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One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
AI coding assistant for editors and IDEs that explains, refactors, documents, and generates code across 56 languages.
Aide helps developers code faster with parallel agents and automated workflows.
Free practical deep-learning courses, the fastai library and a book that make state-of-the-art AI accessible to coders.
Free trial available
No public pricing
Free trial available
No public pricing
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦Bug detection and fix suggestions
- ✦Code and CSS framework conversion
- ✦Unit test and documentation generation
- ✦Regex, SQL query, and CI/CD pipeline generation
- ✦Code explanation and style checking
- ✦Editor extensions for VS Code, Sublime, JetBrains, Visual Studio
- ✦Parallel Agents for faster coding
- ✦GitHub native integration
- ✦Automated PR workflow
- ✦Smart PR suggestions
- ✦Automatic code reviews
- ✦Real-time progress tracking
- ✦Free deep learning courses
- ✦fastai library for PyTorch
- ✦nbdev development tool
- ✦Practical Deep Learning book
- ✦Blog on AI, ethics and technical topics
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
- →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
- →Generating unit tests for existing functions
- →Refactoring legacy code to modern practices
- →Producing inline documentation automatically
- →Learning new programming languages or concepts via AI explanations
- →Automating code reviews
- →Generating PRs automatically
- →Improving code quality through continuous improvements
- →Learning deep learning as a coder
- →Building models with the fastai library
- →Following AI research and ethics writing