Aviator Runbooks | Collaborative Spec-driven AI Development

3 min read Original article ↗

REMOTE AGENTIC  ENVIROMENT

Multiplayer spec-driven development. Plan, share, and execute reusable Runbooks across teams.

From startups to Fortune 500s, the world's most effective engineering teams supercharge their developers with Aviator.

Assign coding tasks from Slack

Convert Slack messages into executable coding tasks with background agents that research, plan, and deliver production-ready code.

Spec-driven execution: Every task generates a detailed Runbook spec

One-click PRs: Go from a single Slack message to a reviewable PR

Auto-scale infra: Ephemeral agent instances spin up on-demand

Real-time visibility: Track progress, review decisions, and reasoning

aviator-runbooks-assign-coding-tasks-slack-screenshot

aviator-runbooks-assign-coding-tasks-handle-review-comments

Handle review comments

Assign review feedback directly to Runbook agents to analyze comments, update pull request, and accelerate your review cycle.

Automate review cycle: Close review loops 3x faster using Runbook agents

Context-aware: Learns from mistakes, maintains centralized context

Intelligent updates: Targeted fixes while preserving code quality

CI failures

Auto-detect, analyze, and resolve CI failures across your pull requests with agents that understand your test suite and infrastructure.

Root cause analysis: Agents automatically parse build logs and test output

Intelligent fixes: Targeted fixes for flaky tests, dependency conflicts, and infrastructure errors

Learn from patterns: Agents captures recurring failure in reusable context

Push fixes directly: Pull request updated with clear explanations of what was fixed

aviator-runbooks-root-cause-analysis-ci-failures

aviator-runbooks-triage-issues-automatically-draft-prs

Triage issues automatically

Streamline issue management with agents that assess, and ask clarifying questions. Assign issues to background agents to plan and execute.

Smart triage workflow: Categorize issues by type, severity, and affected components

Clarification loops: Agents ask reporters targeted clarifying questions

Automated task breakdown: Convert complex issues into executable Runbook specs

Background execution: Agents investigate, propose solutions, and create draft PRs automatically

Use Cases

For engineering teams working on shared, evolving codebases, Aviator’s context-aware Runbooks help standardize AI-development without compromising on the quality.

Ready to scale your AI coding adoption?

Transform scattered processes into reliable, collaborative Runbooks.

How it works

Collaborative reusable Runbooks for planning. Remote sandbox environments for execution.

Plan

plan

Install

Self-host Aviator Runbooks in your private network or use the Cloud setup.

define

Define

Pick a Runbook from the Library or create your own with a simple chat.

provision

Provision

Aviator sets up a sandbox to analyze code, ask questions, and build a Runbook.

run

Run

A Runbook has self-contained steps that agents can execute one by one.

Execute

review

Review

Each step generates stacked PRs. Provide feedback in GitHub for rewrites.

merge

Merge

Once approved, PRs can be merged manually or using the MergeQueue.

share

Share

Collaborate

Invite your team to Runbooks for reviewing and executing the steps.

fork

Fork

Publish Runbooks to the Library for others to reuse or customize.

evolve

Evolve

Agents automatically capture review feedback to update the context files.

Find Out More

Explore the concepts behind Runbooks: remote agentic environments, spec-driven development, and more.

The Rise of Remote Agentic Environments

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The Future of Agentic Coding is Multiplayer

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Spec Driven Development: Key to Scalable AI Agents

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Why AI Coding Still Fails in Enterprise Teams

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