AI Code Review
VS Code
Amartya Jha
• 08 July 2025
Before You Dive Into AI Coding Assistants, Lock Down Your Code Security
What Is CodeAnt AI?
What CodeAnt AI Helps You Do
Why This Matters If You’re Using AI Code Tools
Best GitHub Copilot Alternatives
1. Tabnine
Privacy-first AI coding assistant with over 9 million VS Code installs that puts data protection above everything else. Unlike most competitors, Tabnine never stores or trains on your code, offering self-hosting options for enterprises.
Beyond basic autocomplete, it provides AI chat, specialized agents for testing and documentation, and can even create custom models trained exclusively on your company's private codebase.
Pros:
Your code stays private - self-hosting options and zero data retention guarantee
Custom AI models trained on your company's codebase for personalized suggestions
Beyond autocomplete - includes AI chat, test generation, and legacy code explanation
Works with 20+ languages and integrates seamlessly with major IDEs
Cons:
Can be resource-heavy, sometimes using 40GB+ memory on large multi-language projects
Best features require paid plans - free tier only gives 50 daily completions
Pricing:
Free Plan, Enterprise ($39/month), Dev Plan available ($9/month).
Tip to use:
If you're handling sensitive code, use the self-hosted option and train custom models on your private repos for the most relevant suggestions without privacy risks.
2. Codeium (now Windsurf)
The "modern coding superpower" that shook up the market with unlimited free AI completions. Recently rebranded as Windsurf, this tool supports 70+ programming languages and has gained 2.8 million VS Code installs by offering what competitors charge for.
It's known for frighteningly accurate multi-line predictions and has ranked as the 4th most admired AI tool in Stack Overflow surveys, even beating Google Gemini and Meta AI.
Pros:
Completely free unlimited code completions forever - no daily limits or credit systems
Exceptional autocomplete accuracy that often predicts complex algorithms with surprising precision
Massive language support covering 70+ programming languages and frameworks
Integrated chat interface for code generation, explanation, and refactoring without leaving VS Code
Cons:
Occasional "hallucinations" where generated code can be unusable or overly complex
Chat interface sometimes has "amnesia" issues, forgetting context between sessions
Pricing:
Free (unlimited completions), Pro ($15/month), Teams ($30/month), Enterprise ($60/month)
Tip to use:
Leverage the unlimited free completions for rapid boilerplate generation and save the paid chat features for complex problem-solving to maximize value.
3. Amazon CodeWhisperer (now Amazon Q Developer)
Amazon's AI coding assistant that's been integrated into the broader Amazon Q Developer platform, designed for enterprise tasks beyond just coding.
Built on billions of lines of Amazon's internal code and open-source training data, it offers deep AWS ecosystem integration with real-time code suggestions and robust security scanning.
The tool emphasizes responsible AI usage with features like license attribution for open-source code and "shift-left" security capabilities for early vulnerability detection.
Pros:
Deep AWS integration with context-aware suggestions for services like Lambda, S3, and CloudFormation
Built-in security scanning for Python, Java, and JavaScript with 80% accurate vulnerability detection
Open-source reference tracking that identifies similar code and provides license attribution for compliance
Free tier available with no AWS account required, including basic CLI completions
Cons:
AI capabilities perceived as less sophisticated compared to newer frontier models like GPT-4
Security scanning limited to only three programming languages currently
Pricing:
Free (50 chat interactions), Pro ($19/month with higher limits as mentioned at Spotsaas). As you know amazon Amazon-related services have complex pricing; check the website for proper understanding.
Tip to use:
Perfect for AWS-heavy development - leverage the integrated security scanning and ecosystem-specific code suggestions to build secure, compliant cloud applications.
4. Cursor
AI-first code editor built directly on the VS Code codebase, offering seamless migration of your existing settings, extensions, and keybindings. Known for "magic" tab completion and deep codebase understanding, Cursor can predict your next edit and comprehend entire projects for intelligent multi-file changes.
It's positioned as a comprehensive AI pair programmer that can generate complete functions and project documentation from context.
Pros:
Native AI integration provides more seamless experience than basic extensions
Exceptional multi-line tab completion with accurate developer intent prediction
Comprehensive codebase understanding for intelligent project-wide edits and Q&A
One-click VS Code migration maintains familiar environment while adding powerful AI features
Cons:
May lag behind official VS Code updates, causing compatibility issues with newer extensions
Resource-intensive, especially when processing large codebases, occasionally causing performance lag
Pricing:
Free (limited), Pro ($20/month), Ultra ($200/month), Teams ($40/user/month), Enterprise (custom)
Tip to use:
Use the one-click VS Code settings import, then leverage Agent Mode for complex multi-file editing tasks that benefit from deep codebase context.
5. Replit Ghostwriter
AI-powered coding assistant deeply embedded within Replit's browser-based IDE, designed to accelerate the journey from idea to working prototype.
Unique for its cloud-native approach, Ghostwriter can generate fully functional applications from high-level inputs or even screenshots, with proactive debugging that identifies and suggests fixes for bugs in real-time.
It's particularly valuable for educational purposes and rapid web-based prototyping.
Pros:
Complete cloud IDE eliminates local setup complexity, accessible from any browser
Rapid prototyping capabilities can transform ideas or screenshots into deployable applications
Excellent learning tool for beginners with insights into coding patterns and best practices
Built-in collaboration features enable real-time teamwork on projects
Cons:
Limited direct VS Code integration - core AI features are confined to Replit platform
Credit consumption for debugging AI-generated bugs can lead to expensive "constant fights" with the AI
Pricing:
Free Starter (limited AI, 3 public projects), Replit Core ($20/month), Teams ($35/user/month), Enterprise (custom)
Tip to use:
Ideal for educational projects and rapid web prototyping, but monitor credit usage carefully when debugging to avoid unexpected costs.
6. OpenAI Codex Playground (via VS Code extension)
Direct access to OpenAI's foundational Codex models through VS Code extensions, offering the core technology that powers many AI coding tools. Codex is optimized specifically for software engineering tasks using reinforcement learning on real-world coding challenges. It aims to function as a "programmer co-worker" that can autonomously plan and execute complex development tasks with minimal human input.
Pros:
Powered by state-of-the-art OpenAI models specifically optimized for software engineering
Agentic capabilities designed to function as autonomous programmer co-worker
Effective for targeted task automation like fixing typos and generating utility functions
Potential for high-level workflow integration handling planning, implementation, and testing
Cons:
User experience immaturity with unpredictable wait times and GitHub connection issues
Limited internet access restricts autonomous research capabilities, requiring manual environment setup
Pricing:
Usage-based through OpenAI API - GPT-4.1 ($2-8 per million tokens), GPT-4.1 mini ($0.40-1.60 per million tokens)
Tip to use:
Best for experimental use and specific development tasks, but monitor token usage closely and be prepared for manual environment setup complexities.
7. Phind
AI-powered search engine and coding assistant that combines traditional web search with generative AI to deliver rich, visual answers to technical questions.
Functions as a "pair programming agent" that intelligently browses the web, asks clarifying questions, and performs recursive problem-solving.
The VS Code extension integrates with your codebase to automatically identify relevant code sections for debugging assistance.
Pros:
Hybrid search and AI approach provides up-to-date information with comprehensive technical solutions
VS Code extension automatically identifies relevant code sections for efficient debugging assistance
Agentic problem-solving with dynamic tool selection and multi-step reasoning capabilities
Free tier provides access to GPT-4 powered model for evaluation before subscription
Cons:
Significant privacy concerns - default behavior potentially publishes user queries and code publicly
AI frequently asks too many or irrelevant clarifying questions, disrupting development workflow
Pricing:
Pro ($20/month) and Business Plan ($40/month/user)
Tip to use:
Essential to subscribe to paid plan with data opt-out enabled when working with proprietary code, and provide explicit prompts to minimize unnecessary questioning.
8. Zed.dev AI
High-performance code editor built from scratch in Rust, designed to be the "world's fastest AI code editor" with native AI integration and real-time collaboration.
Features innovative "agentic editing" capabilities and uses a transparent, open-source approach including proprietary open-source LLM called Zeta.
Emphasizes exceptional performance with minimal typing latency while providing deep AI integration through its Agent Panel.
Pros:
Exceptional performance with blazing-fast speed and minimal typing latency, often outperforming VS Code
Native AI integration through Agent Panel enables deep collaboration between human and AI developers
Open-source and transparent with support for custom models and user-controlled API keys
Privacy-centric design with conversations private by default and no data collection for training
Cons:
Standalone editor requiring adoption of new IDE, losing VS Code's extensive extension ecosystem
Still considered work-in-progress with less mature features like Git integration and language support
Pricing:
Personal (Free, 50 prompts monthly), Pro ($20/month, 500 prompts), Enterprise (custom pricing)
Tip to use:
Ideal for developers prioritizing raw editor speed and privacy-focused AI experience, especially when using your own API keys for cost and data control.
9. Magic AI (Kilo Code)
Open-source AI agent extension for VS Code offering multiple operational modes including Orchestrator, Architect, Code, and Debug.
Features experimental autocomplete, AI-generated commit messages, and custom workflows with emphasis on automatic failure recovery and hallucination-free code through integration with documentation tools.
Operates on transparent pay-what-you-use model for LLM tokens without taking commission.
Pros:
Completely open-source with transparent pay-what-you-use pricing model for LLM tokens
Advanced agentic workflows with Orchestrator Mode for breaking complex projects into subtasks
Automatic failure recovery designed to detect and fix errors without manual intervention
Hallucination-free code approach using documentation lookup tools for more reliable output
Cons:
Operational instability with AI getting stuck in loops or confusing working directories
Limited autocomplete functionality when using external AI providers
Pricing:
Open source (free), pay directly for LLM tokens, $20 free credits to start, Enterprise (custom pricing)
Tip to use:
Leverage Orchestrator or Architect modes for complex multi-step development tasks, utilizing automatic failure recovery for more robust AI-driven development.
10. Codiga
Real-time static code analysis tool integrated directly into VS Code, providing instantaneous feedback with every keystroke. Offers automated fixes for vulnerabilities and coding issues with single-click resolution, along with customizable rule creation for team-specific coding standards.
Features a Code Snippets Hub for discovering and sharing reusable code patterns across development teams.
Pros:
Real-time static analysis provides immediate feedback and automated fixes for vulnerabilities
Customizable rule sets enable teams to create and enforce specific coding standards
Cross-platform consistency ensuring uniform code quality across IDEs and CI/CD pipelines
Explicit privacy guarantee that code is never stored or used for system training
Cons:
Limited language compatibility may not support every programming language
Subscription required for advanced features, potentially creating cost barriers for smaller teams
Pricing:
Free (basic features), Teams ($12-14/month with full repository support and dedicated pipelines)
Tip to use:
Define custom code analysis rules matching your team's standards for real-time feedback and automated fixes directly in your VS Code workflow.
11. Blackbox AI
Real-time code completion and debugging assistant claiming "World's Fastest AI Code Autocomplete" at 200 milliseconds response time.
Offers comprehensive AI features including code chat, generation, commenting, explanation, and unique capabilities like README generation and commit message creation. Supports integration with multiple AI providers and includes generous free tier for individual developers.
Pros:
Exceptionally fast autocomplete with 200ms response time for rapid code generation
Comprehensive AI feature suite including chat, generation, commenting, and project setup guidance
Smart context understanding of project structure with relevant setup suggestions
Generous free tier offering unlimited completions and chat usage for normal usage patterns
Cons:
Occasional AI hallucinations generating incorrect or outlandish solutions requiring manual review
Privacy concerns as cloud-only service sending code to external servers without self-hosted options
Pricing:
Free (unlimited basic usage), Pro ($7.99/month), Business ($29.99/month), and Ultimate from $99.99/month. Also has 90 day free trial.
Tip to use:
Leverage exceptionally fast autocomplete for boilerplate code and quick refactoring, but always review generated code due to hallucination potential.
12. DeepCode (Snyk Code)
AI-powered security analysis tool integrated into Snyk Code, providing real-time code scanning and automated vulnerability remediation directly within VS Code.
Specializes in identifying, automatically fixing, and prioritizing security vulnerabilities using neural networks trained on millions of lines of code.
Features 80% accurate security autofixes with a hybrid AI approach combining symbolic and generative AI.
Pros:
Purpose-built AI specifically designed for secure development with vulnerability detection and autofix capabilities
Hybrid AI approach combining symbolic and generative AI for high accuracy and minimal hallucinations
Shift-left security integration enables early issue identification and resolution in development process
No customer data used for training, with models trained exclusively on permissively licensed open-source projects
Cons:
User interface complexity when managing large volumes of vulnerabilities with filtering and sorting challenges
Limited automated fix support for inter-file changes, focusing only on single-file corrections
Pricing:
Free, Team ($25/month), Enterprise (custom pricing with automated fixes)
Tip to use:
Integrate into VS Code workflow for proactive security scanning and AI-powered autofixes to address vulnerabilities during development rather than post-deployment.
13. Sourcery
Real-time code quality enhancement tool focusing primarily on Python, JavaScript, and TypeScript with AI chat assistant that understands codebase context.
Provides on-demand code reviews, automated GitHub and GitLab PR reviews, and continuous quality feedback with scoring system.
Can generate Mermaid diagrams, comprehensive unit tests, and detailed code explanations for optimization.
Pros:
Real-time refactoring suggestions directly in IDE for immediate code quality improvements
Comprehensive quality feedback with function scoring and sub-scores for length, complexity, and working memory
AI chat with codebase context for questions, improvements, diagrams, tests, and explanations
Free tier available for open-source projects with Pro features included
Cons:
Performance issues in VS Code with reports of slow or unusable extension behavior
Language specificity limiting utility for developers working outside Python, JavaScript, and TypeScript environments
Pricing:
Open Source (Free for public repos), Pro ($12/month annually), Team ($24/month), Enterprise (custom pricing)
Tip to use:
Consistently apply real-time refactoring suggestions and monitor quality scores within VS Code to address maintainability issues before committing changes.
14. CodiumAI (now Qodo)
Quality-first generative AI coding platform rebranded as Qodo, supporting all programming languages with integrated AI chat, code completion, and test generation. Focuses on generating meaningful tests, improving code quality, proactively uncovering bugs, and streamlining pull request processes. Features automated code review through "Qodo Merge" for enhanced development workflows.
Pros:
Quality-first approach emphasizing reliable code generation with fewer bugs and comprehensive test coverage
Broad language support compatible with virtually all programming languages for versatile development needs
Strong privacy and security posture with SOC2 certification, SSL encryption, and no data retention policy
Extensible agentic coding workflows with Model Context Protocol tooling for integration with external services
Cons:
Inconsistent code quality with reports of unusable or overly complex generated code requiring manual rework
Customer support issues including reports of ignored support requests and delayed assistance
Pricing:
Developer (Free, 250 credits monthly), Teams ($30/user/month, 2500 credits), Enterprise ($45/user/month)
Tip to use:
Prioritize test generation capabilities to quickly increase coverage and uncover bugs, particularly for newly developed functions or classes.
15. GPT Pilot (Pythagora)
Core technology behind Pythagora VS Code extension, designed as a "real AI developer companion" capable of writing full features, debugging, and discussing issues.
Focuses on building fully working, production-ready applications with human oversight, suggesting AI can handle approximately 95% of coding tasks.
Employs multi-agent architecture with specialized agents for implementation, quality checks, and documentation.
Pros:
Full application generation capabilities including front-end and back-end components for complete projects
Iterative development approach with step-by-step coding and real-time debugging as issues emerge
Multi-agent architecture with specialized agents for implementation, review, troubleshooting, and documentation
Scalability for large projects through intelligent code context filtering for relevant processing
Cons:
Early stage maturity with operational issues including rate limits, WSL compatibility problems, and project loading difficulties
Dependency on human oversight for critical 5% of work, meaning not fully autonomous development yet
Pricing:
Free Plan (limited), Pro ($49/month for individuals and small teams), Premium ($89/month), Enterprise (custom)
Tip to use:
Leverage multi-agent approach for iterative full-stack development, but be prepared for human oversight and intervention during complex challenges.
16. AskCodi
AI assistant integrated across IDEs with context-awareness and customizable shortcuts, requiring API key from AskCodi web application for full functionality. Provides chat interface, natural language code suggestions, and specialized mini-apps for specific development tasks. Features broad AI capabilities including documentation, explanation, testing, and integration with multiple LLM providers.
Pros:
Broad AI capabilities including chat, code suggestions, documentation, explanation, and test generation
Context-aware assistance understanding project structure with conversation history maintenance
Privacy-focused design ensuring generated code is not saved for user confidentiality
Multi-model support providing access to various LLMs including Gemini, Claude, and GPT-4o
Cons:
Long response times causing delays that hinder development workflow fluidity
Inconsistent code quality often requiring manual corrections and gap-filling for complex segments
Pricing:
Premium ($149.99/year, 500 AI credits monthly), Ultimate ($349.99/year, 1500 AI credits monthly)
Tip to use:
Leverage context-aware features for quick code explanations and documentation, but be prepared to iteratively refine output for accuracy and completeness.
17. Sourcegraph Cody
AI coding assistant with over 685,000 VS Code installs, designed to work with any programming language using broad LLM training data.
Known for deep codebase context understanding across multiple files, enabling project-wide insights and intelligent assistance.
Offers comprehensive AI features including agentic chat, autocomplete, inline editing, and customizable Prompt Library for tailored workflows.
Pros:
Deep codebase context understanding enabling highly relevant AI assistance for complex projects
Multi-model support allowing users to select preferred LLMs including Claude Sonnet 4 and GPT-4o
Comprehensive AI feature suite with agentic chat, autocomplete, inline editing, and custom prompts
Enterprise-ready with flexible deployment options and support for large-scale security requirements
Cons:
Performance issues including slow code generation and inconsistent suggestion quality
Integration is perceived as less seamless compared to GitHub Copilot due to underlying API limitations
Pricing:
Enterprise starter - $19/month/user, Enterprise Search - $49/month/user.
Tip to use:
Leverage deep codebase context understanding for large multi-file projects to obtain relevant AI suggestions and accelerate code reviews.
Conclusion
Look, there's no shortage of AI coding tools anymore. We've covered 17 solid options, and honestly, most of them are pretty good at what they do.
The market is flooded with choices - from Codeium's unlimited free completions to Tabnine's privacy-first approach, from Cursor's project-wide understanding to specialized tools like Snyk Code for security.
Each one has its strengths.
The thing is: almost every tool on this list has a free plan or trial. So don't overthink it. Download a few, try them on your actual projects, and see what clicks with your workflow.
Maybe Codeium's autocomplete feels natural to you. Maybe Cursor's codebase understanding is a game-changer for your complex projects. Maybe you discover that combining two different tools gives you the perfect setup.
The only way to know what works for you is to test them. Your coding style, your projects, your team setup - it's all different. What works amazingly for someone else might not fit your workflow at all.
Bottom line:
Pick 2-3 tools from this list. Try their free versions for a week each. Keep what helps, ditch what doesn't.
The best AI coding assistant is simply the one that makes your day easier.
One more thing
- while you're speeding up your coding with these tools, don't forget about code reviews. All that faster coding means more pull requests to review. If your team is getting swamped with reviews, CodeAnt.ai automatically handles the grunt work - summarizing changes, catching issues, and suggesting fixes.
Most teams cut their review time in half. Worth checking out if PRs are piling up.
Till next time.
Thanks for Reading.
