Product & Features

Introducing Codegen 3.0: The Operating System for Code Agents

September 17, 2025

Software development is undergoing its biggest transformation since the compiler. Code generation has unlocked fundamentally new types of software we can build. But deploying AI agents in real engineering teams requires more than just powerful models – it requires infrastructure.

What Does It Mean to Be an OS for Code Agents?

Think about what an operating system does: it manages resources, provides isolation between processes, handles I/O, and gives applications a consistent interface to hardware. Codegen does the same for AI agents.

When you run code agents at scale, you need:

  1. Process isolation: Sandboxes where agents can safely execute code without affecting production
  2. Resource management: Orchestration that routes requests and manages concurrent agents
  3. I/O handling: Deep integrations with your existing tools (Slack, GitHub, Linear, etc.)
  4. Monitoring: Telemetry and analytics to understand what agents are doing
  5. Access control: Permissions and rules to keep agents within boundaries

Codegen provides all of this as a unified platform. Your agents run on our infrastructure, but with your rules, your integrations, and complete transparency.

What’s New in Codegen 3.0

Claude Code Integration

CLI agents are the building blocks of modern AI development and Claude Code is no exception.

We’ve built tight integrations with Claude Code that bring enterprise-grade infrastructure to your terminal:

  1. Cloud telemetry for every local session: Every Claude Code interaction is logged to the cloud, creating searchable history and audit trails
  2. Background agents on command: Start long-running tasks without blocking your terminal
  3. Full MCP access out of the box: All your Codegen integrations (Slack, Linear, databases) are automatically available through MCP

This means you can run Claude locally while getting the benefits of cloud infrastructure – monitoring, analytics, and team visibility.

State-of-the-Art AI Code Reviews

Code review has become more of a bottleneck than code production. That’s why we’re launching AI code reviews as a first-class citizen.

Our review agents:

  1. Provide line-by-line analysis with actionable suggestions
  2. Catch security vulnerabilities and unsafe patterns
  3. Suggest architectural improvements
  4. Maintain consistent code quality across human and AI contributions

Configure review rules at the organization level, then customize per repository. It’s built on the same infrastructure that powers our code generation agents, ensuring reliability and scale.

Enterprise-Grade Sandboxes

Real development means running tests, installing dependencies, and keeping massive codebases in sync.

Our sandbox infrastructure has been rebuilt from the ground up to handle this reality:

  1. Instant boots: Pre-warmed environments ready in seconds
  2. Persistent state: Maintain installed dependencies across agent runs
  3. Production parity: Configure environments that match your stack exactly
  4. Full transparency: See exactly what agents are doing in real-time

These aren’t toy environments – they’re built for codebases like Notion, ClickUp, and Linear.

Comprehensive Analytics

Any successful deployment of code agents requires measurement.

Codegen Analytics provides granular insights into:

  1. Cost breakdowns: Track spending by model, agent, and team
  2. Impact metrics: PRs merged, lines changed, velocity improvements
  3. Adoption patterns: See who’s using what, where, and how often
  4. ROI analysis: Understand the real value agents deliver to your organization

Live dashboards update in real-time, giving you the data needed to optimize your AI investment.

The Platform in Action

Here’s how it all comes together: A developer triggers an agent from Slack to implement a new feature. The agent spins up in a sandbox, pulls the latest code, implements the feature with full access to your tool stack via MCP, runs tests, and creates a PR.

When CI fails, the Check Suite Auto-fixer automatically analyzes logs and pushes fixes. The PR Review agent provides intelligent feedback. Throughout this process, everything is logged, measured, and visible in your analytics dashboard.

This is what we mean by an operating system for code agents – complete infrastructure that makes AI development work in production.

Built on Real Experience

These aren’t theoretical features. They’re built from years of experience with thousands of engineering teams shipping production code with AI. We’ve learned what breaks, what scales, and what actually matters when you’re trying to ship software, not demos.

The gap between vibe coding and professional software development is real. Codegen 3.0 bridges that gap with infrastructure built for the messy reality of software engineering.

Get Started

Codegen 3.0 is available today. Start with our GitHub integration, connect your tools, and see what it means to have real AI infrastructure. Explore all of Codegen’s capabilities in our docs.

The future of software development is here. And it’s running on Codegen.