This post introduces Devin AI, an autonomous software engineering agent, and walks you through getting started with it on your own repository.

Introduction

Devin is an autonomous AI software engineering agent built by Cognition Labs. Instead of suggesting the next few lines of code, Devin takes a task described in plain English, plans how to solve it, and then executes that plan end to end.

To do this, Devin works inside a sandboxed development environment with the same tools a human engineer uses:

  • A shell: to install dependencies, run build commands, and start servers.
  • A code editor: to read a codebase and write or refactor files.
  • A browser: to read documentation, look up errors, and test the running application.

With that environment, Devin can handle a full slice of everyday engineering work: writing new features, debugging failures, running the test suite and iterating until it passes, opening a pull request, and even deploying the result.

How is this different from a code-completion assistant?

A code-completion assistant lives inside your editor and reacts to what you are typing right now. You stay in the loop for every keystroke, and you still own the plan, the terminal, and the tests.

Devin is agentic. You hand over a goal (“fix this failing integration test”, “migrate this service to the new API”) rather than a cursor position. Devin then decides the steps, runs commands, reads the output, corrects itself when something breaks, and reports back with a reviewable change. You move from writing every line to reviewing the work — which is why treating Devin’s output like a pull request from a teammate is the right mental model.

Quick Start

1. Sign Up and Access Devin

Head to app.devin.ai and create an account. Once you are in, you get a session workspace: a chat panel on one side and Devin’s live shell, editor, browser, and planner on the other. Watching that panel is the easiest way to build intuition for how the agent thinks.

2. Connect a Repository

Connect your source control provider (GitHub, GitLab, or Bitbucket) from the settings page and grant access to the repositories you want Devin to work on. Devin clones the repo into its own machine, so nothing runs on your laptop.

It is worth spending a few minutes on the repository setup step here — telling Devin how to install dependencies, run the app, and run the tests. For a Jekyll blog like this one, that is as simple as:

bundle install
bundle exec jekyll serve

Devin snapshots that environment and reuses it for every future session on the repo.

3. Give Devin a Task Prompt

Start a session and describe the outcome you want, not the keystrokes. Good prompts name the files or areas involved and state how you will judge success:

In the pbrajesh/blog repo, add a new post under _posts/ introducing
Devin AI. Follow the front matter and formatting conventions used by
_posts/2026-04-26-Ollama-VS-Code-Continue-Integration.md, and don't
modify any other files.

The build is failing on main with a Liquid syntax error in about.md.
Reproduce it locally with `bundle exec jekyll build`, fix the root
cause, and confirm the build passes before opening a PR.

Vague prompts (“improve the blog”) produce vague results. Constraints, acceptance criteria, and pointers to existing examples are what turn a prompt into a good task.

4. Review the Plan

Before touching code, Devin produces a plan: the steps it intends to take and the files it expects to change. Read it. If a step is wrong or a constraint is missing, reply in the chat and Devin will re-plan.

This is the cheapest place to correct course — a thirty-second comment here saves you reviewing a diff that went in the wrong direction.

5. Review and Merge the Output

When Devin finishes, it pushes a branch and opens a pull request with a summary of what changed and why. Review it exactly as you would a colleague’s PR: read the diff, check the tests, pull the branch locally if you want to run it yourself.

If something is off, comment on the PR or reply in the session — Devin picks up the feedback, pushes a follow-up commit, and keeps CI green. Once you are happy, merge.

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