AWS Kiro Crew Transforms AI Coding Agents Into Autonomous Engineering Teams Running 24/7

AWS's Kiro Crew aims to turn AI coding agents into autonomous engineering teams

The open-source orchestration offering could help enterprises automate long-running software engineering workflows, although governance and interoperability challenges remain, analysts say. AWS on Tuesday released Kiro Crew, an open-source orchestration platform designed to help enterprises move beyond interactive AI coding assistants toward long-running, autonomous engineering workflows that span repositories, developer tools, and multiple work sessions. Rather than simply generating code, Kiro Crew coordinates multiple AI agents, schedules recurring work, preserves project context across sessions, and integrates with developer tools to investigate incidents, monitor pull requests (PRs), triage tickets, and automate software engineering tasks while developers are away from their keyboards, according to the hyperscaler. "Kiro Crew is a persistent, open-source development workspace for work that is bigger than a single task in a single session," Darko Mesaros, distinguished developer advocate at AWS, told InfoWorld. "Think of it as an application layer that turns AI coding agents into always-working, self-learning, autonomous teammates."

AWS launches Kiro Crew, an autonomous agentic orchestrator for 24/7 code development

Amazon Web Services Inc. today launched Kiro Crew, an autonomous workspace that keeps artificial intelligence coding agents running all day and all night. The company said it developed Crew to allow developers to start a task, walk away and come back when something is worth administering. It tasks multiple agents and their sub-agents on a multi-step task so developers can let them run unattended. It can also manage recurring jobs that run on a schedule, and a heartbeat monitors the system until something needs to be reviewed. The software also provides Apps, an interface that allows developers to bring their own tooling, giving individual processes their own purpose-built UI and structure. An App can combine a custom user interface with agents, skills, schedules and backend services. The new solution is built on Kiro, expanding on the same agent infrastructure of the software's autonomous mode. Kiro is AWS's development environment that integrates agentic AI for software engineers, which allows them to rapidly turn ideas into production-ready code. The difference between Kiro Crew and Kiro's "autonomous mode" is one of scope: autonomous mode handles individual tasks within a single session; Crew continues working whether a developer is online or off, maintains memory across sessions, runs scheduled work and orchestrates multiple specialist agents. As this entire system is built on Kiro, it can read .kiro configuration out of the box, built off steering files, skills and custom agents the user has already built as part of their coding environment. One thing that Amazon touted about Crew is that it is designed to be "self-learning and self-evolving." By providing persistent memory of preferences, active-project context, and relevant history into new sessions, it can bring corrections along with every run. This includes lessons that change later behavior involving workspace-scoped or project-specific guidance. For example, if a user repeatedly asked an agent to code in a particular way, such as a preferential use of a certain function over another, the agent would ingrain that guidance. Also, if a specific tool, for example an MCP server that provides Python best practices, constantly fails on certain requests that need to be reformatted to get it to work properly, the agents can pass on this information between sessions. Amazon stressed that agentic memory remains visible, allowing developers to decide what Crew carries forward. Interacting with and expanding Crew Crew runs locally or remotely on developer hardware, providing the ability to view, audit and control. The app and web dashboard provide a place to work directly with Crew across conversations, files, approvals, memory, schedules and Apps. Developers can also talk to Crew via their usual chat interfaces. This means reaching out to the agents via Slack, Telegram and Discord, allowing them to continue the same work without needing to stay in the same place. This means that a developer could start their tasks in the Crew dashboard, then walk away. If they're off doing something else and realize they need to add a task or adjust something, they can contact Crew via Discord, or have an agent check in when something needs review. The core of Crew is also extensible, allowing the community to build an ecosystem of Apps and integrations that expand what it can do. The company said this community-driven capability became the core of Crew when it first emerged among Amazon's own developers and going forward this will be preserved. For developers that work with other harnesses and agentic orchestrators such as OpenClaw, Hermes and other open-standards-based platforms, Crew can incorporate their skills and configurations as well. This means that developers can easily move their lived-in experience from these harnesses and use Crew alongside their agentic resources, allowing it to slot in as an addition to the developer toolset, instead of an outright replacement that needs to be trained up to work. The Kiro Crew app for macOS is available for direct download or installation from the GitHub Repository. The repository additionally includes setup instructions for Linux and Windows, alongside guides for connecting chat interfaces such as Slack, Telegram and WeCom.