Code Assistant Checklist

No, strict policy: Claude Code can run locally with code staying on the developer's machine (code context is sent to the API for inference but not stored for training). GitHub Copilot Business has a zero-retention policy. Cursor Team routes through their servers -- verify their data policy meets your requirements. For maximum control, consider self-hosted open-source alternatives (Continue, Tabby) though capability is lower.

Yes, with enterprise-grade protections: All four options commit to not training on your code on business/enterprise plans. This is sufficient for most organizations.

Yes: GitHub Copilot Enterprise, Anthropic (Claude Code), and OpenAI (Codex) are SOC 2 Type II certified. Verify Cursor's current certification status -- it's a newer company and certifications are evolving.

No: All options are viable. Move on.

Yes: GitHub Copilot Enterprise includes IP indemnification. Microsoft backs this. OpenAI and Anthropic offer indemnification on certain enterprise plans. Cursor's indemnification terms depend on which underlying model is used.

Not a priority: Move on.

VS Code: GitHub Copilot has the deepest VS Code integration. Cursor is a VS Code fork so extensions and keybindings carry over. Claude Code and Codex work alongside any IDE via terminal.

JetBrains (IntelliJ, PyCharm, WebStorm): GitHub Copilot has a JetBrains plugin. Cursor is VS Code only. Claude Code and Codex are IDE-agnostic (terminal-based).

Vim/Neovim/Emacs: Claude Code works natively in terminal. GitHub Copilot has a Neovim plugin. Codex is terminal-based. Cursor doesn't apply.

Mixed IDEs across team: Claude Code and Codex have an advantage here -- they work the same regardless of editor. GitHub Copilot covers the most IDEs via plugins. Cursor requires everyone to switch editors.

Inline autocomplete while typing: GitHub Copilot and Cursor are strongest here. Real-time suggestions as you type with tab-to-accept. Claude Code and Codex focus on larger tasks rather than line-by-line completion.

Multi-file edits and refactoring: Claude Code and Codex excel at this -- they can read your full codebase and make coordinated changes across many files. Cursor's agent mode also handles multi-file edits. GitHub Copilot's multi-file capability is more limited.

Autonomous task completion: Claude Code and Codex can take a task description and independently implement it -- reading files, writing code, running tests, and iterating. This is a different paradigm from suggestion-based tools.

Code review and explanation: All four tools handle this well. Claude Code and Codex can review entire PRs. GitHub Copilot has a dedicated chat panel. Cursor integrates review into the editor.

Small to medium (under 100K lines): All options work well. Not a differentiator.

Large monorepos (100K+ lines): Claude Code handles large codebases well -- it can navigate and understand extensive codebases through its context window and file reading. Codex operates in sandboxed environments with your repo cloned in. GitHub Copilot and Cursor primarily use local file context and may not capture cross-repo dependencies as effectively.

Predictable per-seat: GitHub Copilot and Cursor charge a flat monthly rate per developer. Easy to budget. No surprises.

Usage-based: Claude Code and Codex charge based on API usage (tokens processed). Cost scales with actual usage. Light users cost less, heavy users cost more. Harder to predict monthly spend but often cheaper for teams that don't use AI constantly.

Need to cap costs: Per-seat tools inherently cap costs. For usage-based tools, both Anthropic and OpenAI allow you to set spending limits. Monitor closely for the first month to establish baseline usage patterns.

JavaScript/TypeScript, Python, Java, Go, Rust: All four tools perform well with mainstream languages. Not a differentiator for common stacks.

Niche or legacy languages (COBOL, Fortran, proprietary DSLs): GitHub Copilot has the broadest language coverage due to training data from GitHub. Claude Code and Codex handle many languages but may have less depth on rare ones. Test with your specific language before committing.

Multiple languages in one codebase: Claude Code and Codex handle polyglot repos well since they can read and reason about the full project structure. GitHub Copilot and Cursor provide suggestions based on the file you're currently editing.