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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.
No public pricing
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No public pricing
No public pricing
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Unified encrypted inference endpoint
- ✦Multi-agent parallel execution
- ✦CLI, IDE, and API access
- ✦App builder and remote coding agents
- ✦Chairman LLM output evaluation
- ✦35+ IDE integrations
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Automating refactors, tests, and migrations
- →Running competing AI coding agents
- →Building apps from prompts
- →Integrating agents into CI/CD