This set builds vocabulary for describing collaborative, in-place AI editing surfaces for documents and code.
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At standup, a dev mentions using a side-by-side editing surface in ChatGPT where AI-suggested edits to a document or code file can be reviewed and applied selectively. Which feature fits?
Canvas provides a dedicated editing surface alongside the chat, where a document or code file can be revised collaboratively, with the model's suggested edits shown distinctly from the user's own changes. This differs from a plain chat reply that regenerates the entire response as unstructured text. It is designed for iterative document and code editing workflows.
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During a design review, the team wants to accept only specific AI-suggested edits within a longer document rather than the entire regenerated version. Which capability supports this?
Canvas supports selective edit review, letting a user accept or adjust specific suggested changes within a document rather than being forced to take an entire regenerated version wholesale. This granular control mirrors how a human editor might review tracked changes. It reduces the friction of re-prompting just to fix one unwanted portion.
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In a code review, a dev uses canvas to iteratively refine a function's logic while keeping the rest of the file untouched. Which use case does this represent?
Canvas is designed for targeted iterative editing, where specific portions of a document or code file can be refined across multiple turns while the rest remains stable. This focused editing reduces the risk of unrelated regressions elsewhere in the file compared to full regeneration each time. It supports a workflow closer to normal incremental code editing.
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An incident report shows a canvas-edited code file was copied into production without a final review of the applied changes. What practice would have prevented this?
Even though canvas visually distinguishes suggested edits, the final applied result should still be reviewed before being used in production, the same as any other AI-assisted code change. Visual clarity during editing doesn't substitute for a final correctness check. This caution applies broadly to any AI-assisted editing surface.
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During a PR review, a teammate asks how canvas differs from a normal back-and-forth chat conversation. What is the key distinction?
A normal chat conversation regenerates a full text reply each turn, while canvas maintains a persistent document that can be edited in place with visible, targeted changes. This makes canvas better suited to longer documents or code files that benefit from incremental refinement. The distinction is about workflow structure, not underlying model capability.