
Introducing Runbooks - a multiplayer AI coding platform that enables collaborative spec-driven development. Some key features:
Runbooks is purpose-built for complex brownfield projects that involve understanding large codebases. Aviator agents internally run Claude code to analyze the code and prepare multistep plans (called Runbooks).

Invite engineers, PMs, and all stakeholders to share and collaborate on these Runbooks. Plan together, get feedback, and reuse existing templates.

Aviator manages ephemeral sandboxes that check out the repository and run Claude code in the background. These sandboxes can run custom environments and can scale to hundreds of agents instantaneously for parallel execution.

Agents manage all learnings into editable context files that are used for future execution. Using these auto-generated institutional knowledge graphs, the agents build up business context and get smarter over time.

The Runbooks can be published and reused. Write once, execute N times to standardize common operations or large replicable migrations. It also comes pre-built with a Runbook Library with tried and tested templates.

Interested? Join our beta.
FlexReview is out of Beta now, and can be directly accessed self-serve. Here’s what’s new:
Use aviator-config.yaml to define multi-level ownership definition in a YAML file. Distributed ownership simplifies updates and make it collaborative. Example:


A GitHub status check to ensure that appropriate approvals have been granted before a pull request is considered mergeable:
Extension that shows which team is the owner for specific files. Highlights the files that you are responsible to review based on your ownership.
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Set up OOO for team members who should be assigned for code reviews.
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Set up each team’s default Slack channels and customize notifications. Get notified for pending team reviews, subscribe to listen to changes in specific code paths.
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Reach out if you are interesting in trying it out or have any feedback!

Introducing Aviator Agents - an LLM-based agentic framework to perform large scale code migrations in your repositories.

These agents emulate human patterns to perform migrations by:
Aviator Agents plan out steps to perform a task and iterate to improve accuracy.
Unlike most LLM based frameworks, Aviator Agents is an end-to-end framework that connects directly with GitHub. This eliminates the need to set up a custom environment and build process.
It directly integrates with GitHub and supports Open-AI o1, Claude Sonnet 3.5, Deepseek R1, and Llama 3.1 models.
Aviator Agents is currently in private beta. If you are interested in trying it out please reply back or sign up on: aviator.co/agents