Replicas lets engineering teams delegate coding tasks to AI agents that run in isolated cloud VMs. Each agent gets a full dev environment with dependencies, databases, and your actual codebase. Trigger tasks from Slack, GitHub, Linear, or the API, and come back to a pull request ready for review. Built-in feedback loops automatically handle CI failures, code reviews, and merge conflicts. Backed by Y Combinator and used by teams like Mintlify, Composio, and Knowunity.

• Isolated Cloud VMs: Each agent runs in its own sandboxed virtual machine with a full dev environment, including installed dependencies, databases, and your actual codebase running locally inside the sandbox.
• Multi-Agent Support: Works with Claude Code, Codex, OpenCode, and more. Bring your own API keys or subscriptions so you only pay for infrastructure.
• Workflow Integrations: Trigger agents from GitHub (mention @tryreplicas in PR comments), Slack (ping @Replicas in any channel), Linear (assign issues directly), or the web dashboard.
• Automated Feedback Loops: Agents automatically react to CI failures, code reviews, and merge conflicts, iterating until the PR is clean and ready to merge.
• Environments: Configure agents to run your entire codebase locally, verify their own work, and provide preview URLs for review.
• REST API: Programmatic access via a REST API to integrate Replicas into any custom workflow or CI/CD pipeline.
• Parallel Task Execution: Run multiple agents simultaneously on different tasks, allowing teams to burn through tickets and develop features in parallel.

• Works Where You Already Do: Trigger tasks directly from Slack, GitHub PRs, or Linear issues without switching tools or opening a separate dashboard.
• True Environment Isolation: Each agent gets its own VM with a real dev environment, eliminating state bleed between runs and making failures clean to recover from.
• Automatic Iteration on Failures: The built-in feedback loop handles CI failures and merge conflicts automatically, reducing the back-and-forth that slows down traditional agent workflows.
• Free Tier Available: The Hobby plan offers 1,200 minutes of usage at no cost, letting you test the platform before committing to a paid plan.
• Strong Dogfooding Track Record: The Replicas team ships 95% of their own PRs through the platform, demonstrating real confidence in the product.

• Review Bottleneck at Scale: Multiple parallel agents can produce PRs faster than your team can review them. Ten agents means ten PRs a human still has to read and trust.
• Usage Costs Scale with Workload: BYOK model means token usage is separate from subscription fees
• Complex Tasks Still Need Human Judgment: Like all AI coding agents, Replicas works best on well-defined tasks. Open-ended feature work or nuanced architectural decisions still require human oversight.
• Paid Plans Are Pricey: At $120-$300 per seat per month (before API costs), the platform represents a significant investment, especially for smaller teams.

• Parallel Feature Development: Assign multiple coding tasks to separate agents at the same time. Each agent works in isolation, letting your team develop several features in parallel without merge conflicts until PRs are ready.
• Automated PR Fixes from Code Review: Mention @tryreplicas in a GitHub PR comment describing what needs to change. An agent spins up, makes the fix, and pushes an updated commit without a developer context-switching away from their current work.
• CI/CD Failure Resolution: When a build breaks, Replicas agents can automatically pick up the failure, diagnose the issue in an isolated environment, and submit a fix. Teams use this for around-the-clock on-call support.
• Issue Triage from Linear or Slack: Product and engineering teams assign Linear issues or Slack messages directly to Replicas. The agent picks up the task, works through it in a sandbox, and delivers a PR for the team to review.
• Multiplayer Handoff Workflows: Product managers and engineers hand off agent sessions back and forth as development progresses, using Replicas as a shared workspace where context is preserved between handoffs.