XDA’s piece on Cursor this week made the unfashionable point: the tool got useful for the writer when they stopped using it to write code. The value sat in the planning, the scoping, and the review loops; the tab-completion side was the smaller half of the gain. The category of tools that handle the planning side of AI-assisted coding (not just the writing side) has grown fast in the past year. We tested 7 desktop apps that handle the planning, scoping, and review parts of an AI coding workflow.
What to look for in an AI code planning app
A few features separate the apps that help you ship from the ones that just autocomplete.
- A planning surface. A real “describe the task, sketch the plan, then execute” loop, not just inline completion.
- Multi-file awareness. The model should reason about a change across the whole codebase, not just the current file.
- Reviewable proposals. The plan and the diff should be inspectable before any code lands.
- Tool use. The model should be able to run tests, search the codebase, and read documentation as part of the plan.
- Bring-your-own-model support, for cost control and privacy.
- Terminal-native or editor-native, depending on your workflow.
Quick comparison
| App | Best for | Editor or terminal | Pricing | Standout feature |
|---|---|---|---|---|
| Cursor | Editor-native planning with Agent mode | Editor | Subscription | Composer and Agent in one IDE |
| Claude Code | Terminal-native autonomous coding | Terminal | Subscription | Best long-task autonomy in the category |
| Aider | Git-native pair programming in the shell | Terminal | Free (BYOK) | Each AI change is a clean git commit |
| GitHub Copilot Workspace | Plan-first workflow tied to issues | Web | Subscription | Spec, plan, implement, all from a GitHub issue |
| Plandex | Long-running coding plans with rollback | Terminal | Free (BYOK) | Branching plans with checkpoints |
| Sourcegraph Cody | Codebase-aware chat and edits across repos | Editor | Freemium | Best multi-repo context handling |
| Continue | Open-source AI in VS Code and JetBrains | Editor | Free (BYOK) | Full local-model support, swap providers freely |
The 7 best apps for AI code planning on desktop
1. Cursor — best editor-native planning with Agent mode
Cursor has anchored the AI-coding category for two years and the planning side is what keeps it ahead. The Composer flow handles multi-file edits with an inspectable diff before anything lands, and the Agent mode runs longer autonomous tasks that show their plan and their tool calls along the way. For users who want one tool that covers tab completion, multi-file edits, and longer autonomous tasks, the editor is the right surface.
The 2026 Cursor releases added longer agent-mode context windows and improved background task handling.
Where it falls short: Metered token pricing surprised heavy users in 2025. The VS Code fork can drift on extension compatibility.
Pricing: Subscription.
Platforms: Windows, macOS, Linux.
Download: cursor.com
Bottom line: Pick this when you want one IDE that covers writing, planning, and autonomous execution.
2. Claude Code — best terminal-native autonomous coding
Claude Code is the terminal client that turned long-running autonomous coding into a workflow that actually finishes tasks. Point it at a repo, describe what you want, and the model plans, edits, runs tests, and revises. The transcripts are inspectable, the per-task token reporting is honest, and the integration with the wider Claude product line (sub-agents, MCP, Skills) extends the workflow beyond writing code.
The 2025-2026 Claude Code releases added better long-task autonomy, sub-agent orchestration, and the routine system that lets you fire scheduled tasks.
Where it falls short: Terminal-native is a culture as much as a UI; users who want an editor surface will look elsewhere. The Anthropic subscription is the cost.
Pricing: Subscription.
Platforms: Windows, macOS, Linux.
Download: claude.com/code
Bottom line: Pick this when long autonomous tasks in a terminal are the workflow you want.
3. Aider — best Git-native pair programming in the shell
Aider is the open-source pair-programming tool that treats every AI change as a git commit. The model reads the repo, writes the change, runs your linter, and commits with a clean message. The discipline is the value: every iteration is a reviewable diff in your git history, and rollback is git revert.
The 2025 Aider releases improved repo-map context handling and added support for more model providers.
Where it falls short: Terminal-native. You write more prompts than in editor-native tools. The first session has a learning curve.
Pricing: Free; bring your own model API key.
Platforms: Windows, macOS, Linux.
Download: aider.chat
Bottom line: Pick this when you want every AI change to land as a clean git commit.
4. GitHub Copilot Workspace — best plan-first workflow tied to issues
GitHub Copilot Workspace is Microsoft’s plan-first interpretation of AI-assisted coding. Open a GitHub issue, click “Open in Workspace,” and Workspace produces a spec, a plan, and an implementation that you review at each stage before merging. The integration with the rest of GitHub (Actions, Pull Requests, Copilot Review) keeps the workflow inside the tools your team already uses.
The 2025 Workspace releases tightened the spec-to-plan and plan-to-code transitions and added stronger review prompts.
Where it falls short: Cloud-only. Tightly tied to GitHub, which is fine for most teams and a blocker for the rest. Requires Copilot subscription.
Pricing: Subscription (part of Copilot plans).
Platforms: Web (any OS).
Download: githubnext.com/projects/copilot-workspace
Bottom line: Pick this when your team already lives in GitHub Issues and Pull Requests.
5. Plandex — best long-running coding plans with rollback
Plandex treats AI-assisted coding as a long-running plan with branches and checkpoints. You describe the goal, Plandex breaks it into steps, executes each one in a sandboxed copy of your repo, and lets you review, accept, reject, or roll back at any point. The branching model handles the moment when an AI plan goes sideways better than most competitors: you keep the good steps and rerun the bad ones from a checkpoint.
The 2025 Plandex releases improved the multi-model orchestration and added stronger context budgeting on large codebases.
Where it falls short: Newer than Aider or Cursor; the community is smaller. Setup is heavier than dropping into Cursor’s chat.
Pricing: Free, open-source; bring your own model.
Platforms: Windows, macOS, Linux.
Download: plandex.ai
Bottom line: Pick this when long plans need branches and rollback you can trust.
6. Sourcegraph Cody — best codebase-aware chat across repos
Sourcegraph Cody wraps the Sourcegraph code search and intelligence engine in a chat and edit surface. The result is the strongest multi-repo context handling in the category: ask a question about a function and Cody finds the right callers across every repo Sourcegraph has indexed, not just the one in your editor. For monorepo and multi-repo teams, that scope is the differentiator.
The 2025 Cody releases extended agent-style autonomous flows and improved the JetBrains plugin parity with the VS Code extension.
Where it falls short: Best results need a Sourcegraph deployment. Free tier is real but the enterprise context is where the differentiation shows.
Pricing: Freemium, with paid Enterprise plans.
Platforms: Windows, macOS, Linux (VS Code, JetBrains extensions).
Download: sourcegraph.com/cody
Bottom line: Pick this when the codebase spans multiple repos and the AI needs to see all of them.
7. Continue — best open-source AI in VS Code and JetBrains
Continue is the open-source AI assistant that turns vanilla VS Code or JetBrains into a Cursor-style experience without the lock-in. Bring your own model: Anthropic, OpenAI, Mistral, a local Ollama instance, or any provider with an OpenAI-compatible endpoint. Inline edits, chat, and the experimental agent mode sit alongside the native editor features.
The 2025 v1 release stabilised the agent flow and added MCP tool support that matches Cursor’s MCP integration.
Where it falls short: Configuration sprawl is real; choosing models, embedders, and providers takes a setup session. The polish of the agent UX trails Cursor.
Pricing: Free, open-source; bring your own model bills.
Platforms: Windows, macOS, Linux (VS Code, JetBrains).
Download: continue.dev
Bottom line: Pick this when model choice and self-hosting matter more than out-of-the-box polish.
How to pick the right one
- If you want one editor that covers writing, planning, and autonomous execution: Cursor.
- If you want a terminal-native autonomous workflow: Claude Code.
- If you want every AI change to land as a clean git commit: Aider.
- If your team lives in GitHub Issues and Pull Requests: Copilot Workspace.
- If long plans need branches and rollback: Plandex.
- If the codebase spans multiple repos: Sourcegraph Cody.
- If model choice and self-hosting matter most: Continue.
Frequently asked questions
What is the best free AI coding planning tool?
Aider, Plandex, and Continue are all free (you bring your own model API key). Sourcegraph Cody has a real free tier for the editor extensions. Cursor and Claude Code are subscription products.
Can I plan a change without writing code?
Yes. Cursor’s Composer can produce a plan and a proposed diff without applying it. Copilot Workspace’s plan stage is explicit. Claude Code’s plan-mode runs the model in “draft a plan, do not execute” mode before any edits happen.
Which tool handles long-running tasks best?
Claude Code’s autonomous mode has the strongest long-task track record at the time of writing. Plandex’s checkpoint-and-branch model also handles long plans gracefully. Cursor’s Agent mode is closing the gap.
Do these work with a local model?
Continue and Aider both support local models through Ollama or any OpenAI-compatible endpoint. Plandex supports the same. Cursor, Claude Code, Copilot Workspace, and Cody are tied to their own model stacks.
Is “AI code planning” different from AI code completion?
Yes. Completion fills the next few characters. Planning describes what to change, scopes the work across the codebase, generates a reviewable diff or set of steps, and (in the strongest tools) executes them under your supervision. The XDA point holds: the planning side is where the real gain is.
