The outcome
Learn the interaction loop using a small task with a clear outcome.
Devin is a autonomous AI software engineering agent. Investigating codebases, implementing scoped engineering tasks, producing pull requests, and standardizing repeatable work with Knowledge and Playbooks. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.
Before you begin
Set the boundary before the tool starts.
Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.
AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.
Step by step
A workflow you can repeat.
- 01
Index an authorized repository and confirm its default branch, instructions, integrations, and checks.
- 02
Begin in Ask mode with a small task, clear acceptance criteria, and the relevant repository context.
- 03
Review the proposed plan before starting an Agent session and state forbidden or approval-gated actions.
- 04
Inspect activity, final diff, test results, and Session Insights before merging anything.
Working standard
What good use looks like.
- State the outcome before the background.
- Provide the real source material.
- Review the result before expanding the task.
Devin can use shells, browsers, secrets, integrations, and Git. Apply least privilege, scope sessions tightly, keep production actions human-approved, and review every code and dependency change.
Official references
Check the current product documentation.
Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.