An AI coding assistant uses a language model to draft, explain, or change code from natural-language instructions and nearby project files. It can suggest a whole function, create tests, or describe unfamiliar code.
Traditional autocomplete uses the language server and static analysis. It mainly suggests real symbols, methods, and types that are valid at the cursor. Its suggestions are narrow but usually grounded in the codebase.
An AI assistant can invent new code, so it is more flexible but less reliable. It may use a missing API, misunderstand a requirement, or produce insecure code. Use autocomplete as a source of known facts and treat AI output as a draft that still needs review and testing.
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