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Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
No public pricing
Free trial available
No public pricing
- ✦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
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦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
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Prompt-to-app full-stack generation
- ✦Built-in backend, database and auth
- ✦One-click integrations (Slack, Notion, HubSpot, etc.)
- ✦Instant hosting and custom domains
- ✦Superagents for automated workflows
- ✦GitHub sync and code export
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →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
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks
