
An agentic IDE that moves beyond AI coding, enabling spec-driven development from prototype to production.
Kiro is a next-generation agentic integrated development environment (IDE) designed to take engineering teams beyond conventional AI-assisted coding into the realm of agentic engineering. Built for macOS, Windows, and Linux, Kiro positions itself as the bridge between rapid prototyping and production-grade software delivery, powered by a specification-driven workflow that lets AI agents act on clear, structured requirements rather than piecemeal prompts.
At the core of Kiro is a full project context engine that enables deep understanding of your entire codebase. This allows the built-in agents to perform multi-file operations, refactor across modules, generate natural language code, and maintain coherence across large-scale changes. Kiro's conversational coding interface supports interactive, iterative development, while its spec-driven development methodology ensures that every agent action is aligned with an explicit specification. The platform also includes agent hooks for automation, making it possible to integrate intelligent workflows into existing development pipelines and CI/CD processes.
Kiro is engineered for developers and teams who need more than autocomplete. It is equally suited for solo practitioners moving from idea to MVP, as well as engineering organizations looking to standardize AI-assisted development around reproducible, spec-centric practices. With a tiered pricing model including a free plan and several Pro tiers, Kiro makes advanced agentic tooling accessible to both individual developers and enterprises. The IDE supports a wide range of models, from open-weight models to premium options like Claude Sonnet 4.5, giving users flexibility based on their performance and budget requirements.
By combining agent hooks, full-context reasoning, and a spec-first workflow, Kiro aims to reduce the friction between prototyping and shipping, ultimately helping teams accelerate development cycles without sacrificing code quality or maintainability.
Software developers seeking AI-native coding assistance, Engineering teams adopting agentic development workflows, Tech leads and architects managing large codebases, Startups and solo developers building MVPs rapidly, DevOps engineers automating code generation pipelines, Organizations requiring spec-driven development practices, AI researchers and enthusiasts exploring agentic tooling
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