In 2026, Cognition acquired Windsurf and merged it into Devin Desktop, marking a new era for autonomous AI engineering. Devin is no longer just a code completion tool — it's an AI agent that can independently plan, execute, and deploy complex engineering tasks. This guide dives deep into Devin Desktop's core capabilities, workflows, and best practices.

What Is Devin Desktop?
Devin Desktop is Cognition's autonomous AI software engineer platform. In early 2026, Cognition acquired Windsurf (formerly Codeium), merging its IDE capabilities with Devin's autonomous agent engine to create the all-new Devin Desktop.
**Core Positioning**: Unlike "interactive" AI coding assistants like Cursor or Claude Code, Devin Desktop is an "autonomous" AI engineer. You give it a high-level task description, and it independently handles:
1. **Codebase Analysis** — Understands project structure, dependencies, and architecture patterns
2. **Planning** — Breaks complex tasks into executable steps
3. **Code Writing** — Implements features in a sandboxed environment
4. **Test Execution** — Runs tests automatically and fixes failures
5. **PR Submission** — Generates clean diffs for human review
This "delegation-style" workflow shifts developers from "writing code" to "reviewing code," delivering 5-10x productivity gains.
Use our [JSON to YAML tool](/en/tools/json-to-yaml) to debug API responses.
Core Features Deep Dive
**1. Devin Review — Intelligent Code Review**
Devin Desktop introduces "Devin Review," which intelligently organizes code diffs to help teams efficiently review AI-generated code.
```typescript
// Devin Review configuration example
// .devin/review.config.ts
export default {
review: {
// Auto-classify changes
autoClassify: true,
categories: ['feature', 'bugfix', 'refactor', 'test', 'docs'],
// Security checks
security: {
scanSecrets: true,
checkDependencies: true,
validateTypes: true,
},
// Review rules
rules: [
{
pattern: '**/*.ts',
requireTests: true,
maxComplexity: 15,
},
{
pattern: '**/api/**',
requireValidation: true,
requireErrorHandling: true,
}
]
}
};
```
**2. Parallel Cloud Agents — Multi-Task Execution**
Devin Desktop supports running multiple cloud agents in parallel, each working in an isolated sandbox:
```yaml
# Parallel task configuration
# .devin/tasks.yml
tasks:
- name: "Migrate auth module to TypeScript"
priority: high
sandbox:
runtime: node-20
timeout: 30m
- name: "Fix flaky integration tests"
priority: medium
sandbox:
runtime: node-20
timeout: 15m
- name: "Update API documentation"
priority: low
sandbox:
runtime: node-20
timeout: 10m
# All tasks run in parallel without interference
```
**3. Visual QA — Full Browser and Desktop Testing**
Devin Desktop includes a complete browser and desktop environment for end-to-end visual testing.
Use our [Markdown to HTML tool](/en/tools/markdown-to-html) to format documentation.

Real Case: 8-Month Migration Done in 8 Days
A fintech company needed to migrate legacy Java 8 microservices to Java 21 + Spring Boot 3. Estimated manually: 8 months. With Devin Desktop: just 8 days.
**Devin's Workflow**:
```bash
# Step 1: Analyze codebase
$ devin analyze --repo ./legacy-services --depth full
Analyzing 47 microservices...
Found 2,341 Java files
Identified 892 deprecated API usages
Mapped 156 external dependencies
# Step 2: Generate migration plan
$ devin plan --task "Migrate to Java 21 + Spring Boot 3"
Migration Plan Generated:
├── Phase 1: Update build configs (47 services)
├── Phase 2: Replace deprecated APIs (892 instances)
├── Phase 3: Update dependency versions (156 deps)
├── Phase 4: Fix breaking changes (234 files)
└── Phase 5: Run tests and fix failures
# Step 3: Execute in parallel
$ devin execute --parallel 5 --plan migration-plan.yml
Executing 5 parallel agents...
Agent 1: Processing auth-service ✅
Agent 2: Processing payment-service ✅
Agent 3: Processing notification-service ✅
Agent 4: Processing user-service ✅
Agent 5: Processing order-service ✅
```
**Key Code Change Example**:
```java
// Before migration (Java 8 + Spring Boot 2.x)
@RestController
public class UserController {
@Autowired
private UserRepository userRepository;
@RequestMapping(value = "/users/{id}", method = RequestMethod.GET)
public ResponseEntity getUser(@PathVariable Long id) {
User user = userRepository.findOne(id);
if (user != null) {
return ResponseEntity.ok(user);
}
return ResponseEntity.notFound().build();
}
}
// After migration (Java 21 + Spring Boot 3.x)
@RestController
@RequiredArgsConstructor
public class UserController {
private final UserRepository userRepository;
@GetMapping("/users/{id}")
public ResponseEntity<UserDTO> getUser(@PathVariable Long id) {
return userRepository.findById(id)
.map(UserDTO::fromEntity)
.map(ResponseEntity::ok)
.orElse(ResponseEntity.notFound().build());
}
}
```
Use our [CSV to JSON tool](/en/tools/csv-to-json) to handle data migration.
Devin Desktop vs Cursor vs Claude Code
| Feature | Devin Desktop | Cursor | Claude Code |
|---------|--------------|--------|-------------|
| **Mode** | Autonomous | Interactive | Interactive |
| **Best For** | Large migrations/batch tasks | Daily development | Complex refactoring |
| **Code Review** | Devin Review (auto) | Manual | Manual |
| **Parallelism** | 5+ cloud agents | Single window | Single terminal |
| **Price** | $50-$200/mo | $20/mo | $20/mo |
| **Sandbox** | Full cloud sandbox | Local | Local |
**Selection Guide**:
- Need to batch process many tasks → Devin Desktop
- Daily fast development iteration → Cursor
- Deep code understanding and refactoring → Claude Code
- Best combo: Use all three together
Use our [Batch Image Format Converter](/en/tools/batch-image-format-converter) to handle project assets.

Quick Start Guide
```bash
# 1. Install Devin Desktop
$ npm install -g @cognition/devin-desktop
# 2. Initialize project configuration
$ devin init
# 3. Configure ACP protocol connection
$ devin connect --protocol acp
# 4. Start your first autonomous task
$ devin task "Add comprehensive error handling to all API endpoints"
# 5. Check task progress
$ devin status
# Devin Desktop is working...
# ✅ Analyzed 23 API endpoints
# ✅ Identified 8 endpoints missing error handling
# 🔄 Implementing error handling...
# ⏳ Running tests...
```
**ACP Protocol Integration**:
Devin Desktop supports the open ACP (Agent Communication Protocol) for collaborating with other AI agents:
```typescript
// Call Devin via ACP protocol
import { ACPClient } from '@acp/client';
const client = new ACPClient({
endpoint: 'http://localhost:3000',
agent: 'devin-desktop'
});
// Delegate a task to Devin
const result = await client.delegate({
task: 'Refactor database layer to use connection pooling',
context: {
repo: './my-project',
constraints: ['maintain backward compatibility', 'add tests']
}
});
console.log(result.status); // "completed"
console.log(result.pr_url); // "https://github.com/.../pull/42"
```
Use our [Regex Tester](/en/tools/regex-tester) to validate patterns.
Frequently Asked Questions
What is the relationship between Devin Desktop and Windsurf?
Cognition acquired Windsurf (formerly Codeium) in early 2026, integrating its IDE capabilities into the Devin platform to form Devin Desktop. The Windsurf brand has ceased independent operations.
How much does Devin Desktop cost?
Devin Desktop offers multiple plans: Team plan at $50/month (5 parallel agents), Business plan at $200/month (unlimited agents + priority support). Enterprise custom plans require contacting sales.
Is code generated by Devin safe?
Devin runs all code in sandboxed environments with built-in security scanning. All changes require human review before merging. Devin Review automatically flags potential security issues.
What programming languages does Devin support?
Devin supports all major programming languages including TypeScript/JavaScript, Python, Java, Go, Rust, C++, and more. Its TypeScript and Python support is the most mature.
How do I integrate Devin into my existing workflow?
Devin integrates with existing tools via the ACP protocol. It supports GitHub, GitLab, Jira, and other platforms. You can use it through CLI, API, or IDE plugins.
Conclusion
Devin Desktop represents a major leap from "assisting" to "autonomous" in AI coding tools. For teams that need to handle large volumes of repetitive engineering tasks, it's a powerful force multiplier. While pricier, the ROI is substantial for large-scale migrations, batch fixes, and automated testing scenarios. We recommend pairing it with Cursor (daily development) and Claude Code (deep refactoring) to build a complete AI engineering toolchain.