Code Completion

Completion remains suitable for casual day-to-day coding, with low latency, little distraction, and immediate use upon acceptance.

The work boundary of completion mode is: it ends once a suggestion is given, and it will not automatically modify based on error reports.

The essential difference between completion and an Agent lies in the unit of work: the unit of completion is a line of code, while the unit of an Agent is a task.

Traditional code completion can only predict the next line based on context.

Code completion scenarios are extremely sensitive to first-token latency, which differs from the optimization goals of batch code generation tasks.

Code completion and repository-level code understanding are capabilities of two different orders of magnitude: the former relies on local syntax patterns and common API calling habits, while the latter requires building cross-file symbol indexes, tracing function call chains, and identifying module dependencies.

Code completion is a speed-enhancement feature that may be replaced by intent-driven Agent interactions.

It is recommended to incorporate the Agent evaluation system into the regression testing process to quickly verify whether performance degradation has occurred after each model or prompt update

In actual programming assistance scenarios, simple code completion requests (such as variable naming, function signatures, and common pattern application) may account for as much as 70%–80% of the total.