If you've seen GitHub Copilot, Cursor, and Claude Code mentioned in the same breath and felt confused about what separates them — you're not alone. These tools all involve AI and code, but they represent fundamentally different products that fit different points in your workflow.
Here's the map.
Category 1: AI Extensions
What they are: Add-ons that bolt AI capabilities onto your existing editor. You stay in VS Code, JetBrains, Vim, or wherever you already work — the extension just adds smarter completions, chat, and code generation inside it.
How they feel: Like having a knowledgeable colleague looking over your shoulder. You write; the AI assists. Every line you accept is one you consciously approved.
Examples: GitHub Copilot, Tabnine, Amazon Q Developer, Augment Code, JetBrains AI, Gemini Code Assist, Sourcegraph Cody, Blackbox AI.
Primary job: Inline code completion, chat, and agentic tasks (file editing, bug fixes) — all from within your current editor.
When to reach for an extension:
- You like your current editor and don't want to change it
- You want AI help throughout your coding day, not just for delegated tasks
- You're in a regulated industry and need on-premise options (Tabnine)
- You want the most widely supported IDE coverage (Copilot works in 10+ editors)
Key trade-off: Extensions enhance your editor but don't replace your workflow. You're still driving — the AI is riding shotgun.
Category 2: AI IDEs
What they are: Fully fledged editors built from the ground up (or forked from VS Code) with AI as a first-class citizen. Not a plugin — the AI is baked into the core editing experience.
How they feel: Like working in a future version of VS Code where the AI is everywhere, not bolted on. Features like multi-file editing, codebase-aware context, and agentic "Compose" or "Cascade" modes are native, not afterthoughts.
Examples: Cursor, Windsurf (now Devin Desktop), Trae, Kiro, Google Antigravity, Zed.
Primary job: Replace VS Code or your current IDE with a smarter version that deeply integrates AI into the editing loop.
When to reach for an AI IDE:
- You spend most of your day writing and editing code and want AI integrated into that flow
- You want multi-file editing and complex refactors to feel like a native feature, not a plugin
- You're comfortable switching editors and want the full experience, not a compromise
- You want inline completions and a powerful agent mode in one product
Key trade-off: You commit to a new editor. That's fine for many developers, but it's a meaningful switch — especially if your team has IDE standards or if you use an editor the AI IDEs don't cover.
Category 3: Coding Agents
What they are: Autonomous AI tools that run outside your editor and handle tasks end-to-end. You describe what you need; the agent reads your codebase, edits files, runs commands, debugs, and iterates — often without you watching every step.
How they feel: Like delegating a task to a capable junior developer. You hand it a ticket; it hands you back a pull request or a set of changes to review.
Examples: Claude Code, Codex (OpenAI), Devin, Gemini CLI, Aider, Warp (agent mode), Amp, OpenHands, Jules, Cosine.
Primary job: Handle a complete task autonomously — from understanding the goal to implementing and testing it — so you can work on something else in the meantime.
When to reach for a coding agent:
- You have a well-defined task you want to delegate entirely (add a feature, fix a bug, write tests)
- You want to parallelize: have the agent work on one thing while you work on another
- You're doing large-scale operations (refactors, migrations, adding tests to a legacy codebase) where you'd rather review diffs than write every line
- You prefer your own editor and don't want to switch IDEs, but still want powerful AI coding capabilities
Key trade-off: Agents are best for delegating, not for collaborative real-time coding. If you want to be in the driver's seat every step of the way, an agent is the wrong tool.
How the sub-types differ within agents
Not all coding agents work the same way. Two flavors worth knowing:
Interactive agents (Claude Code, Aider, Gemini CLI, Amp) run in your terminal, show you what they're doing as they go, and let you steer mid-task. You can interrupt, redirect, or ask questions.
Async agents (Codex, Jules, Cosine, Devin) work in cloud sandboxes. You assign the task, do other work, and review the result when it's done — like reviewing a PR from a contractor. Less visibility, more throughput.
The combination most experienced developers use
You don't have to pick one category. Most developers who've settled into an AI workflow use all three, for different things:
| Layer | Tool | Use |
|---|---|---|
| Daily coding | GitHub Copilot or JetBrains AI | Inline completions and quick chat |
| Editor | Cursor or Windsurf | Multi-file editing and AI Composer |
| Delegation | Claude Code or Codex | Autonomous task completion |
The pattern: use an extension or IDE for the moment-to-moment work, and an agent for chunks of work you can fully delegate.
Quick decision guide
"I don't want to change my editor" → Start with an AI extension (Copilot, Tabnine, Augment Code).
"I want the richest possible AI coding experience in a single product" → Try an AI IDE (Cursor, Windsurf).
"I want to delegate tasks and review results rather than code everything myself" → Try an interactive agent (Claude Code, Aider) or an async agent (Codex, Jules).
"I work across multiple repos and need the agent to understand all of them" → Look at Amp (Sourcegraph's multi-repo context) or Devin.
"I need something free and open-source" → Aider, Cline, OpenHands, Gemini CLI.
Related comparisons
- Claude Code vs Cursor — agent vs AI IDE, head-to-head
- Codex vs GitHub Copilot — async agent vs inline assistant
- Windsurf vs Claude Code — AI IDE vs terminal agent
- Tabnine vs Augment Code — two enterprise extensions compared