Accelerating Software Development Velocity with Devin

The evolution of AI in software engineering

Cognition's platform introduces two distinct ways to accelerate development:

1. Windsurf: This product is an integrated development environment (IDE) layered with AI capabilities, built on the open-source version of Visual Studio Code. Windsurf, along with its collaborative agent, Cascade, is designed to accelerate individual engineers when they are hands-on with their code, assisting with tasks such as reading, understanding, debugging, and testing.
2. Devin: This product represents the next evolution of AI for software engineering. Devin is an autonomous AI agent meant to handle delegated tasks, providing a robust scaling factor and parallel capacity for the engineering organization.

If an organization finds that it has work stuck in the backlog for months or years, simply having individual engineers go 20% faster (Windsurf's primary function) won't solve that problem; delegating that work to autonomous agents (Devin's function) is necessary for scaling.

Devin is designed to act as a new type of colleague or co-worker. It exists in product surfaces like Slack and Jira, where you can assign tasks to it or ask it questions.

Analogy

Think of the relationship between Windsurf and Devin as akin to that of a seasoned chef (the human engineer) and their two assistants. Windsurf is the immediate line cook, helping the chef execute complex recipes more efficiently and troubleshoot ingredients on the fly. Devin, however, is the kitchen manager; you delegate to them all the repetitive prep work, inventory management, and cleaning (the "Devin's toil" and backlog work), freeing the master chef to focus on the highest-value, most creative dishes.

Understanding the autonomous agent

Devin operates like a colleague with their own "laptop". When assigned a task, it "turns on its machine" to utilize its own IDE, browser and shell environment, allowing it to run terminal commands, edit code and interact with web servers.

The foundation of Devin's intelligence and value falls under a few features:

• Deep Wiki: DeepWiki automatically generates system-wide documentation from a source code repository. It reverse-engineers and distills complex codebase information into a consumable, organized artifact, allowing the human developer and the AI agent to share an understanding of the system.
• Ask Devin: By generating an accurate DeepWiki, Devin demonstrates that it understands the codebase and is equipped to operate as an intelligent consultant that knows your code. For additional questions that users have about their code base, the natural progression is to go to Ask Devin. In Ask Devin, a developer can ask any question (such as whether the API design is scalable or has obvious antipatterns), and Devin will research the code base as context to provide a meaningful, grounded response.
• Devin Sessions: When you have identified a task and key elements as context to assign a scope of work to Devin, you create a Devin Session. Devin Sessions can optionally be created with context from an Ask Devin conversation. Crucially, when Devin does its assigned task in a Devin Session, the ultimate goal is to create a Pull Request with code changes to the source code repository.

Devin can open pull requests with meaningful comments, suggest a human review checklist, and respond to feedback/comments on those pull requests if the job was not completed. Devin is a Software Engineer, powered by AI.

Identifying ideal tasks for Devin

While Devin is a flexible platform, its primary value proposition as an autonomous software engineering agent is for tasks that are suitable for delegation. Here are a few sample criteria to ensure a task can be delegated successfully to Devin:

Specific high-value use cases

Organizations can derive immediate value by delegating the following tasks to Devin:

• Security Remediation: Fixing security vulnerabilities is an excellent use case, as the solution is often implied in the finding. Devin can run a security scan (such as Snyk), identify the issue (e.g., debug mode enabled), fix the local code, and then re-run the scan to validate the fix before initiating a pull request.
• Bug Fixes: Devin can triage reported bugs from systems like Jira. If given the log sources and the ability to reproduce the anomalous behavior on a local application variant, Devin can fix the bug and validate that the issue no longer occurs.
• Code Modernization and Refactoring: Devin can help with migrations (e.g., refactoring application code to be cloud-native or containerized). It is highly effective at rote, repetitive tasks, such as updating schema changes (like converting numeric identifiers to alpha-numeric formats across a large codebase).
• SQL Optimization: Devin can analyze a SQL query and experiment with rewriting it or changing indexes. It can validate the changes by running the query against a live database, ensuring the change not only reads better but runs more efficiently (less time/memory) while yielding the same data output.
• Code Reliability and Performance: Tasks related to optimizing performance, resolving memory leaks, or improving code reliability are suitable.
• Documentation and Test Coverage: Assigning Devin to embed docstrings across all code or to add test coverage are tasks where success is easily definable and repeatable.
• Accessibility Compliance: Devin can analyze an application or website against accessibility standards (such as WCAG), identify issues like missing alt text or insufficient color contrast, implement the required code changes, and then re-run accessibility scans to validate compliance before submitting a pull request.

Enterprise deployment and security

For highly regulated customers, such as those in the financial services industry, the controls and governance applied to Devin have met high security requirements. Key governance points include:

• Devin is designed for the enterprise target audience.
• Customers can bring their own VPC to run the Devin compute agent.
• Devin fits into existing processes. Release controls, approval requirements for merging pull requests, and security testing mechanisms all remain in place. If Devin introduces a bug, the existing security scanning and testing tools that prevent human-introduced bugs will function similarly for AI-introduced code.

Conclusion and next steps

Devin represents a new form of engineering capacity, an autonomous co-worker that reliably tackles delegated work, accelerates velocity and shortens the path to modernizing complex systems. By pairing human engineers with Devin, organizations can finally clear long-standing backlogs, improve code quality and focus their teams on the highest-value innovation.

To explore how WWT and Cognition (parent organization to Windsurf) can help your organization adopt this model, schedule a briefing.

Let's put Devin to work!