Recently, AI products from major manufacturers have been released like mushrooms after the rain, one after another showing off their strengths: should we not release now, are we really going to save it for the New Year?
, announced available for use on December 11th.
Just by mentioning @Devin, it can help you solve front-end bugs, create draft PRs for backlog tasks, complete code refactoring, and more.
🔥 Key highlights of Devin:
Seamlessly collaborate with your team, integrated directly into Slack, GitHub, or your IDE (beta).
Starting at $500/month, designed specifically for engineering teams.
Use Devin for everything from building new features (like the Devin API) to migrating from Clerk to Auth0. Even Devin's QA testing is done by Devin itself!
Already contributed to several popular open-source projects, such as fixing MCP issues for Anthropic and submitting merged PRs:
🔗 View Devin's workflow: https://app.devin.ai/sessions/266955553baf40cfa7fdd32d42ab219d
🔗 View the merged PR: https://github.com/modelcontextprotocol/inspector/pull/105
Organize and review the network evaluation of Devin with a $2 billion valuation.
Translate and organize the YouTube content of "Devin Review by Steve (Builder.io)."
https://www.youtube.com/watch?v=oU3H581uCsA
Core functions of Devin Devin is an AI programming agent designed for professional developers, featuring the following key characteristics:
Workflow based on Slack:
Devin's interaction is not through an IDE, but rather via Slack tags for operations such as requesting updates, fixes, or adding features. It supports remote server browsing, VS Code editing, planning functions, and more.
Task execution and feedback:
Devin records operational steps and stores key points in notes.txt for future reference. It also supports the creation of "knowledge entries," mimicking the "collective knowledge" shared within a team.
Real-world usage experience
The first task of the evaluator is to have Devin deploy a new image generation model. In the interaction with Devin, it successfully cloned the code repository and generated an image of a cat, and could generate more images subsequently. 
Devin also supports executing complex tasks, such as creating web interfaces and sending status updates during the process.
Strengths and Weaknesses
Strengths: Devin can generate plans, write code, find and fix errors, and even run its own end-to-end tests. It can iterate tasks based on user feedback, actively generate preview URLs, and help users intuitively check the results. Disadvantages: The workflow is mainly asynchronous, which is relatively slow, usually requiring about 15 minutes to generate a PR. There are issues with Devin's logical explanations, and sometimes the results do not meet expectations. The operation is relatively complex and not suitable for developers who wish to debug locally in real-time.
Comparison with Cursor
Devin： Its working method leans more towards automation, receiving instructions and providing feedback via Slack. However, this asynchronous approach may be inconvenient for highly efficient developers. (That said, I saw Mr. Yuan's shared comment from Mr. Yusen, who seemed to have a different view on async. Mr. Yusen felt that Devin was the first truly async product, which could be interrupted and adjusted at any time.) The pricing is relatively high, starting at $500 per month, which sets a high threshold. Cursor： It emphasizes real-time operations in the local environment, which aligns better with developers' habits. Cursor can quickly scan code repositories, find relevant files, and make direct modifications, providing instant feedback.
Summary: This guy prefers Cursor more.
The video creator's preference for Cursor may indeed be related to his role in working on the Builder.io product, and below is the workflow he recommends.
Check out the comment on X by Sharq Wy - e/acc @sharqwy.
https://x.com/sharqwy/status/1866871411551375815
Devin is not just an AI tool; it's more like an indefatigable, incredibly capable intern in the cloud.
After using Devin for an hour, my understanding was completely refreshed. Although it's expensive ($500/month), it's definitely not your average AI assistant. It's not the kind of tool that requires constant supervision (like @cursor_ai Composer or @windsurf_ai Cascade). Devin can work independently—you assign a task, then leave, and when you come back, there’s already significant progress, much like a fully self-sufficient junior developer.
Copy an example website and upgrade a static blog to a dynamic version with backend management capabilities.
Devin's workflow was almost like that of a human developer taking over and completing the task:
: Immediately choose FastAPI and PostgreSQL, design the data structure for the blog, and build the API. : Write API implementation code, test cases, and verify using curl POST. : Build the UI and integrate the logic. ：Log in to Shadow Browser, populate backend data, test the UI, and switch between frontend and backend to ensure everything runs smoothly.
：Devin actually tests and verifies its own work as if it really cares about the outcome. This kind of self-verification for work results gives a sense of "this is the future."
If Windsurf feels like an outsourcing team, Devin is more like a trustworthy intern who can independently handle real tasks. Although it isn't a CTO yet and still requires clear guidance, its execution ability has reached new heights.
One sentence summary:
Copilot and Cursor feel like AI simply overlaid on an IDE, whereas Devin feels like the AI itself has possession of the IDE, using it as a tool to accomplish tasks.