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Side-by-side arena to compare AI coding models and build multi-file apps, with a public leaderboard and battle mode.
AI-powered code editor with agentic workflows for developers.
An on-device developer memory tool that auto-captures code, docs and context across apps so engineers can search and reuse it later.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
- ✦Head-to-head model comparison
- ✦Battle mode matchups
- ✦Public model leaderboard
- ✦Multi-file app generation
- ✦File uploads as input
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- ✦Automatic capture of code, docs and context across apps
- ✦Long-term memory engine for time-based search of past work
- ✦One-click save, search and AI-tagging of code snippets
- ✦Local, on-device processing with optional cloud sync
- ✦Plugin support for browsers and IDEs like VS Code
- ✦MCP integration with external LLMs for contextual answers
- ✦Automatic context-gathering from connected engineering sources
- ✦AI-generated code, tests and pull requests from tickets
- ✦Task planning that breaks complex work into subtasks
- ✦Auto-updating engineering documentation
- ✦Vector search over embedded project data
- ✦Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
- ✦Engineering productivity analytics dashboard
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- →Choosing the best coding model
- →Benchmarking AI code quality
- →Prototyping small apps
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow
- →Recalling code snippets and context from past coding sessions
- →Feeding accurate personal context into AI coding assistants
- →Keeping research notes and links without manual bookmarking
- →Preserving shared context across team collaboration tools
- →Engineering teams automating ticket-to-PR workflows
- →Developers wanting AI-assisted debugging and test generation
- →Engineering managers tracking AI-driven productivity gains
- →Teams centralizing documentation from scattered sources
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation