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I can’t truthfully claim that I personally went six months without opening VS Code: the available evidence does not document an author’s own workflow or results. What it does show is that coding work can now move between an editor, a terminal, a desktop app, and cloud sessions—and that this changes where developers review and steer work, not whether they need to do so.
Does AI mean you can stop using VS Code?
No. It means you can choose to do more of the directing and review outside the editor. VS Code’s official guide still describes a complete agent workflow inside the editor: keep the conversation alongside code, inspect edits as they happen, and use the debugger, terminal, and tests in the same environment. It also covers assigning tasks and tracking multiple agent sessions. Copilot, Claude, and Codex are listed as supported agent-harness examples; availability depends on extensions, accounts, and product configuration. Microsoft’s VS Code guide presents an editor-centered approach, not a requirement that every coding task happen there.
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What changes when the agent works outside the editor?
Terminal-based repository work
Codex CLI documents a workflow that starts in a repository: the agent explores files, plans a change, edits code, and can run local development tools. The developer reviews commands and diffs, with permission controls shaping what the agent can do. The documentation also describes scripting and CI use, local review, and handing work to cloud sessions. This moves the interaction surface to the terminal, but the repository and the resulting changes still need inspection. OpenAI recommends Git checkpoints around tasks so changes can be reviewed and recovered deliberately. Codex CLI documentation explains the terminal loop and its controls.
Moving between interfaces
OpenAI’s February 2026 Codex app announcement describes moving among CLI, web, an IDE extension, and a dedicated app. Work can be handed between those surfaces, and changes can be reviewed before opening them in an editor for manual edits. That is a shift in where a developer starts or checks a task—not evidence that the editor has become obsolete. OpenAI’s Codex app announcement describes these access points.
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What do adoption figures actually say?
In Flutter’s Q2 2026 community survey, 66% of respondents selected VS Code and 32% selected Claude Code. The same survey reported Android Studio at 40%, Antigravity at 23%, GitHub Copilot at 19%, Cursor at 18%, and Codex at 17%. Respondents could select multiple tools, so these figures overlap: they are not exclusive market shares and do not establish that developers moved from VS Code to an agent. They describe Flutter community respondents, not all developers. Flutter’s survey report gives the context for the selections.
What can workplace studies tell us about productivity?
Anthropic surveyed 132 of its engineers and researchers and interviewed 53 in August 2025; its report was published December 2, 2025. Employees estimated that Claude was used for 59% of their work and reported an average productivity gain of 50%. In the same internal survey, 55% said they used Claude daily for debugging, 42% for understanding code, and 37% for implementing features. These are self-reports from one AI company’s workforce, not independently measured productivity gains or a forecast for other teams. Anthropic itself says productivity is difficult to measure and notes possible perception bias. Anthropic’s report describes the study and its limitations.
The report also classified 8.6% of Claude Code tasks in its internal usage data as “papercut fixes.” That figure reflects Anthropic’s own task classification; it is not an estimate of how much work agents handle across developers or products.
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Why task type matters more than a universal winner
A 2026 study by Giovanni Pinna, Jingzhi Gong, David Williams, and Federica Sarro analyzed 7,156 pull requests associated with five coding agents. In its revised paper, documentation-task acceptance was 82.1% and new-feature acceptance was 66.1%. Acceptance varied by task and agent, and no evaluated agent led in every category. These results describe the paper’s sampled pull requests and acceptance measure; they do not guarantee quality in a particular repository or show that one agent will fit every workflow. The study’s revised arXiv paper provides its task-stratified analysis.
What should a workflow keep in place?
Whether the agent is beside the code, in a terminal, or in a separate app, the core loop is delegation followed by review. A useful workflow keeps the human responsible for checking what changed and whether it works:
- Give the agent a bounded task and enough repository context to act on it.
- Use permissions and approvals appropriate to the task; do not treat an agent’s ability to run commands as a reason to skip oversight.
- Inspect the diff and commands before accepting changes.
- Run relevant tests and use debugging tools when needed; a plausible explanation or successful edit is not proof that the change is correct.
- Keep Git checkpoints so you can isolate, compare, or revert work.
The interface can change the friction of starting work, keeping context, and reviewing edits. The evidence here does not establish that abandoning VS Code improves productivity, or that a developer can safely stop checking code. It supports a narrower conclusion: agent-assisted work can be organized around different interfaces, while review and verification remain part of the job.
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