This content originally appeared on DEV Community and was authored by Meidi Airouche
AWS has released Kiro, a new AI-powered IDE with built-in agentic workflows, specification generation, and cloud integration. But how does it compare to other popular tools like GitHub Copilot, Google Gemini Code Assist, or Cursor?
AI coding assistants have rapidly moved from autocomplete tools to more autonomous systems capable of planning, writing, testing, and even deploying code. In this context, AWS introduced Kiro, an IDE that claims to bring structure and end-to-end AI integration to software development.
This article offers a deep, technical comparison between Kiro, GitHub Copilot Agent Mode, Google Gemini Code Assist, and Cursor, focusing on concrete features, workflows, and real-world developer use cases.
What is AWS Kiro?
Kiro is an AI-native IDE developed by AWS, built as a customized fork of VS Code (based on Code-OSS). It focuses on specification-driven development and provides out-of-the-box support for:
- Agent-assisted task decomposition,
- Automatic generation of technical specifications (
requirements.md,design.md, etc.), - Integration of infrastructure as code (AWS CDK, SAM, Terraform),
- Built-in hooks for tests, documentation, and security checks.
Kiro works locally and integrates with AWS services (Bedrock, IAM…), but it can also be used in other environments (e.g., with GitHub or local repos).
Feature Comparison
| Feature Category | Kiro (AWS) | Copilot Agent (GitHub) | Gemini Code Assist (Google) | Cursor (Anysphere) |
|---|---|---|---|---|
| Spec Generation |  Automatic requirements.md, design.md, tasks.md
|
 No automatic spec generation |
Manual via chat |
 Prompt-based only |
| Code Agent | Plans and implements across multiple files |
Handles multi-file context |
Assisted actions, test generation |
Contextual refactoring and commands |
| Pre-Commit Hooks | Built-in test, lint, doc, security checks |
Manual setup or external tooling |
Reactive suggestions only |
Partial automation |
| Infrastructure Gen | Supports AWS CDK, SAM, Terraform |
Requires separate configuration |
No infra scaffolding features |
Not infra-oriented |
| IDE Integration | Native VS Code fork |
Official VS Code extension |
VS Code, IntelliJ, Android Studio |
Custom VS Code fork |
| Cloud Alignment |  AWS-native (IAM, Bedrock) |
 GitHub + Azure |
Google Cloud oriented |
Cloud-agnostic |
| Steering/Rules | .kiro/steering for project coding norms |
Prompt-defined preferences only |
No native steering |
Custom plugins or config |
| MCP Support | Yes |
No |
Yes |
No |
Workflow differences
A key difference between these IDEs is how much structure they impose or support.
Kiro:
- You define a goal or description.
- Kiro generates structured specs (requirements, design).
- It decomposes tasks and assigns them to agents.
- On save or commit, it can run tests, linting, documentation generation, and security scanning.
- Optionally scaffolds infrastructure code with IaC tools.
GitHub Copilot Agent Mode:
- You prompt it in chat or command mode.
- It generates code and can make edits across multiple files.
- It’s highly reactive but requires manual steering.
Gemini Code Assist:
- Offers code suggestions, test generation, and chat interface.
- CLI (Gemini CLI) supports shell commands and task automation.
- It’s focused on augmenting the developer rather than enforcing structure.
Cursor:
- Focused on large-scale code refactoring, search, and editing.
- Excellent for legacy or unfamiliar codebases.
- Less opinionated — leaves decisions to the developer.
Pricings
| Plan | Kiro | Copilot Pro | Gemini Free | Cursor |
|---|---|---|---|---|
| Free | 50 agent tasks/month | |
~180k completions |
|
| Pro | \$19/month (1k tasks) | \$10/month | – | \$20–\$30/month |
| Pro+ | \$39/month (3k tasks) | Enterprise pricing | Enterprise plans | Enterprise pricing |
When to use what
| Use Case | Best Fit | Reasoning |
|---|---|---|
| Structured app development | Kiro | Provides specs, infra scaffolding, QA hooks |
| Rapid prototyping / GitHub-native | Copilot Agent | Integrated in GitHub and VS Code, great for agile teams |
| Personal or lightweight usage | Gemini | Free, minimal setup, multiplatform |
| Legacy code or refactoring | Cursor | Advanced context navigation and editing capabilities |
Pros & Cons about Kiro
Pros :
- Structured dev flow (design → tasks → code → deploy)
- Agentic hooks (test, lint, scan on save/commit)
- Infrastructure-as-code support
- Ideal for production environments
Cons :
- Currently in preview; evolving rapidly
- Requires AWS Builder ID / IAM role for full integration
- Interaction quotas tied to pricing tiers
Conclusion
Is Kiro a Copilot alternative?
Yes, but it’s targeting a different layer of the dev process. While Copilot and Gemini enhance developer productivity, Kiro imposes structure, enforces good practices, and tries to integrate every phase from planning to deployment.
For developers working in regulated environments, teams that need standardization, or cloud-first projects (especially on AWS), Kiro can add significant value.
However, for quick hacks, side projects, or legacy code navigation, other tools may be faster or better suited.
And you ? what do you think?
As it’s pretty new, don’t hesitate to share your feedback in comment. It will be precious to build a better opinion about this tool !
This content originally appeared on DEV Community and was authored by Meidi Airouche