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 established tools like GitHub Copilot, Google Gemini Code Assist, or Cursor?
As AI coding assistants evolve from simple autocomplete tools into fully agentic systems, a new category of IDEs is emerging — ones that help you plan, structure, test, and ship code end-to-end.
This article provides a deep, technical comparison between AWS Kiro, GitHub Copilot Agent Mode, Google Gemini Code Assist, and Cursor, focusing on their features, workflows, and usage in real-world developer contexts.
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.
Pricing
| 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 |
Do You Need to Pay for AWS Bedrock Separately?
No, unless you configure Kiro to use your own Bedrock models:
- ✅ Default setup (e.g. Claude Sonnet) → included in Kiro’s pricing
- ⚠️ Custom models via .kiro/agents.yaml → billed separately by AWS
- ⚠️ External Bedrock calls via CLI/plugins → also billed by AWS
👉 For most users, there's no extra Bedrock cost unless you opt into advanced configurations. Beware with this.
When to Use Which Tool
| 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 and Cons of 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
How to Use Kiro Effectively ?
Kiro introduces a workflow that differs from traditional IDEs. To get the most out of it, it's worth adapting your habits slightly to embrace its agentic, spec-driven model.
Installation & Setup
Kiro is currently in public preview and can be installed locally:
brew install aws/tap/kiro # macOS
kiro login # authenticate via AWS Builder ID, IAM, or GitHub
You can also download platform-specific installers from kiro.dev.
For the authentication, Kiro supports:
- AWS Builder ID
- IAM roles
- GitHub or Google accounts
If you're deploying or using Bedrock models (e.g., Claude Sonnet), you’ll need AWS credentials configured locally via aws configure.
Project Bootstrapping
You can start from scratch or use an existing codebase. In either case, run:
kiro init
This command:
- Sets up the .kiro/ directory (for agent config and steering rules)
- Creates empty spec files (
requirements.md,design.md, etc.) - Connects your repo to Kiro's agent backend
Using Agents to Build Features
With Kiro running, press Cmd+K (or via Command Palette) and describe a feature:
"Build a CRUD REST API for invoices with validation and automated tests."
Kiro will:
- Generate a plan (
tasks.md) - Write or scaffold relevant code across files
- Propose tests, docs, and infra (if enabled)
- Apply your .kiro/steering coding standards
You can refine behavior via config:
# .kiro/steering/rules.yaml
rules:
- prefer_lib: zod
- enforce_test_coverage: true
- infra: terraform
Pre-Commit Quality Hooks
Kiro can automatically:
- Run unit tests (npm test, pytest, etc.)
- Lint your codebase
- Check security rules (via integrated scans)
- Regenerate documentation
By default, these hooks run on:
- File save
- Git commit
Configure hook behavior in .kiro/config.yaml.
Infrastructure Integration
Kiro supports scaffolding with:
- AWS CDK
- AWS SAM
- Terraform
Example :
kiro infra add dynamodb-table --stack invoice-db
Kiro can then deploy the stack using your local AWS credentials or CloudFormation pipeline.
Continuous Agent Workflows
Kiro agents aren't just for code generation, they can:
- Monitor task progress
- Keep specs up to date
- Detect stale or undocumented changes
- Suggest updates when your code diverges from the plan
Use:
kiro sync
To refresh your spec and design files based on recent code edits.
Tips
- Start every feature with a description, not just code — Kiro thrives on intent.
-
Use
.kiro/steeringto define how your team writes code. - Let agents run tests and scans early — they'll prevent issues from escalating.
- Adopt it gradually — it plays nicely with existing tools, including Git, VS Code, and AWS CLI.
Final Thoughts
Kiro isn’t trying to replace Copilot — it’s targeting a different layer of software engineering. Where Copilot and Gemini are productivity tools, Kiro is a structure enforcer. It brings planning, design, QA, and infra together in a single, AI-supported loop.
For teams building long-lived, production-grade applications — especially in AWS environments — Kiro offers strong value.
That said, if your needs are exploratory, fast-paced, or centered on legacy code, tools like Copilot or Cursor may remain more flexible.
What Do You Think?
Have you tested Kiro? Planning to?
Feel free to share your thoughts in the comments — real-world feedback is essential to evaluate how tools like this actually change development workflows.
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