Kiro is an agentic Integrated Development Environment (IDE) developed by Amazon Web Services (AWS), designed to streamline software development by emphasizing structured specifications over conversational prompts. ^{[1] [2]}

Launched on July 14, 2025, Kiro aims to provide a more guided and consistent approach to building applications, particularly for enterprise environments, by integrating artificial intelligence directly into the developer workflow ^[1].

Overview

Kiro represents AWS's strategic entry into the rapidly evolving field of AI-powered developer tools, positioning itself as a direct competitor to existing agentic IDEs such as Cursor and Windsurf.

A foundational aspect of Kiro's design is its reliance on the open-source Visual Studio Code (VS Code) project. This choice is significant as it allows developers to seamlessly integrate their existing VS Code settings, configurations, and a wide array of plugins, minimizing the learning curve and ensuring a familiar and extensible environment for users transitioning to Kiro. The ability to retain personalized setups and toolchains is a key advantage, fostering developer adoption and productivity ^[1].

Beyond its VS Code base, Kiro incorporates robust support for the Model Context Protocol (MCP). This protocol is crucial for facilitating the connection and interoperability of various development tools and services within the IDE, enabling a more cohesive and integrated development experience. For its underlying artificial intelligence capabilities, Kiro leverages Anthropic's Claude Sonnet 4 as the default large language model (LLM), with Claude Sonnet 3.7 available as an alternative option. AWS has also indicated clear plans to expand support for additional LLMs in the future, offering greater flexibility and choice to developers as the AI landscape evolves ^[1].

Kiro is designed for broad accessibility and cross-platform compatibility, with native applications available for Linux, macOS, and Windows operating systems. This ensures that developers across different environments can utilize the tool effectively. Furthermore, it supports a comprehensive range of popular programming languages, making it a versatile solution for diverse development projects, from web applications to backend services. During its initial preview phase, Kiro is offered free of charge, allowing developers to explore its capabilities without immediate financial commitment.

Following the preview period, AWS plans to introduce tiered professional plans to cater to different levels of usage and team sizes. These plans will include a standard professional tier at $19 per month for up to 1,000 agent interactions and a Pro+ plan at $39 per month for up to 3,000 interactions, providing scalable options for individual developers and larger teams ^{[2] [3]}.

Technology & Features

Kiro distinguishes itself from other AI coding assistants by introducing unique features centered around structured specifications and automated workflows, moving beyond simple prompt-based interactions ^[1].

These core innovations, "Kiro Specs" and "Kiro Hooks," aim to integrate AI more deeply into the development lifecycle, particularly for generating and refining production-ready code. This approach addresses the common challenge where initial AI-generated code, often referred to as "vibe coding," requires significant manual effort to meet enterprise-grade quality, security, and maintainability standards ^[4].

Kiro Specs

Kiro Specs provide a powerful mechanism for developers to define the requirements and design of their projects in a structured, declarative manner. This method represents a significant departure from traditional prompt engineering, where developers might rely solely on natural language descriptions to convey desired outcomes to an AI.

While some existing tools, such as Anthropic's Claude Code, utilize similar concepts like a Claude.md file for project guidance, AWS has integrated specs as a fundamental and central component of the entire Kiro development experience.

This deep integration is particularly beneficial for enterprise environments, where formal documentation, clear requirements, and adherence to architectural patterns are paramount for successful project delivery and long-term maintainability ^[2].

The workflow for Kiro Specs is designed to automate and guide the development process through several intelligent steps:

• Automated User Story Generation: Upon initiating a new project, Kiro automatically generates user stories based on initial high-level inputs. These stories are structured according to the Easy Approach to Requirements Syntax (EARS), a widely recognized format that ensures clarity, conciseness, and testability of requirements. EARS-structured user stories typically follow patterns like "When [trigger], the system shall [response]," making them unambiguous. Developers retain the crucial ability to review, modify, and refine these generated stories to precisely align with specific project needs and business logic, ensuring the AI's output matches human intent ^[1].
• Comprehensive Design Document Creation: Following the user story phase, Kiro proceeds to build a comprehensive design document. This process involves a deep analysis of either an existing codebase provided by the developer or the newly generated and refined spec requirements. The AI leverages this analysis to create critical architectural elements, including detailed data flow diagrams that illustrate how information moves through the system, precise TypeScript interfaces for defining data structures and API contracts, robust database schemas for data persistence, and well-defined API endpoints for inter-service communication. This automated generation of design artifacts lays out a clear and actionable blueprint for the application's construction, significantly reducing the manual effort typically involved in architectural planning ^[1].
• Granular Task and Subtask Generation: Subsequent to the design phase, Kiro generates a detailed, step-by-step list of tasks and subtasks required to implement the application. This granular breakdown guides the development process, incorporating essential considerations such as comprehensive testing procedures (e.g., unit tests, integration tests) and adherence to accessibility requirements. Developers maintain control over the execution, as they can selectively trigger each task and observe Kiro's progress and output in real-time. This allows for iterative development and validation at each stage ^[1].

Kiro Hooks

Kiro Hooks function as event-driven automation triggers that enable AI agents to execute specific tasks in the background. These hooks can be activated automatically in response to various file system events, such as when a file is saved, created, or deleted, or they can be triggered manually by the developer. This capability allows for continuous integration of automated processes directly within the development workflow, providing a layer of proactive assistance ^[1].

The primary purpose of Kiro Hooks is to automate repetitive or critical tasks, thereby enhancing development efficiency, maintaining code quality, and enforcing best practices. For instance, a hook could be configured to automatically update a project's Readme file whenever an API endpoint is modified, ensuring that documentation remains current and accurate without manual intervention.

Another practical application could involve running a scan for leaked credentials or sensitive information before code is committed to a version control repository, significantly bolstering security measures early in the development cycle.

According to Nikhil Swaminathan and Deepak Singh, Amazon's VP of developer agents and experiences;

"Kiro hooks act like an experienced developer catching things you miss or completing boilerplate tasks in the background as you work."

They further elaborate on the broader organizational benefits, stating that

"Hooks enforce consistency across your entire team. Everyone benefits from the same quality checks, code standards, and security validation fixes,"

highlighting their role in standardizing development practices, improving team collaboration, and ensuring a consistent level of quality across all projects^{[5] [6]}.