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Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Free browser-based pseudocode editor and compiler with exam-board syntax modes, aimed at computer science students and teachers.
Open-source terminal AI pair programmer that edits code in your local git repo and auto-commits, working with most LLMs.
No public pricing
No public pricing
No public pricing
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
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦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
- ✦Syntax highlighting and error checking for pseudocode
- ✦Cloud-based project saving across devices
- ✦Built-in pseudocode compiler for instant execution
- ✦Toggleable syntax rules for AQA, OCR, CIE, Edexcel and IB
- ✦AI tutor and code-to-language converters (Pro tier)
- ✦Bulk institutional licensing for schools and universities
- ✦Terminal-based AI pair programming
- ✦Edits code in your local git repo
- ✦Automatic git commits with messages
- ✦Codebase mapping for large projects
- ✦Works with cloud and local LLMs
- ✦Voice-to-code, image/web context, lint and test
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding 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
- →Students learning programming logic before writing real code
- →Teachers grading pseudocode assignments to exam-board specs
- →Exam preparation for computer science courses
- →Converting pseudocode into Python, C++ and other languages
- →Building features and fixing bugs via AI in the terminal
- →Working on large existing codebases
- →Automating git commits
- →Using local LLMs for private coding