What problem does Kiro solve for developers?
Kiro moves beyond basic AI coding to provide agentic engineering, helping developers turn prompts into structured requirements and ship maintainable code. It addresses the gap where unit tests pass but code doesn't match intent by using property-based tests and automated reasoning to catch bugs missed by traditional testing.
Who is the target audience for Kiro?
Kiro is built for developers and teams, including enterprise users. It helps them do their best work by providing tools for spec-driven development and parallel agents, and it is operated by AWS with enterprise-grade security, reliability, and administration controls.
What features and capabilities does Kiro offer?
Kiro offers spec-driven development, parallel AI agents, property-based tests, and integration with tools like Figma and Terraform. It includes a CLI that works with many shells and CLIs, an IDE supporting Open VSX extensions, and compatibility with the Agent Client Protocol (ACP), AGENTS.md, Skills.md, and MCP.
How is Kiro priced or packaged?
Kiro uses a credit-based pricing model with no daily or weekly rate limits and pre-paid overages. This allows users to code without unexpected interruptions, and it is offered as an enterprise-grade product with predictable costs.
Which AI models does Kiro support?
Kiro is powered by models including Anthropic Claude and open-weight models. It also offers an 'Auto' mode that selects the best model for a task based on complexity, model quality, latency, and cost.
What is Kiro used for, and in what situations?
Kiro is used for spec-driven development, implementing features with parallel AI agents, and catching edge-case bugs with property-based tests. It is suitable for building software across large codebases, planning from spec to pull request, and running headless code reviews in CI/CD pipelines.