Comparing Singularity with “every AI IDE” in a single article did justice to none of them. VS Code, Cursor, Devin and Conductor answer different needs: some extend an editor, some delegate a task to a cloud agent, others orchestrate several agents on the same machine. A five-column table blurred those differences.
This page therefore replaces our former grouped comparison with a series of in-depth articles: one competitor per article, each with a sourced overview, a ten-criterion table, the same scenario run in both tools, the competitor’s strengths, where Singularity differs, a trial protocol and an FAQ. Here you will find the map of the series and the reference points shared by every article.
Series checked on October 10, 2026 against each tool’s official documentation and Singularity’s own. It compares workflows, without speed or generated-code quality benchmarks. Plans, product names and prices change fast: every article lists its sources so you can verify them.
Four families of tools
IDEs extended with agents
VS Code with GitHub Copilot, JetBrains IDEs with Junie and Air and Zed start from an established editor and add agents. Their strength: you keep your habits, extensions and language tooling. The question is coordination: how do you follow several agent tasks at once and control how they are integrated?
AI-first IDEs
Cursor, Windsurf, now Devin Desktop, Google Antigravity and Kiro were designed around the agent: agent windows, remote execution, artifacts, specs. They bundle their own models and plans, which makes onboarding easy but often ties usage to their catalogue and credits.
ADEs and agent orchestrators
Paradev (formerly Superset), Conductor, Orca and Warp are Singularity’s closest neighbours: they run several agents in parallel, often in Git worktrees, with the CLIs and accounts you already have. The differences lie in the unit of work (session, workspace or ticket), review and how changes are integrated.
Providers’ own agents
Claude Code, OpenAI Codex and Devin are agents offered directly by their vendors, as a CLI, an app or in the cloud. Claude Code and Codex can also act as Singularity providers: the choice is then about the control surface, the vendor’s app or a ticket board.
Every comparison
| Tool | Family | What sets it apart | Detailed comparison |
|---|---|---|---|
| VS Code + GitHub Copilot | IDE with agents | The reference editor, with an Agents window, third-party harnesses and GitHub’s cloud agent. | Singularity vs VS Code + GitHub Copilot |
| JetBrains (AI Assistant, Junie, Air) | IDE with agents | JetBrains IDE code intelligence, extended by the Junie agent and the Air environment. | Singularity vs JetBrains (AI Assistant, Junie, Air) |
| Zed | IDE with agents | Open source Rust editor, parallel agent threads and external agents through ACP. | Singularity vs Zed |
| Cursor | AI-first IDE | VS Code-derived AI editor, Agents window, Cloud Agents and Bugbot. | Singularity vs Cursor |
| Windsurf / Devin Desktop | AI-first IDE | Windsurf, now Devin Desktop: a Kanban of local and cloud agents, Spaces and worktrees. | Singularity vs Windsurf / Devin Desktop |
| Google Antigravity | AI-first IDE | Google’s agent-first IDE: agent manager, artifacts and a driven browser. | Singularity vs Google Antigravity |
| Kiro | AI-first IDE | AWS’s IDE built on specs, steering and hooks, with an autonomous agent. | Singularity vs Kiro |
| Paradev (Superset) | ADE / agent orchestrator | Desktop app that runs your agent CLIs in local worktrees, with a diff viewer. | Singularity vs Paradev (Superset) |
| Conductor | ADE / agent orchestrator | Mac app running several agents in parallel, one workspace per branch. | Singularity vs Conductor |
| Orca | ADE / agent orchestrator | Open source ADE: a worktree, terminal and browser per task, pull-request-centric flow. | Singularity vs Orca |
| Warp | ADE / agent orchestrator | A terminal turned ADE, local and cloud agents, open source client. | Singularity vs Warp |
| Claude Code | Provider’s own agent | Anthropic’s agent as a CLI, extensions, desktop and web app; Singularity can drive it too. | Singularity vs Claude Code |
| OpenAI Codex | Provider’s own agent | CLI, IDE extension, cloud tasks and an app inside ChatGPT; Singularity can drive it too. | Singularity vs OpenAI Codex |
| Devin | Provider’s own agent | Cognition’s autonomous cloud agent that opens pull requests, with a CLI and Devin Review. | Singularity vs Devin |
Each row links to a full article. Families are a guide only: several tools overlap categories, and the line between IDE and ADE moves with every release.
What stays constant on the Singularity side
Every article describes Singularity with the same reference points, checked against its documentation:
- The ticket as the unit of work. The Kanban board is an execution surface: a ticket carries the description, priority and agent configuration; it keeps the activity, blockers, result and a short resolution. Child tickets, specialised roles and dependencies structure larger work (orchestration).
- Worktrees and rebase integration. In worktree mode, each ticket works in its own isolated Git copy; a commit queue serialises concurrent integrations. Settings define review and automation levels. Tests and review remain necessary: a worktree prevents neither conflicts nor regressions (worktrees).
- Your providers, your accounts. Adapters drive Claude Code, Codex, Copilot, Cursor, Gemini, Mistral and Ollama with your own subscriptions or keys. Model calls go wherever the chosen provider runs them (AI providers).
- A complete environment. Editor, terminal, graphical Git client, LSP, multi-project workspaces and plugins from its own marketplace (marketplace).
- A free application. Every feature is free; the Singularity Licence, at EUR 24 per month per workstation, only unlocks paid plugins such as Pipelines (pricing). Singularity is proprietary software.
How to choose
Rather than counting features, start from the way you work:
- You mostly write code yourself and want an assistant close to the code: an IDE with agents or an AI-first IDE is often the most direct option.
- You delegate long tasks and come back to a pull request: look at cloud agents (Devin, Cursor Cloud Agents, GitHub’s cloud agent, Codex cloud).
- You move several tasks forward in parallel on your machine: compare the orchestrators and pick the unit of work that suits you (session, workspace or ticket).
- You want every run tied to a request, its dependencies and its Git integration: that is where Singularity focuses.
A shared trial protocol
Before parallel trials, follow the worktree setup recipe: dependencies per checkout, ignored configuration, separate ports and databases, and sequencing for shared resources.
- Pick a representative task (for example a feature touching an API and its interface) and write the same acceptance criteria.
- Give it to each tool with the same model where possible, so you compare the workflow rather than the model.
- Measure the time spent preparing context, following progress, reviewing the diff and integrating the change.
- Rerun the test suite after integration and note the fixes required.
- Record the cost actually billed: application, subscriptions, credits and remote execution. Follow the before/after measurement protocol, including failures and review time.
Explore the getting started guide or download Singularity to run this trial on your own project.