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Kiro

Kiro: The AI IDE for prototype to production. Streamline AI coding with spec-driven development and autonomous agents.

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Introduction

Overview

Kiro is an advanced AI Integrated Development Environment (IDE) designed to revolutionize the way developers approach AI coding, bridging the gap from initial prototype to production-ready software. It emphasizes spec-driven development, bringing structure and mature engineering practices to the often unstructured world of AI-assisted coding.

What is Kiro?

Kiro acts as an intelligent coding partner, transforming natural language prompts into clear requirements, system designs, and actionable tasks. It facilitates collaboration between the developer and AI agents, which then implement the defined specifications. This structured approach ensures that AI-generated code is not only functional but also maintainable and well-documented.

Key Benefits

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Structure to AI Coding: Moves beyond "vibe coding" by enforcing spec-driven development for clearer requirements and designs.

Automation: Automates repetitive tasks like documentation generation and unit test creation through agent hooks triggered by events like file saves.

Enhanced Context: Utilizes specs, steering, and smart context management to understand intent better, enabling complex feature implementation in larger codebases with fewer iterations.

Tool Integration: Seamlessly connects to external tools, databases, APIs, and documentation via MCP integration, bringing your development environment to your world.

Familiar Environment: Built on Code OSS, Kiro supports VS Code plugins, themes, and settings, offering a comfortable transition for existing VS Code users.

Main Features

Kiro offers a suite of features designed for efficient AI development:

Spec-Driven Development: Define requirements, design, and tasks before coding begins, with Kiro agents implementing the spec.
Agent Hooks: Automate background tasks such as generating documentation or unit tests upon specific triggers (e.g., file save).
Multimodal Chat: Interact with Kiro using text or by providing images of UI designs or architecture diagrams to guide implementation.
Steering Files: Configure agent behavior, coding standards, and preferred workflows on a per-project basis.
Model Flexibility: Choose between Claude Sonnet 4 for reliable performance or "Auto" for a balanced mix of models optimizing for quality, latency, and cost.
Code Diffs & Previews: Visualize code changes as they happen and approve, edit, or step through modifications easily.

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Information

Websitekiro.dev
Published date2025/11/04

Frequently Asked Questions

Freemium

+1

Product Information

Pricing Model

💎 Freemium

Supported Platforms

Web

Windows

Mac

Linux

Supported Languages

English

Key Features

📝

Spec-Driven Development

Transform prompts into clear requirements, system designs, and discrete tasks, with AI agents implementing the spec while you maintain control.

⚙️

Automate Tasks with Agent Hooks

Delegate tasks to AI agents that trigger on events like 'file save' to autonomously generate documentation, unit tests, or optimize code.

🔗

Integrate Tools and Data (MCP)

Integrate with docs, databases, and APIs using native MCP integration, bringing your external resources directly into your development workflow.

🖼️

Multimodal Chat & Input

Interact with Kiro using multimodal inputs, including images of UI designs or architecture diagrams, to guide code implementation.

🔧

Project-Specific Steering

Configure agent behavior, coding standards, and preferred workflows per project using simple steering files.

🧠

Flexible AI Models

Choose between Claude Sonnet 4 for advanced reasoning or 'Auto' mode for a cost-effective blend of frontier models.

Pros & Cons

Pros

Provides structure to AI coding through spec-driven development.
Automates repetitive tasks like documentation and testing with agent hooks.
Supports integration with various tools and data sources via MCP.
Offers a familiar development environment with VS Code compatibility.
Enables multimodal interactions, including image-based guidance.

Cons

Cookie preferences management can be confusing and difficult to save.
The website content is heavily focused on AWS, which might alienate users not within the AWS ecosystem.

Use Cases

1Rapid prototyping of AI-powered applications.
2Automating the generation of unit tests and documentation for AI models.
3Developing complex features in large codebases with AI assistance.
4Collaborating with AI agents on system design and architecture.
5Streamlining the transition from AI-generated code to production-ready software.

Who Should Use This?

👤AI Developers
👤Software Engineers
👤DevOps Engineers
👤Startup Founders
👤Product Managers

Kiro