What is Amazon Kiro and how does it help developers?

Amazon Kiro is an AI-powered integrated development environment (IDE) launched by AWS, designed to assist developers with spec-driven development and autonomous project management. It uses AI agents to generate and maintain code, project plans, and specifications, making cloud-native development easier and more efficient.

How does GitHub Copilot support coding tasks?

GitHub Copilot is an AI code assistant powered by OpenAI’s Codex models. It provides real-time code completions, suggestions, and can help write complex code snippets across many programming languages directly in popular code editors like VS Code.

What unique features does JetBrains AI offer in its IDEs?

JetBrains AI integrates advanced machine learning features within JetBrains IDEs, including smart code completion, error detection, and refactoring suggestions. It supports a broad range of programming languages and is designed to enhance developer productivity and code quality.

What capabilities does Cursor IDE bring to AI-assisted development?

Cursor IDE is a developer-centric AI tool that focuses on improving code navigation, repository-level debugging, and multi-file management with AI assistance. It leverages AI to help developers understand and modify large codebases more effectively.

Which AI-powered IDE is best for cloud-native development?

Amazon Kiro is optimized for cloud-native development, especially within the AWS ecosystem. Its spec-driven approach and autonomous agents make it ideal for managing complex cloud projects and infrastructure-as-code workflows.

Can these AI IDEs be integrated into popular development environments?

Yes, GitHub Copilot integrates seamlessly with editors like Visual Studio Code, JetBrains AI features are built into JetBrains IDEs, and Cursor IDE offers its own standalone tools. Amazon Kiro is designed for AWS environments but aims to integrate with common developer workflows.

AI-Powered IDEs Comparison: Amazon Kiro vs GitHub Copilot vs JetBrains AI vs Cursor IDE

Overview of AI-Powered Coding IDEs

Amazon Kiro uses Anthropic Claude via AWS Bedrock for spec-driven development. GitHub Copilot leverages OpenAI GPT-4 for inline code completion. JetBrains AI Assistant supports multiple models including GPT-4, Claude, and Gemini. Cursor IDE provides project-wide indexing with frontier AI models.

Amazon Kiro IDE

AI Model

Anthropic Claude 3.7 Sonnet and Claude 4 via AWS Bedrock

Key Features

Spec-driven development workflow
VS Code-based desktop application
Large codebase handling through project steering files
Deep AWS integration
20k-line project capability tested

Pricing

Free preview: 50 AI actions per month. Planned: Pro $19/month, Pro+ $39/month

Strengths

Excellent for large, complex projects
Automated planning and documentation
AWS cloud integration
Context-aware development

Limitations

Early stage, rough around edges
Requires internet connectivity
Manual approval needed for AI actions
Slower than some competitors

GitHub Copilot

AI Model

OpenAI Codex and GPT-4 for advanced features

Key Features

Inline ghost-text completions
VS Code and JetBrains integration
Chat panel for natural language queries
Broad language and framework support
Sub-second response times

Pricing

Free: 2000 completions + 50 chat messages/month. Pro: $10/month. Pro+: $39/month

Strengths

Most widely adopted AI coding assistant
Fast, responsive completions
Excellent language coverage
Lightweight integration

Limitations

Limited context window
Requires open files for context
May be distracting with constant suggestions
Generic suggestions without full project context

JetBrains AI Assistant

AI Model

Multiple: OpenAI GPT-4.1, Anthropic Claude 3.7, Google Gemini 2.5 Pro, local LLMs

Key Features

Deep IDE integration across all JetBrains products
Offline mode with local models
Multi-file editing capabilities
Smart actions for tests and refactoring
Web search integration

Pricing

AI Free tier: unlimited local models, limited cloud usage. AI Pro/Ultimate: higher quotas included in subscriptions

Strengths

Native IDE integration
Offline capability
Multiple model support
Generous free tier

Limitations

Requires JetBrains IDE
Inline completions less fluid than Copilot
Heavy usage requires expensive subscriptions
Still catching up in UX details

Cursor IDE

AI Model

Supports all frontier models: GPT-4.1, Claude Sonnet/Opus, Gemini Pro, plus custom models

Key Features

Built-in project indexing (1-15 minutes)
Up to 1M token context in Max Mode
AI Composer for multi-file editing
VS Code fork with AI-first design
Cross-file reasoning and refactoring

Pricing

Hobby: Free (limited). Pro: $20/month. Ultra: $200/month. Teams: $40/user/month

Strengths

Excellent for large codebases
Comprehensive project understanding
Advanced multi-file capabilities
Privacy mode available

Limitations

Can be slow with large context
Autocomplete accuracy issues reported
Requires internet connectivity
Limited free tier

Side-by-Side Comparison

Feature	Amazon Kiro	GitHub Copilot	JetBrains AI	Cursor IDE
AI Model	Claude 3.7/4	Codex/GPT-4	Multi-model	All frontiers
Large Projects	Excellent	Good	Good	Excellent
Context Window	Spec-based	Open files	IDE context	Up to 1M tokens
Offline Mode	No	No	Yes	No
Free Tier	50 actions/month	2000 completions	Unlimited local	Limited

Best Use Cases

Amazon Kiro

Large-scale enterprise projects, AWS-integrated development, teams requiring structured spec-driven workflows

GitHub Copilot

General-purpose development, quick prototyping, developers wanting fast inline completions

JetBrains AI Assistant

JetBrains ecosystem users, offline development, privacy-conscious teams, multi-language projects

Cursor IDE

Large codebase refactoring, cross-file editing, developers switching from VS Code

Performance Metrics

Response Time

GitHub Copilot: Sub-second completions
JetBrains AI: Fast for single-file operations
Cursor IDE: Variable, depends on context size
Amazon Kiro: Slower due to spec processing

Accuracy

Amazon Kiro: High for large projects with specs
GitHub Copilot: Good for visible context
JetBrains AI: Improving, especially for typed languages
Cursor IDE: Variable, some accuracy issues reported

Conclusion

Each AI-powered IDE serves different development needs. Amazon Kiro excels at structured, large-scale development with AWS integration. GitHub Copilot provides the most mature inline completion experience. JetBrains AI Assistant offers flexibility with offline capabilities. Cursor IDE leads in project-wide AI understanding but with some accuracy trade-offs.

Selection depends on project size, preferred workflow, cloud integration needs, and budget considerations. All tools continue rapid development in 2025.