Kiro

freemium

Agentic IDE from Amazon with spec-driven development.

Kiro is an agentic IDE from Amazon built on VS Code. It introduces spec-driven development — AI first writes specs and design docs before touching code. Features autonomous agents, hooks for automation, and deep AWS integration.

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kiro.dev
Kiro screenshot

Screenshot · kiro.dev

PricingFreemium
Price / month$20/mo
Free tierYes
Open sourceNo
Built onVS Code fork
ReleasedJuly 2025

Platforms

MacWindowsLinux

AI Models Supported

claudeamazon-nova

Key Features

  • Spec-driven development
  • Autonomous agents
  • Hooks (event automation)
  • Steering documents
  • AWS integration
  • MCP support

News — Amazon Web Services

product updateAmazon Web Services

AWS launches Managed Knowledge Base for Bedrock with 6 enterprise connectors and automatic ACL enforcement

Amazon Web Services launched Managed Knowledge Base for Bedrock in general availability, offering a fully managed retrieval solution with six native enterprise connectors including SharePoint, Confluence, and Google Drive. The service handles document parsing up to 500 MB for PDFs, 2 GB for audio, and 10 GB for video, with real-time access control list verification at query time.

2 min read
product updateAmazon Web Services

Amazon Nova Act Brings Vision-Based Web Navigation to UX Testing, No Hard-Coded Scripts Required

AWS has released a cloud-deployed UX testing platform built on Amazon Nova Act, a multimodal foundation model that navigates web interfaces through visual understanding rather than hard-coded selectors. The solution processes documentation with Claude 4.5 Sonnet to generate test scenarios, executes parallel testing via ECS, and analyzes results automatically, addressing the scalability limitations of manual testing and maintenance overhead of traditional automation tools.

3 min read
product updateAmazon Web Services

AWS SageMaker HyperPod adds three-tier data capture, direct Hugging Face deployment, and NVMe caching for enterprise inf

Amazon SageMaker HyperPod has launched infrastructure updates for enterprise inference workloads. The platform now captures inference data at three points—endpoint, load balancer, and model pod—with configurable sampling and S3 storage. Teams can deploy models directly from Hugging Face Hub without pre-staging weights, with support for gated access across vLLM, TGI, and SGLang runtimes.

3 min read

AWS introduces rDPO unlearning technique to reduce false content moderation in Amazon Nova models by 53 percentage point

AWS has developed Reverse Direct Preference Optimization (rDPO), a novel unlearning technique that reduces over-deflection in Amazon Nova models by up to 53 percentage points. The approach allows organizations to selectively adjust content moderation safeguards while preserving general model capabilities through LoRA adapters.

2 min read