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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.
Free browser-based pseudocode editor and compiler with exam-board syntax modes, aimed at computer science students and teachers.
AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦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
- ✦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
- ✦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
- →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
- →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
- →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