Kiro

Kiro is an agentic AI engineering system for shipping quality software, available through an IDE, a CLI, a web interface, a mobile app, and Kiro Crew. The homepage frames Kiro as a set of building blocks for turning the software lifecycle into a loop the developer directs as autonomously as they are comfortable with: persistent agents pick up signals and tasks, build and verify in sandboxes, flag what needs review, and learn from each session. Crew is the persistent layer. Kiro Crew agents pick up work and keep going while you are away, while workflows split long tasks into checked steps so agents cannot skip a test that failed, a design the homepage describes as quality enforced at every step. In the FAQ, Kiro says its agents turn prompts into executable specs, validate code correctness to find bugs that unit tests miss, and build across large codebases with parallel agents that learn from every session, helping with everything from quick fixes to complex tasks in the cloud when the developer steps away. Its own summary describes Kiro agents as planning, building, reviewing, and verifying real engineering work on your machine or in the cloud. Model and language coverage are spelled out on the homepage. Kiro works with frontier models including Claude and GPT and open-weight models like DeepSeek and Qwen, or its Auto option can route each task to the right model. The FAQ lists supported languages including Python, Java, JavaScript, TypeScript, C#, Go, Rust, PHP, Ruby, Kotlin, C, C++, shell scripting, SQL, Scala, JSON, YAML, and HCL. Homepage testimonials add reported team experience, including a wealth engineering leader reporting a productivity uplift and roadmap acceleration, users describing spec-driven work that turns rough ideas into production-ready specifications, and hooks that automatically run follow-up tasks such as tests and documentation in the background. Kiro suits developers and engineering teams who want spec-driven, checked agent work with persistent follow-through, rather than one-off code generation, and who want to choose how much autonomy each task gets.