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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsCode completion suggests code as you write; an AI coding agent takes on a broader task, gathers project context, makes changes through available tools, and can respond to the results. The practical difference is how much work you delegate and how you review it—not a hard boundary between product types. Many development environments offer both workflows.
How code completion works
Code completion is suggestion-led. While you are editing, the tool offers code—often inline in the editor—for you to accept, reject, or adapt. You remain responsible for directing the work and applying the suggestion. In its guide to AI workflows, Visual Studio Code distinguishes getting code suggestions while typing from asking an agent to find relevant code, make changes, and run tests.
A completion can be more than a single token or line. What defines the workflow is that it proposes code in the flow of your editing rather than taking responsibility for a larger sequence of project actions.
How an AI coding agent works
An agent is task-led. You describe an outcome—such as fixing a failing test—and the agent can investigate relevant files and error output, edit code, run commands or tests, inspect what happened, and iterate. The exact tools and permissions depend on the product and its configuration; an agent should not be assumed to inspect every file or run every test automatically.
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GitHub describes IDE agent mode as an interactive workflow that can select files, edit them, run commands, and iterate, while letting the developer inspect and steer the changes. This is an example of the agent pattern, not a guarantee that every agent has identical capabilities.
Compare the workflow, not the product label
| Dimension | Code completion | AI coding agent |
|---|---|---|
| Task scope | Suggestions during a local coding task, such as completing an expression or function. | A request that may require several steps or changes across files. |
| Context gathering | Works in the context of your editing and the information available to the completion feature. | May actively locate relevant project files and use command or test output as context. |
| Action | Proposes code for you to accept, reject, or adapt. | May edit files and invoke terminal or other tools, subject to its capabilities and permissions. |
| Iteration | You decide what to do with the suggestion and make any follow-up changes. | Can respond to command or test results and try further changes. |
| Control and review | You control whether suggested code enters your file. | You may need to review a diff or worktree, steer the agent, approve commands, or undo changes; automation settings affect the exact controls. |
| Typical fit | Quick coding flow or a narrow, local edit. | A well-defined task that needs investigation and several actions. |
These are workflow tendencies, not fixed thresholds. An agent can make one focused edit, and a completion feature can suggest multiple lines. To understand what a particular product will do, check the selected mode and its permissions rather than relying on the word “agent.”
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Many tools offer a spectrum of AI workflows
A single development environment may provide inline suggestions, focused edits, chat, planning, and agent modes. Those options differ in how much context they gather and how much action they take on your behalf. Visual Studio Code’s workflow guide separates suggestions while typing, focused inline edits, planning, and working with an agent.
For a larger task, planning mode can be useful when you want to inspect an approach before edits begin. For a small change, a suggestion or focused edit may keep you closer to the code and avoid delegating unnecessary work. Choose based on the task and the control you want, not on a claim that one mode is universally better or faster.
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Choose the right mode for the task
- Use completion when you are already writing code and want a suggestion to finish or adapt.
- Use a focused edit when you know the location and nature of a limited change but want help applying it.
- Consider an agent when the request spans steps or files and requires investigation, tool use, or reacting to test output.
- Start with a plan when you want to assess the proposed approach before allowing changes.
For example, you could ask an IDE agent to fix a failing test. In the workflow documented by VS Code, the agent can use the failure information to find relevant code, make changes, run tests, and iterate. That makes an agent a plausible fit for the multi-step job; it does not remove your responsibility to check that the fix is sound.
What autonomy means for review and safety
An agent’s ability to act does not mean it is reliably correct or should be left unchecked. It can make mistakes or go off track. Review the changes it made and the results of commands or tests, and steer or undo work when needed. VS Code’s announcement describes visible tool calls and undo while warning that an agent can make mistakes.
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Command approval is also configuration-dependent. GitHub documents default command approval and notes that administrator or editor settings can allow automatic execution. Check the settings for your environment instead of assuming every command will always prompt you first.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.IDE agent mode is not the same as a cloud coding agent
“Agent” can refer to different workflows. IDE agent mode works interactively in the editor: you can inspect progress and steer the agent as it works. GitHub’s cloud coding agent is a separate, asynchronous workflow oriented around an issue and a pull request. GitHub’s June 13, 2025 article explains this distinction. It is a distinction between two agent workflows, not the basic difference between an agent and code completion.
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Availability depends on the product and setup
Agent modes are not available in every editor or account under identical conditions. GitHub’s documentation lists Visual Studio Code, Visual Studio, JetBrains IDEs, Xcode, and Eclipse for its agent mode, while noting that product and organization settings can affect availability. Check the current documentation and your organization’s configuration for the specific tool you use.
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