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Kiro AI
✓ verifiedFreemium
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
3.8M visits/mo
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Void Editor
✓ verifiedFree
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
Pricing
Basic: $0/month
Pro: $20/month
Team: $49/month
Free: $0/mo (50 credits)
Pro: $20/user/mo (1,000 credits)
Pro+: $40/user/mo (2,000 credits)
Pro Max: $100/user/mo (5,000 credits)
Power: $200/user/mo (10,000 credits)
No public pricing
No public pricing
No public pricing
Core features
- ✦Integration with Notion databases
- ✦Unlimited fields and submissions
- ✦Customizable form styling
- ✦Conditional logic and validation rules
- ✦Ready-made form templates
- ✦File uploads
- ✦Multi-page forms
- ✦Email, Slack, and Discord notifications
- ✦Submission editing
- ✦Form protection (password, captcha)
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
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- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
Use cases
- →Guest blog submission forms
- →Event attendee check-in forms
- →Customer satisfaction surveys
- →Patient intake forms
- →Photography quotation requests
- →Equipment rental requests
- →Photo shoot permit requests
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help
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