Visual Studio Code’s marketplace is packed with AI helpers that turn natural language prompts into code, explain legacy projects, and automate tests. We tested the leading options through late 2024 across Python, JavaScript, TypeScript, Rust, and infrastructure stacks. Here are the AI tools worth installing.
Quick Picks
- GitHub Copilot & Copilot Chat: Best overall autocomplete and inline explanations.
- Codeium: Free alternative with strong TypeScript/JavaScript support and enterprise features.
- Continue.dev: Open-source chat agent customizable with your own models.
- Tabnine: Privacy-focused completions with on-prem deployments.
- Pieces for Developers: AI-enhanced snippet manager integrating research and code references.
GitHub Copilot + Copilot Chat
GitHub Copilot pairs OpenAI models with context-aware suggestions as you type. The Copilot Chat extension adds side-panel conversations, test generation, and built-in commands for explanation and refactoring.
- Standout features: Supports multi-file context, test case prompts, and knowledge of GitHub issues/pull requests.
- Pricing: $10/month for individuals, free for verified students and open-source maintainers.
- Best for: Developers who already use GitHub repos and want tight integration.
- Get it: Install Copilot
Codeium
Codeium offers free unlimited autocompletion with server-side AI plus optional paid teams features. Install the VS Code extension, sign in, and you can access chat, refactor commands, and multi-line completions.
- Standout features: Supports 70+ languages, custom models for enterprise, and “Codeium Chat” that references your current file.
- Pricing: Free for individuals; enterprise tiers add self-hosting and SSO.
- Best for: Teams that need a fast, no-cost AI assistant to get started.
- Get it: Install Codeium
Continue.dev
Continue (formerly Continue.dev) is an open-source extension that turns VS Code into an AI playground. It lets you connect to OpenAI, Anthropic, or open-weight models hosted on your own server. You can create custom commands that run shell snippets, search docs, or orchestrate multi-step prompts.
- Standout features: Slash commands (
/edit,/test), multi-file context selection, and Git integration. - Pricing: Free. Costs depend on the model API you choose.
- Best for: Developers who want full control over data privacy and model choice.
- Get it: Install Continue
Tabnine
Tabnine focuses on privacy-first AI coding assistance. You can run models locally or in a private cloud, ensuring code never leaves controlled environments. Tabnine supports completion, code review suggestions, and knowledge base search.
- Standout features: Supports on-device inference for select languages, integrates with JetBrains and IDEs beyond VS Code.
- Pricing: Free starter tier with basic completions; Pro starts at $12 per user/month, Enterprise negotiable.
- Best for: Regulated industries and teams with strict compliance requirements.
- Get it: Install Tabnine
Pieces for Developers
Pieces combines AI note-taking, snippet management, and context recall. The VS Code extension recognizes code you copy, surfaces related resources, and lets you query your own snippet library via Pieces Copilot.
- Standout features: Offline-friendly embeddings, AI-generated commit message suggestions, and integration with browser extensions.
- Pricing: Free individual tier; paid plans unlock collaborative workspaces.
- Best for: Developers who research often and want AI-assisted knowledge capture.
- Get it: Install Pieces
Honorable Mentions
- Aider: Command-line first tool with VS Code integration for refactoring via GPT-style models.
- Supermaven: Fast completions with minimal latency, popular among Rust developers.
- Sourcegraph Cody: Great for exploring large mono-repos; pairs best with Sourcegraph’s code intelligence.
- Ponicode (Smart Tests): AI-assisted unit test generation for JavaScript/TypeScript.
How to Evaluate AI Tools for Your Team
- Privacy & compliance: Check data retention policies and whether you can opt out of model training.
- Language support: Confirm support for your primary stack (backend, infrastructure, mobile).
- IDE performance: Monitor CPU and memory usage—heavy extensions can slow VS Code on older laptops.
- Collaboration features: Shared chat history, knowledge bases, and inline comments can improve team adoption.
Best Practices When Using AI Coding Assistants
- Review every suggestion. AI can hallucinate APIs or produce insecure code.
- Use unit tests and linters to verify generated code before merging.
- Keep secrets out of prompts—mask API keys and proprietary formulas.
- Capture feedback. Encourage teammates to thumbs-up/down suggestions so the tool improves for your org.
Getting Started Checklist
- Update VS Code to the latest version for API compatibility.
- Install one AI assistant at a time to evaluate impact before stacking multiple tools.
- Configure keybindings or slash commands that match your workflow.
- Document approved tools and prompt guidelines in your team’s playbook.
Frequently Asked Questions
Do I need multiple AI extensions? Start with one primary assistant. Add others only to cover gaps like testing or documentation.
Will AI replace code reviews? No. Treat AI as a pair-programming partner. Human review remains essential for architecture and security.
Is there an offline option? Tabnine and Continue with local models provide offline or on-premises setups.
Final Thoughts
AI helpers inside VS Code can shave hours off repetitive work when used responsibly. Pick the extension that fits your compliance needs, train it on your codebase, and keep humans in the loop for quality control.