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Use both, for different jobs. An IDE’s editing, navigation, debugging and project tools give you direct control; AI completion, chat and agents add suggestions or take on bounded work. Keep routine precision work in your hands, use AI where it helps, and review any changes or commands an agent proposes. No cited evidence establishes one workflow as a universal productivity winner.
What is the difference between an AI assistant and an IDE?
A traditional integrated development environment (IDE) is the workspace where you edit and navigate code, inspect a project, and use development tools such as debugging. An AI coding assistant adds generated code suggestions, conversational help, and, in some setups, agents that can work across project files.
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These are complementary layers, not mutually exclusive choices: AI features can run inside an IDE. The available features depend on the IDE, its extension and the relevant release. GitHub’s feature matrix lists capabilities across supported IDEs; check it against your own setup rather than assuming every editor offers the same tools.
Which approach should you use for each task?
| Task or need | Best starting point | Why |
|---|---|---|
| Make a precise, small change or inspect behavior closely | IDE editing and debugging tools | You control the changes directly and can follow the project’s behavior as you work. |
| Fill in a small, local piece of code | Inline AI completion | Accept, revise or reject a suggestion immediately; read it before keeping it. |
| Understand unfamiliar code or discuss an approach | Chat or Ask mode | Ask for an explanation or bounded suggestion while keeping edits in your hands. GitHub says Ask can be used to understand code without modifying the project. |
| Complete a clearly defined task spanning steps or files | Agent mode, selectively | An agent can identify files to change, offer edits and terminal commands, and iterate on issues. Review its work before accepting it. |
| Learn an unfamiliar codebase or verify a delicate change | IDE navigation, inspection and debugging, optionally with chat | Keep the project’s structure and observed behavior visible; use AI as an aid rather than a substitute for checking. |
How to delegate work to an agent without giving up control
- Choose a task with a clear result. Break vague work into a bounded request that you can verify, especially when it touches several files.
- Check the feature in your exact environment. Availability varies by IDE and extension release; consult the current feature matrix for your setup.
- Inspect streamed edits. GitHub’s documentation describes reviewing agent changes and accepting or rejecting proposed commands. Command execution can be configured to run automatically, so check that setting before relying on an approval prompt.
- Verify the result in the project. Use your normal review, tests and debugging workflow to confirm the change does what you asked.
- Check current usage terms. GitHub says each agent prompt consumes GitHub AI Credits; confirm the allowance and terms that apply to your account.
GitHub describes the intended use this way: “Use agent mode when you have a specific task in mind and want to enable Copilot to autonomously edit your code.” — GitHub Docs, Using agent mode in your IDE.
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What does the evidence say about productivity?
JetBrains Research’s April 15, 2026 study analyzed two years of telemetry from 800 developers: 400 classified as AI Assistant users and 400 non-users, based on observed assistant use during the study period. It examined 151,904,543 logged events, including typed characters, debugging starts, delete and undo activity, external paste events and IDE activations; the researchers also surveyed 62 developers and conducted interviews.
The study reported that AI users increased typed characters by almost 600 per month, compared with an average increase of 75 characters per month among non-users. That is a measure of typing behavior, not proof of faster delivery, better code quality or a causal productivity gain. The researchers describe the work as identifying workflow patterns, not establishing causal effects.
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A separate JetBrains Research paper identified as January 2026, published for ICSE-SEIP ’26, interviewed 35 professional developers across adopter, churner and non-user groups and used an internal prediction market of 102 practitioners to assess 12 desired features. It reports alignment around implementation and context-awareness features, while proactivity and maintenance were underestimated and technically unaddressed in its analysis. This is evidence about developer needs and perceived feasibility, not a product comparison.
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How common is AI coding—and what does that tell you?
JetBrains’ 2026 Developer Ecosystem Survey report says its tenth survey received responses from more than 15,000 professional developers worldwide and was statistically reweighted. For May–July 2026, it reports that 90% of professional developers used AI coding agents at work at least weekly and 68% daily. These are self-reported adoption figures, not a controlled measure of effectiveness or a recommendation for your workflow.
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The same report shows that workplace tool use changed over the periods it compared: Claude Code was around 39% in May–July 2026, up from 18% in January 2026; GitHub Copilot was 21% in May–July 2026, compared with 29% a year earlier; and Cursor was 12% in May–July 2026, compared with 18% in January 2026. It also reports 9% used JetBrains AI in IDEs and/or Junie at work. These survey figures describe reported use among the survey’s population, not code quality, a head-to-head ranking or what will suit an individual developer.
Quick Recap
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A practical decision rule
- Need exact control? Work directly in the IDE, using navigation, editing and debugging tools.
- Need a small suggestion? Try inline completion, then inspect the result.
- Need an explanation or options? Ask chat for bounded help while you make the change.
- Need several coordinated edits? Consider an agent when you can state the task clearly and review its changes and any commands.
- Unsure whether a feature is available or affordable? Verify the IDE and extension release, plus the current usage or credit terms, before building your workflow around it.
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