugs far better than sprawling architectural changes. Keep the tickets tight. Big rewrites are still your job.

Every pull request gets an intelligent review pass, not just the ones someone remembers to look at. devlo reads the diff, flags problems, and leaves comments inline where the issue lives. It's built for AI code review, not a generic lint check. For teams where review is the bottleneck, this shortens the queue because routine problems are handled before a human opens the file. No waiting. That alone changes the pace of a release week.

You don't need a separate dashboard to assign work. Mention devlo in a GitHub issue or reply to a review comment, and it picks up the task inline. It reads like a normal conversation, which means the whole discussion stays in one thread your team can follow. Why does that matter? Because tools people have to leave their editor to use tend to get abandoned. This one shows up where the work already happens.

devlo plugs into the tools already in your stack: GitHub for code and issues, Jira for tickets, Slack for chat, plus a browser interface. The pitch is no context switching. A PM can hand off a task from Slack. An engineer can review the same work in GitHub. The work moves without anyone opening a new tab. Simple, and it works.

Beyond the default assistant, you can define custom agents for specific workflows. Set a trigger, like a new Jira ticket or a failing GitHub check, and define the outcome you want, then let the agent run. You're effectively building a tailored AI coding agent per workflow. This is real automation. devlo reacts to events rather than waiting for someone to type a prompt.

Most teams can't say how much of their output is AI-assisted. devlo tracks team velocity and separates out the portion driven by AI, giving managers a hard number to work with. Think of it as your AI developer assistant reporting back on its own contribution. Handy. It's the feature you'll want if leadership is asking whether the tool actually pays for itself.

devlo markets SOC-2 Type-2 compliance and zero data retention, meaning it claims not to keep your code after processing it. It also points to its SWE-Bench standing as evidence of capability. These matter if you're weighing a hosted AI tool against a self-hosted one. Confirm the details against your own policy before you connect a private repo. Don't skip that step.