Queue vs Devin AI

Devin introduced the concept of an AI software engineer. Queue gives teams the infrastructure to build, deploy, and manage autonomous agents across their entire organization.

AI is moving beyond code completion and chat interfaces into a new category: autonomous software development.

One of the most visible products in this category is Devin AI, which demonstrated how AI systems can plan tasks, write code, run tests, and interact with developer tools with minimal supervision.

Queue shares a similar vision but approaches the problem from a different angle. Rather than creating a single AI engineer, Queue provides a platform for deploying specialized agents that can operate across engineering, operations, support, and product workflows.

A quick comparison

One AI engineer vs an entire agent platform

Devin popularized the idea of assigning software tasks directly to an AI system. Instead of asking for code suggestions, developers can provide a goal and allow the AI to work toward completion.

Queue embraces the same shift toward autonomy but expands the concept beyond a single agent.

Organizations rarely have one engineer responsible for everything. They have specialists: developers, reviewers, testers, infrastructure engineers, support teams, and operations teams. Queue is designed around the same philosophy.

Teams can deploy dedicated agents for code reviews, documentation, dependency management, testing, bug triage, infrastructure automation, and internal workflows—each configured with different tools, permissions, and objectives.

Built for organizations, not just tasks

Autonomous execution is only part of the challenge.

As organizations adopt AI agents, they need visibility, governance, security, permissions, observability, and collaboration. They need a way to manage dozens or hundreds of agents operating across multiple systems.

Queue was built with this reality in mind.

Every agent run is observable and auditable. Teams can track actions, inspect decisions, manage permissions, review outputs, and integrate agents into existing engineering workflows.

Rather than treating AI as a standalone product, Queue treats AI agents as infrastructure.

Beyond software engineering

While Devin focuses primarily on software development, Queue extends beyond engineering tasks.

Agents can interact with customer support platforms, internal tools, project management systems, APIs, cloud infrastructure, databases, and external services. This allows organizations to automate workflows across multiple departments rather than limiting automation to code-related tasks.

For many teams, the most valuable automation opportunities exist outside the editor.

Queue helps bring autonomous execution to the entire organization.

The future of AI work

The introduction of autonomous software engineers marked an important milestone for the industry. It showed that AI systems are capable of much more than generating snippets of code.

The next step is creating systems that organizations can reliably deploy at scale.

That requires infrastructure, observability, permissions, integrations, governance, and flexibility—not just intelligence.

That's the future Queue is building.

Both Queue and Devin represent a shift toward autonomous software development. The difference is scope. Devin focuses on creating an AI engineer. Queue focuses on creating the platform that allows organizations to deploy entire teams of AI agents.

If you're looking for an autonomous coding assistant, Devin is an impressive solution.

If you're looking to build, manage, and scale AI agents across your organization, Queue is built for that future.